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Wireless sensors in agriculture and food industry—Recent development and future perspective
Abstract
This paper presents an overview on recent development of wireless sensor technologies and standards for wireless communications as applied to wireless sensors. Examples of wireless sensors and sensor networks applied in agriculture and food production for environmental monitoring, precision agriculture, M2M-based machine and process control, building and facility automation and RFID-based traceability systems are given. The paper also discusses advantages of wireless sensors and obstacles that prevent their fast adoption. Finally, based on an analysis of market growth, the paper discusses future trend of wireless sensor technology development in agriculture and food industry.
... (6) Radio Frequency Identification (RFID): this technology is used primarily for tracking and identification purposes. In the case of the agri-food industry, Wang et al. (2006) and Ruiz-Garcia et al. (2009) observe how the combination of RFID tags, sensors and IoT allows the setup of wireless sensor networks for data acquisition and processing. ...
... (3) The identification and tracking cluster essentially considers the combination of blockchain technology with identification technologies such as RFID tags to ensure product traceability (Ruiz-Garcia and Lunadei, 2011;Wang et al., 2006). There are two main objectives. ...
... The use of IoT systems and smart sensor networks could guarantee the safety of the products during the storage and transport phases. Information systems and IT software could be used to speed up the transition of products from cultivation to the retail stage, reducing losses and preventing low-quality products from reaching the market (Ruiz-Garcia et al., 2009;Wang et al., 2006). Despite the possible advantages, the successful implementation of such innovations depends on the ability to manage the relationships between the actors in the supply chain, both in terms of information flows and in terms of process coordination. ...
Purpose
This study aims to analyse how the adoption of Industry 4.0 technologies can help different types of agri-food supply chains introduce and manage innovations in response to the challenges and opportunities that emerged following the COVID-19 pandemic.
Design/methodology/approach
A systematic literature review methodology was used to bring together the most relevant contributions from different disciplines and provide comprehensive results on the use of I4.0 technologies in the agri-food industry.
Findings
Four technological clusters are identified, which group together the I4.0 technologies based on the applications in the agri-food industry, the objectives and the advantages provided. In addition, three types of agri-food supply chains have been identified and their configuration and dynamics have been studied. Finally, the I4.0 technologies most suited for each type of supply chain have been identified, and suggestions on how to effectively introduce and manage innovations at different levels of the supply chain are provided.
Originality/value
The study highlights how the effective adoption of I4.0 technologies in the agri-food industry depends on the characteristics of the supply chains. Technologies can be used for different purposes and managers should carefully consider the objectives to be achieved and the synergies between technologies and supply chain dynamics.
... An intelligent sensor usually consists of a sensing device, a signal conditioning, a computational block, and a communication block [4]. Furthermore, sensors with wireless communication capabilities are the key to the wireless sensor network for smart sensing [5]. For instance, in agricultural applications [6], wireless sensor nodes are distributed in farmland. ...
... The dynamic model of UAV in this part can be extended to multi-rotor UAVs by adding the extra angular velocities from additional rotor blades in (5). The number of angular velocities is equal to the number of rotors. ...
... As mentioned in the BLDC-motor dynamic section, the angular velocity of the blades ω i should be acquired firstly. This can be carried out by substituting coefficients (A11) and (A12), desired torque M d (q d ) and desired force T d (q d ) in the trajectory and force section into (5) in the UAV dynamic model section. Then, (5) can be rewritten as: ...
Quadrotor unmanned aerial vehicles (UAVs) are widely used as flexible and mobile access points and information carriers for the future Internet of Things (IoT). This work studies a quadrotor UAV-assisted IoT network, where the UAV helps to collect sensing data from a group of IoT users. Our goal is to optimize the UAV’s overall energy consumption required to complete the sensing task. Firstly, we propose a more accurate and mathematically tractable model to characterize the UAV’s real-time energy consumption, which accounts for the UAV’s dynamics, brushless direct current (BLDC) motor dynamics and aerodynamics. Then, we can show that the UAV’s circular flight based on the proposed energy-consumption model consumes less energy than that of hover flight. Therefore, a fly–circle–communicate (FCC) trajectory design algorithm, adopting Dubins curves for circular flight, is proposed and derived to save energy and increase flight duration. Employing the FCC strategy, the UAV moves to each IoT user and implements a circular flight in the sequence solved by the travelling-salesman-problem (TSP) algorithm. Finally, we evaluate the efficiency of the proposed algorithm in a mobile sensing network by comparing the proposed algorithm with the conventional hover-communicate (HC) algorithm in terms of energy consumption. Numerical results show that the FCC algorithm reduces energy consumption by 1–10% compared to the HC algorithm, and also improves the UAV’s flight duration and the sensing network’s service range.
... An economical and computerized respiratory chamber design is an important device to enhance postharvest fresh fruit and vegetable storage. Recently, wireless and networks sensors have been introduced for supporting agriculture works such as measuring, monitoring, and control, but their development is just in the early phase (Wang et al., 2006). Therefore, the wireless sensor network (WSN) was examined for measuring and monitoring oxygen respiration rate in plants (Lokke et al., 2011), storage condition (Green et al., 2009)it is possible to detect any significant increases in temperature occurring during silage decomposition. ...
... Meanwhile, a wireless sensor network is a system comprised of radio frequency (RF) transceivers, sensors, microcontrollers, and power sources. Several types with self-organizing, self-configuring, self-diagnosing, and self-healing capabilities have been developed to solve problems or to enable applications that traditional technologies cannot address (Wang et al., 2006). This network system was applied in this study to provide real-time oxygen and carbon dioxide concentrations during fruit respiration. ...
... Meanwhile, a wireless sensor network is a system comprised of radio frequency (RF) transceivers, sensors, microcontrollers, and power sources. Several types with self-organizing, self-configuring, selfdiagnosing, and self-healing capabilities have been developed to solve problems or to enable applications that traditional technologies cannot address (Wang et al., 2006). This network system was applied in this study to provide real-time oxygen and carbon dioxide concentrations during fruit respiration. ...
Fresh fruit respiration information is essential optimizing food storage systems. Meanwhile, respiration is defined as the process of oxygen production and carbon dioxide release during storage in a closed respiratory chamber. Therefore, this study aims to design a low-budget computerized respiratory chamber for enhancing fruit packaging and storage system. Real-time fruit respiration can be measured by applying wireless gas sensors network. The respirometer consisted of 3,600 mL glass jar with a screw stainless lid, while the electrochemical and non-dispersive infrared sensors were mounted on the cover of the glass jar for collecting data on the oxygen, carbon dioxide, and temperature during mangoes’ respiration. Arduino USB port was used to record all measured parameters consisting of oxygen (%) and carbon dioxide concentrations (ppm, as well as temperature in the respiration chamber. Additionally, a controlled cooling chamber was applied to maintain the temperature during storage, while data communication was supported by Xbee S2C based on radio frequency. According to the respirometer real-time reading, there was a decrease in oxygen concentration caused by increasing carbon dioxide release with temperature. The low-budget respirometer was used to measure the respiration rate and record the data through a wireless sensor network system. The data plot shows that the respiration rate increased as the storage temperature and the respiratory quotient ranged from 0.32-0.44.
... Wireless sensor networks (WSN) have been used for many years in the fields of precision agriculture, environmental monitoring and traceability for food production and smart agriculture. (Wang et al., 2006) (Amin et al., 2004), The ability of wireless sensor networks to configure, self-organize, diagnose and improve makes it preferable for food industry and smart agriculture. WSN is a system of microcontrollers, RF transceivers, sensors and power supplies (Wang et al., 2006). ...
... (Wang et al., 2006) (Amin et al., 2004), The ability of wireless sensor networks to configure, self-organize, diagnose and improve makes it preferable for food industry and smart agriculture. WSN is a system of microcontrollers, RF transceivers, sensors and power supplies (Wang et al., 2006). However, IoT; WSN integrates various existing Technologies such as RF identification, middleware, cloud computing, and end-user applications (Manrique et al., 2016). ...
Tarım alanında yaşanan sorunların çözümünde akıllı teknolojilerin kullanımı önem kazanmaktadır. Çalışmaların önemli bir amacı da tarım ürünlerinin sera ortamlarında yetiştirilmesini sağlamaktır. Bu sayede akıllı sistemler tarafından kontrol edilen seralarda uygun toprak ve iklim koşulları oluşturularak tarım ürünlerinin yetiştirilmesi ve insanların bu ürünlere erişiminin kolaylaştırılması önemli bir araştırma ve uygulama konusu haline gelmiştir. Bu çalışmada, görüntü işleme teknikleri, makine öğrenmesi yöntemleri ve Nesnelerin İnterneti kullanılarak, bir ürünün yetiştirilmesinin takip edilmesi ve uygun yetiştirme koşullarının belirlenmesi amaçlanmaktadır.
... Para el estudio se tomó en cuenta las variables más relevantes en análisis de eficiencia y consumo de energía de las topologías de una red WSN [4]. Para dicho efecto se analizan los siguientes aspectos: ...
... a) Características de la red WSN Son variables creadas por el usuario caracterizar la simulación. En este caso hay que redefinir las siguientes: [4] Tipo de canal= WirelessChannel Modelo de radio Propagación= TwoRayGround Tipo de capa de enlace= LL Modelo de antena= OmniAntenna Número de nodos= 11 Protocolo de enrutamiento= Ad Hoc On-Demand Vector Routing (AODV). Tipo de Trafico= UDP/CBR Modelo de energía= EnergyModel b) Configuración de los nodos Se especifica una configuración general indicando la posición y el comportamiento de cada uno de ellos, ya sean nodos finales, enrutadores o coordinadores. ...
... In addition, users can give instructions to the microcontroller remotely to adjust for new changes. In today's world, people use microcontrollers for traffic management [3], water distribution [4], and also in the field of agriculture [5]. These systems mainly provide low-cost, low-space, low-power autonomous solutions. ...
For most of us, modern life is busier than ever
before. As a result, we have become heavily dependent on
smart devices and automation to perform our regular activities.
The Internet of Things (IoT) technology enables new forms
of smartness in devices. Home automation is one of the main
applications of the IoT. Low-cost networkable microcontrollers
such as the ESP8266 allow easy connection to a Wi-Fi network
and simplify the use of remotely controllable modules. This
paper presents a new generic remote graphical programming
environment for the ESP8266.
As nonprofessionals, homeowners are restricted from creating
smart IoT applications due to their lack of embedded programming
knowledge. An appropriate generic remote GUI programming
environment overcomes the requirement of learning a new
programming language to program a microcontroller.
... In addition, users can give instructions to the microcontroller remotely to adjust for new changes. In today's world, people use microcontrollers for traffic management [3], water distribution [4], and also in the field of agriculture [5]. These systems mainly provide low-cost, low-space, low-power autonomous solutions. ...
For most of us, modern life is busier than ever before. As a result, we have become heavily dependent on smart devices and automation to perform our regular activities. The Internet of Things (IoT) technology enables new forms of smartness in devices. Home automation is one of the main applications of the IoT. Low-cost networkable microcontrollers such as the ESP8266 allow easy connection to a Wi-Fi network and simplify the use of remotely controllable modules. This paper presents a new generic remote graphical programming environment for the ESP8266. As nonprofessionals, homeowners are restricted from creating smart IoT applications due to their lack of embedded programming knowledge. An appropriate generic remote GUI programming environment overcomes the requirement of learning a new programming language to program a microcontroller.
... The flexible data communication protocol IEEE 802.11 is implemented to extend or substitute a wired local area network, such as Ethernet. The bandwidth of 802.11 is 11 Mbits and it operates at 2.4 and 5 GHz frequency, which is attractive because it is license-free [38]. For the localization of a mobile device, either cellbased solutions or (tri)lateration and location fingerprinting are commonly employed [28]. ...
The rapid growth in the technological advancements of the smartphone industry has classified contemporary smartphones as a low-cost and high quality indoor positioning tools requiring no additional infrastructure or equipment. In recent years, the fine time measurement (FTM) protocol, achieved through the Wi-Fi round trip time (RTT) observable, available in the most recent models, has gained the interest of many research teams worldwide, especially those concerned with indoor localization problems. However, as the Wi-Fi RTT technology is still new, there is a limited number of studies addressing its potential and limitations relative to the positioning problem. This paper presents an investigation and performance evaluation of Wi-Fi RTT capability with a focus on range quality assessment. A set of experimental tests was carried out, considering 1D and 2D space, operating different smartphone devices at various operational settings and observation conditions. Furthermore, in order to address device-dependent and other type of biases in the raw ranges, alternative correction models were developed and tested. The obtained results indicate that Wi-Fi RTT is a promising technology capable of achieving a meter-level accuracy for ranges both in line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, subject to suitable corrections identification and adaptation. From 1D ranging tests, an average mean absolute error (MAE) of 0.85 m and 1.24 m is achieved, for LOS and NLOS conditions, respectively, for 80% of the validation sample data. In 2D-space ranging tests, an average root mean square error (RMSE) of 1.1m is accomplished across the different devices. Furthermore, the analysis has shown that the selection of the bandwidth and the initiator–responder pair are crucial for the correction model selection, whilst knowledge of the type of operating environment (LOS and/or NLOS) can further contribute to Wi-Fi RTT range performance enhancement.
... Microcontroller of IOT platform is used to put in force the manipulate unit. The setup makes use of soil moisture sensors which degree the precise moisture stage with inside the soil [3]. ...
This paper gives the clever irrigation gadget the use of Internet of Things (IOT) through the Arduino 3.2. The goals of this paper are to analyze the idea of clever irrigation gadget the use of IOT, to broaden a gadget the use of an Arduino 3.2 that methods the statistics from the soil sensor which robotically water the plant and to examine the actual time circumstance of soil of the flora through the clever phone this is linked to the internet. The scope of the take a look at is targeted on farming vegetation and gardening. The boundaries of this challenge may be very pricey if it's miles implemented on a huge area.
... The availability of miniaturized sensors with increasingly better performance and integration capabilities is having a revolutionary impact as key enabling technologies to address societal challenges and industrial needs. Their diffusion has promoted the development of new technology sectors and applications: from home automation to smart cities [1][2][3][4][5], from biomedical diagnostics to drug research [6][7][8][9][10][11] and from industrial and environmental monitoring [12][13][14][15] to precision agriculture [16][17][18][19][20][21][22][23][24][25][26]. Electronics and miniaturization play a key role in this process, allowing greater automation in industry and diffuse monitoring applications. ...
In this work, we report the parametric optimization of surface acoustic wave (SAW) delay lines on Lithium niobate for environmental monitoring applications. First, we show that the device performance can be improved by acting opportunely on geometrical design parameters of the interdigital transducers such as the number of finger pairs, the finger overlap length and the distance between the emitter and the receiver. Then, the best-performing configuration is employed to realize SAW sensors. As aerosol particulate matter (PM) is a major threat, we first demonstrate a capability for the detection of polystyrene particles simulating nanoparticulates/nanoplastics, and achieve a limit of detection (LOD) of 0.3 ng, beyond the present state-of-the-art. Next, the SAW sensors were used for the first time to implement diagnostic tools able to detect Grapevine leafroll-associated virus 3 (GLRaV-3), one of the most widespread viruses in wine-growing areas, outperforming electrochemical impedance sensors thanks to a five-times better LOD. These two proofs of concept demonstrate the ability of miniaturized SAW sensors for carrying out on-field monitoring campaigns and their potential to replace the presently used heavy and expensive laboratory instrumentation.
... 50 Food can be observed constantly and its quality can be kept up, consequently improving consumer loyalty and business development. 51 WSNs can likewise be applied inside silage stacks to screen any decay, oxygen level, and temperature. It can guarantee the newness of food during transportation as well as storage stacks. ...
The most well‐known sort of remote Internet connection is wireless local area networks (WLANs) due to its unsophisticated operation and deployment. Subsequently, the quantity of gadgets getting to the Internet through WLANs, for example, PCs, cell phones, or wearables, is expanding radically at the equivalent time that applications' throughput necessities do. To provide wireless networks with supplementary spectral resources, the researchers are considering the aggregation of frequency spectrums in licensed, unlicensed, and shared access (SA) bands. Channel aggregation/channel bonding (CA/CB) techniques accumulate quite a few channels together as one channel for the purpose of achieving better bandwidth utilization. In this study, we focus on reliable CA/CB techniques in different wireless networks. CA/CB procedures are utilized for empowering higher information rates by transmitting in more extensive channels, accordingly expanding range proficiency with the assured secure channel for communication. We also discuss the spectral scarcity issues in today's wireless IoT network. This paper presents an extensive survey on CA/CB procedures and methods, issues and challenges, and open research areas related to IoT devices. We analyze the performance of channel CA/CB strategies in the different wireless networks too. An extensive discussion on the basics of CB, different related ideas of CB, challenges involved in CB, and several pros/cons are provided. Different CB schemes for subjective IoT network systems, challenges, and the need for CB are explored in detail. A few rules on CB for futuristic IoT networks are also mentioned.
... Precision agriculture is an important weapon against poverty and hunger and consistently making life better for billions of people across the globe. In recent time, agriculture is facing stiff challenges in the form of climate change, global warming, soil erosion, desertification, shrinking landholdings, crop failures etc. Agriculture information system (AIS) employs modern technologies like information and communication technology [3], wireless sensors [4], internet of things [5], satellite data [6], and drone images [7] become vital to keep agriculture sustainable, viable, smart and adaptive to future challenges. A traditional agriculture information system uses global positioning system (GPS) for accurate mapping of agricultural fields [8]. ...
Precise spatial information of crop distribution is vital for government and research organizations to monitor agriculture activities like crop health monitoring, crop yield prediction, and food security. Mapping of crop area is challenging in smallholder farming like India, where crop parcels are smaller than two hectares. With an extension of artificial intelligence, an artificial neural network has ability to learn the spectral feature of multispectral satellite images and map them to a land cover class. However, mixed pixel is a challenging problem in pixel wise classification of coarse resolution satellite images. The linear mixture model is successfully utilized to unmix the signals of a mixed classes. The success of linear mixture model is depending on the selection of endmembers of a mixed class. Therefore, this paper presents an adaptive approach for automatic selection of endmembers of a mixed pixel in linear mixture model using spectral and spatial information. The proposed approach is capable of extracting the fraction area cover of each class by using a constrained least-squares error solution. The GPS field surveys, and drone images are employed to create reference data for the accuracy assessment of proposed algorithm. The experimentation results indicate that the solution of the proposed approach outperformed recent baseline methods in terms of efficiency and accuracy of pixelwise estimated area and overall estimated area of various land cover classes.
... A generic WSN node architecture illustrates a generic WSN node architecture. Each WSN node has a power source, sensor/actuator, microcontroller and memory, and transceiver (Tx/Rx) [43]. A node can support one or more sensors in measuring different values such as soil moisture/water content, soil temperature, soil electrical conductivity, and weather parameters. ...
Due to the increasing global population and the growing demand for food worldwide as well as changes in weather conditions and the availability of water, artificial intelligence (AI) such as expert systems, natural language processing, speech recognition, and machine vision have changed not only the quantity but also the quality of work in the agricultural sector. Researchers and scientists are now moving toward the utilization of new IoT technologies in smart farming to help farmers use AI technology in the development of improved seeds, crop protection, and fertilizers. This will improve farmers’ profitability and the overall economy of the country. AI is emerging in three major categories in agriculture, namely soil and crop monitoring, predictive analytics, and agricultural robotics. In this regard, farmers are increasingly adopting the use of sensors and soil sampling to gather data to be used by farm management systems for further investigations and analyses. This article contributes to the field by surveying AI applications in the agricultural sector. It starts with background information on AI, including a discussion of all AI methods utilized in the agricultural industry, such as machine learning, the IoT, expert systems, image processing, and computer vision. A comprehensive literature review is then provided, addressing how researchers have utilized AI applications effectively in data collection using sensors, smart robots, and monitoring systems for crops and irrigation leakage. It is also shown that while utilizing AI applications, quality, productivity, and sustainability are maintained. Finally, we explore the benefits and challenges of AI applications together with a comparison and discussion of several AI methodologies applied in smart farming, such as machine learning, expert systems, and image processing.
... A generic WSN node architecture illustrates a generic WSN node architecture. Each WSN node has a power source, sensor/actuator, microcontroller and memory, and transceiver (Tx/Rx) [43]. A node can support one or more sensors in measuring different values such as soil moisture/water content, soil temperature, soil electrical conductivity, and weather parameters. ...
Due to the increasing global population and the growing demand for food worldwide as well as changes in weather conditions and the availability of water, artificial intelligence (AI) such as expert systems, natural language processing, speech recognition, and machine vision have changed not only the quantity but also the quality of work in the agricultural sector. Researchers and scientists are now moving toward the utilization of new IoT technologies in smart farming to help farmers use AI technology in the development of improved seeds, crop protection, and fertilizers. This will improve farmers’ profitability and the overall economy of the country. AI is emerging in three major categories in agriculture, namely soil and crop monitoring, predictive analytics, and agricultural robotics. In this regard, farmers are increasingly adopting the use of sensors and soil sampling to gather data to be used by farm management systems for further investigations and analyses. This article contributes to the field by surveying AI applications in the agricultural sector. It starts with background information on AI, including a discussion of all AI methods utilized in the agricultural industry, such as machine learning, the IoT, expert systems, image processing, and computer vision. A comprehensive literature review is then provided, addressing how researchers have utilized AI applications effectively in data collection using sensors, smart robots, and monitoring systems for crops and irrigation leakage. It is also shown that while utilizing AI applications, quality, productivity, and sustainability are maintained. Finally, we explore the benefits and challenges of AI applications together with a comparison and discussion of several AI methodologies applied in smart farming, such as machine learning, expert systems, and image processing
... A generic WSN node architecture illustrates a generic WSN node architecture. Each WSN node has a power source, sensor/actuator, microcontroller and memory, and transceiver (Tx/Rx) [43]. A node can support one or more sensors in measuring different values such as soil moisture/water content, soil temperature, soil electrical conductivity, and weather parameters. ...
Due to the increasing global population and the growing demand for food worldwide as well as changes in weather conditions and the availability of water, artificial intelligence (AI) such as expert systems, natural language processing, speech recognition, and machine vision have changed not only the quantity but also the quality of work in the agricultural sector. Researchers and scientists are now moving toward the utilization of new IoT technologies in smart farming to help farmers use AI technology in the development of improved seeds, crop protection, and fertilizers. This will improve farmers’ profitability and the overall economy of the country. AI is emerging in three major categories in agriculture, namely soil and crop monitoring, predictive analytics, and agricultural robotics. In this regard, farmers are increasingly adopting the use of sensors and soil sampling to gather data to be used by farm management systems for further investigations and analyses. This article contributes to the field by surveying AI applications in the agricultural sector. It starts with background information on AI, including a discussion of all AI methods utilized in the agricultural industry, such as machine learning, the IoT, expert systems, image processing, and computer vision. A comprehensive literature review is then provided, addressing how researchers have utilized AI applications effectively in data collection using sensors, smart robots, and monitoring systems for crops and irrigation leakage. It is also shown that while utilizing AI applications, quality, productivity, and sustainability are maintained. Finally, we explore the benefits and challenges of AI applications together with a comparison and discussion of several AI methodologies applied in smart farming, such as machine learning, expert systems, and image processing.
... Bluetooth is a technology that operates wirelessly and transfers data between compatible devices. Thus, it is considered a cable replacement for mobile devices for old RS-232 data wires and it is mainly designed to maximize the ad hoc networking functionality [85]. Bluetooth uses radio waves (UHF) and bands (ISM) of two different frequencies, the first one is 2.402 GHz, and the second is 2.48 GHz, respectively. ...
A variety of positioning systems have emerged for indoor localization which are based on several system strategies, location methods, and technologies while using different signals, such as radio frequency (RF) signals. Demands regarding positioning in terms of performance, robustness, availability and positioning accuracies are increasing. The overall goal of indoor positioning is to provide GNSS-like functionality in places where GNSS signals are not available. Analysis of the state-of-the-art indicates that although a lot of work is being done to combine both the outdoor and indoor positioning systems, there are still many problems and challenges to be solved. Most people moving on the city streets and interiors of public facilities have a smartphone, and most professionals working in public facilities or construction sites are equipped with tablets or smartphone devices. If users already have the necessary equipment, they should be provided with further functionalities that will help them in day-to-day life and work. In this review study, user requirements and the state-of-the-art in system development for smartphone localization are discussed. In particular, localization with current and upcoming ‘signals-of-opportunity’ (SoP) for use in mobile devices is the main focus of this paper.
... A generic WSN node architecture illustrates a generic WSN node architecture. Each WSN node has a power source, sensor/actuator, microcontroller and memory, and transceiver (Tx/Rx) [43]. A node can support one or more sensors in measuring different values such as soil moisture/water content, soil temperature, soil electrical conductivity, and weather parameters. ...
Due to the increasing global population and the growing demand for food worldwide as well as changes in weather conditions and the availability of water, artificial intelligence (AI) such as expert systems, natural language processing, speech recognition, and machine vision have changed not only the quantity but also the quality of work in the agricultural sector. Researchers and scientists are now moving toward the utilization of new IoT technologies in smart farming to help farmers use AI technology in the development of improved seeds, crop protection, and fertilizers. This will improve farmers’ profitability and the overall economy of the country. AI is emerging in three major categories in agriculture, namely soil and crop monitoring, predictive analytics, and agricultural robotics. In this regard, farmers are increasingly adopting the use of sensors and soil sampling to gather data to be used by farm management systems for further investigations and analyses. This article contributes to the field by surveying AI applications in the agricultural sector. It starts with background information on AI, including a discussion of all AI methods utilized in the agricultural industry, such as machine learning, the IoT, expert systems, image processing, and computer vision. A comprehensive literature review is then provided, addressing how researchers have utilized AI applications effectively in data collection using sensors, smart robots, and monitoring systems for crops and irrigation leakage. It is also shown that while utilizing AI applications, quality, productivity, and sustainability are maintained. Finally, we explore the benefits and challenges of AI applications together with a comparison and discussion of several AI methodologies applied in smart farming, such as machine learning, expert systems, and image processing.
... The whole generation chain is covered, including day-to-day agricultural activities (Wang et al., 2006). Farmers commonly deal with information overload, which necessitates the creation of a new data source (Sorensen et al., 2010). ...
Agriculture is a distinct sector of a country’s economy. In recent years, new patterns have evolved in the agricultural industry. In conjunction with sensor scaling down and precision agriculture, the field of remote sensor networks, such as the wireless sensor network (WSN), was developed. Its major purpose is to make horticultural operations simpler to identify, assess, and manage. This paper uses the proposed DCNN to predict soil moisture and plan irrigation for precision agriculture farmers to reduce water consumption used for cultivation and increase production yield by comparing water content during various stages of plant growth and integrating IoT applications into agriculture. It also optimizes the water level for future irrigation decisions to maintain crop growth and water stability. The data must be served and stored in the form of a grid view, according to Apriori and GRU (gated recurrent unit). Using numerous sensor and parameter modelling methodologies, this system assists in the prediction of irrigation planning based on irrigation needs. The predicted parameters include soil moisture, temperature, and humidity. This observed experimental data supports smart irrigation in crop production with a high yield and little water use. DCNN has a 98.5% experimental result accuracy rate and the MSE value is predicted in DCNN 99.25% of the time.
... The data collected from these sensors nodes are maintained from this centrally located database continuously. Implementation-2 [13] Different sensors are most widely used nodes from various IoT families. It is efficient and reliable option for many agriculture fields which consists of 32kB on chip with sufficient memory for on chip FLASH memory. ...
Most wireless sensor network (WSN) are widely used to adopt various crop monitoring systems which overcome many issues caused due to lack of an efficient crop monitoring system. As there is an increasing need of various decision support systems at different field locations which constantly monitor the crops for good yield. The main focus of this paper is to review the latest available crop monitoring system designs and their implementations using wireless sensor network which results in increasing the crop yielding and quality of farming without manual observation of the farmer. Many physical events such as relative humidity, soil moisture, water levels etc. are most important for the crop productivity, growth, and quality of plants in different agricultural fields. Sensors have to transmit the collected information through a gateway to the data server. The experts can observe the crop growth by calculating various natural factors from the cloud server simultaneously. The analysis of crop growth at various optimal environmental conditions is analyzed and achieved for maximum crop productiveness through this type of continuous monitoring.
... Geographical area and local climate play important role in determining growth of harvest and any stress in climatic condition results in deviation of plant growth [2]. Photosynthesis, transpiration, absorption, respiration, blooming, etc. biological processes are function of ambient temperature [3]. ...
In order to fulfill the need of ever-growing human population, we need to increase agricultural production at a very high rate. Looking into the climatic conditions; which are beyond our control, Greenhouses are the only way out. Greenhouse offers controlled environment for optimized growth of plant. This paper proposes to apply the internet of things (IoT) technology to greenhouse, in order to monitor environmental conditions and irrigation using a web-based application and boost agricultural yield in turn. This IoT-based greenhouse monitoring system was designed for monitoring and controlling different parameters remotely. The system involves multiple-point, sensing of three vital parameters, namely soil moisture, ambient temperature and humidity (10 soil moisture sensors, 4 integrated humidity and temperature sensors), for controlling exhaust fan and water pump to maintain the desired environmental conditions inside. This system was installed in a cucumber greenhouse and found to be monitoring different parameters on a real time basis and logging them in the database. It satisfactorily controlled the parameters in accordance with predefined values. This system is low cost and easy to use for the farmer, with improvement of agriculture yield.KeywordsESP-32Soil moisture sensorDHT-22 (humidity and temperature) sensorIoTWeb application
... In recent years, wireless technology efficiency is increasing at a very fast rate. Wireless sensor and wireless network is becoming more and more advance in every sector like agriculture, health, environment, military, smart buildings, smart transportation, etc (Wang, Zhang and Wang, 2006;Garbhapu and Gopalan, 2017;Liu, Meng, and Cui, 2007;Ali Khan et al., 2012). Healthcare system is one of the essential applications of the wireless sensor network. ...
Artificial Intelligence (AI) gives the desired results to learn
without being modified expressly. Its emphasis is on the turn of events
and planning of PC programs that can get to the information and utilize
it to learn themselves. By learning various example acknowledgment and
theoretical learning hypothesis in AI, computerized reasoning investigates
the examination and development of calculations that can learn and make
forecasts. In this paper, we talk about and look at Naïve Bayes, KNN,
Decision Tree, SVM, Extra Trees, Random Forest, and XGBoost Classifiers
which are AI calculations as for precision. Speech impairment is a technique
in which speech sounds signals produce that is effective to communicate with
others. Speech impairments can be any type, such as occasionally using a
couple of words, to severe, such as not being capable to produce speech
sounds signals at all. The basic outcome is to study the various machine
learning algorithms for speech impairment. For effective machine learning
results, there are four basic parameters selected with effective techniques,
knowledge parameters, and advanced trees algorithm for displaying the
valuable results. Speech impairments in the early days can have an off-
putting influence on social development. In this article, Parkinson’s dataset
from the UCI library is used with the basic speech-related restrictions and
188
ARTIFICIAL INTELLIGENCE AND SPEECH TECHNOLOGY
obtain a better accuracy level with XGBoost classifier compared with the
other classifiers.
Keywords: Speech impairment, XGBoost classifier, Decision Tree classifier,
... Based on weather and soil conditions, the sensor detects the water level and sends a signal to the controller. The wireless information processing unit analyzed the information received from the sensor regarding the water level conditions [5,6]. Based on the obtained parameters, it enables the actuator devices to supply the plants with the required amount of water. ...
Adequately watering plants is a challenging task. Over- and under-watering may harm plants and seeds, as excess or restraint watering reduces crop production and yield. This study presents a method to remotely monitor and efficiently water agricultural fields to increase crop production by utilizing advanced technologies such as internet things, robotics, image processing, and neural networks. Accurate smoothing and image segmentation techniques were employed to study the plants' conditions. Color median, Gaussian, and hybrid median filters were employed to preprocess the data before segmentation and classification. The hybrid median filter and multilevel luminance grading system were employed to increase the quality of the image. The k-means clustering approach was used for image segmentation. The signal-to-noise ratios of the original and recreated images were compared and analyzed.
... The adoption of the Internet of Things (IoT) paradigm enables the communication of storage environments with the product through sensors and wireless connections (Chandra & Ravi, 2016;Gan et al., 2018;Lopes et al., 2008;Wang et al., 2006). IoT makes it possible to access information in storage environments instantly and intelligently from smart objects connected to the internet (Asefi et al., 2015;Chen et al., 2015;Singh & Fielke, 2017). ...
Grain storage in bag silos has increased in recent years, mainly due to the low initial investment cost. However, there is no control of the ecosystem that involves the biotic and abiotic factors of storage. Thus, the objective was to develop and validate a prototype wireless sensor network and Internet of Things (IoT) platform for real-time monitoring of intergranular equilibrium moisture content and predict through neural network algorithms the physical, physical quality-chemical and microbiological mass of corn stored in bag silos. For an evaluation over three months, the experiments were installed with corn grains with two initial moisture contents of 13% and 18% (w.b.), three storage environments with temperatures of 17, 23, and 30 °C in bag silos. It was observed during the monitoring of stored grains, variations of moisture balance hygroscopic that indirectly inferred the quality of corn. The prototype and device with temperature sensors and intergranular relative humidity of the grains stored in bag silos were adjusted, obtaining satisfactory results for the determination of the equilibrium moisture content curves of the mass of corn grains stored, in real-time, connected to an IoT platform, for indirect monitoring of the quality of stored corn grains over time. In the moisture contents of 13% and the storage condition of 17 °C they had the best quality results, while in the storage in bag silos with moisture contents of 13% and 18% showed no differences in the condition of 23 °C. However, at a temperature of 30 °C, the grains suffered a high deterioration. Furthermore, the quality prediction results using Artificial Neural Networks algorithms, indicated a high coefficient of determination of the trained models, presenting itself as a promising perspective, mainly in develop embedded technologies for monitoring and predicting qualitative variables of corn stored in bag silos.
... Early IoT applications focused on agricultural information sensing. For example, Wang et al. built a mobile observation system for bovine animals using pulse oximeters, respiratory sensors, body temperature sensors, environmental sensors, and GPS modules [26], which provided a monitoring tool to prevent the spread of diseases in the herd. González et al. developed a method to perform unsupervised behavioural classification by installing GPS sensors and movement collars on cattle to observe and record foraging [27]. ...
Collecting environmental information of crop growth and dynamically adjusting agricultural production has been proved an effective way to improve the total agricultural yield. Agricultural IoT technology, which integrates the information sensing equipment, communication network, and information processing systems, can support such an intelligent manner in the agricultural environment. Traditional agricultural IoT could meet the service demand of small-scale agricultural production scenarios to a certain extent. However, the emerging application scenario of the agricultural environment is becoming more and more complicated, and the data nodes of the underlying access to IoT backend system are increasing in large number, while the upper-layer applications are requiring high quality of data service. Hence, the traditional architecture-based (i.e., centralised cloud computing) IoT systems suffer from the problems such as small network coverage, data security issue, and limited power supply time while attempting to provide high-quality services at the edge of the network. Emerging edge computing offers the opportunity to solve these issues. This paper builds an intelligent IoT system for agricultural environment monitoring by integrating edge computing and artificial intelligence. We conducted an experiment to validate the proposed system considering the reliability and usability. The experimental results prove the system’s reliability (e.g., data packet loss rate is less than 0.1%). The proposed system achieves the concurrency of 500TPS and the average response time of 300 ms, which meet the practical requirements in agricultural environment monitoring.
Abstract-
There are numerous motivations to execute a smart-Agri arrangement into business and local cultivating.
In reality, the Internet of things (IoT) has the prodigious appropriation of information social affair and
mechanization, a significant industry, for example, horticulture can doubtlessly profit by the IoT.
Monitoring and collecting data for soil moisture, air temperature, air humidity and sunlight intensity
across multiple fields will improve productivity of water utilization and harvest yield of huge and
nearby ranches. but still the smart-agricultural has many challenges and the those makes many
opportunities to the many researchers. in this paper reviews agricultural in the form of IoT, cloud,
datamining and many other technologies. the paper concentrated the smart improvement by the
performance metrics of the proposed work. the survey makes the creates stepping stones for the many
researchers. Many researchers progress verified perceptions in the literature to overcome these problems.
Without qualified assessment, using the settled concepts will not meet the expected outcome of forthcoming researchers. Without a detailed review of current signs of progress, the researchers may not find
opportunities for forthcoming developments in the direction of excellence. The students becoming good
researchers require a comprehensive analysis of unique concepts with contemporary growth. To
accomplish these requirements, numerous works issued in the widespread journals between the years
reviewed in this paper
Recent testing of an active radio frequency identification (RFID) system within an outdoor fenced-enclosure housing four fattening pigs is described. The system is a modular active-RFID system composed by marker, reader and beacon tag. The enclosure was divided into three areas using three marker’s loop-antennas. These areas were the pigs’ feeding, drinking and resting areas. The duration in seconds verified by video recordings that individual animals attended in the zones outlined by the markers was compared with the duration acquired by the active-RFID system. The results indicate an acceptable accuracy of position-data, as overall 5% underestimation was achieved. Different levels of precision were achieved by the active-RFID system according to the feeding, drinking and resting areas monitored. In particular, problems were encountered due to the behaviour of the pigs surrounding the perimeter of the marked areas, the size and positioning of the tag on the pig’s collar, and other software, hardware and calibration issues some of which may be overcome. These issues, together with the cost, are main limitation when using this technology.
Estimating contaminant source has become increasingly important to hazard assessment and emergency management of air contaminant nowadays. In this paper, a source estimation method is proposed to estimate the location and release rate of source. The theoretical basis of this source estimation method is Bayesian inference using the atmospheric dispersion model, Particle Swarm Optimization (PSO) and the observed data. An improved Gaussian dispersion model is proposed to model the continuous emission source. In order to obtain the observed data, a UAV-based air contaminant sensory system is developed consisting of an aerial platform and a sensory system. An experiment is conducted in a chemical industry park to verify the feasibility and credibility of this UAV-based system. Furthermore, the source estimation method proposed recovers the location and release rate of source with a high accuracy, confirming the effectiveness of the method.
A wireless sensor network (WSN) is a network formed by a large number of sensor nodes, each equipped with sensor(s) to detect physical phenomena such as heat, light, temperature, pressure, motion or sound etc. This paper focuses on the historical background of how the wireless sensor network has come into the existence, it's types, and the current trends. It also presents the applications of WSNs in various fields like agriculture, environmental monitoring, military, health, automation, industrial monitoring, public utilities, assets management and many more. This research paper has also pinpointed the various challenges and issues which are being faced in Wireless Sensor Network and the future possibilities of Wireless Sensor Network.
Advanced farming techniques help to know the appropriate environmental conditions, soil quality, water and fertilizer needs, and crop monitoring during each plant's growth phase, resulting in higher yields. Also, IoT-compatible crop monitoring and data collection systems can help identify crop diseases and the breeding status of pathogenic pests. Extracting data from samples collected from the complete crop growth cycle acknowledged a plausible relationship between weather parameters, crop yield, and insect reproduction. Data analysis done on the data collected through an IoT monitoring system helped determine the environmental factors supporting the higher pest breeding conditions. The proposed fuzzy inference system's knowledge base is designed using these weather parameters. The multi-objective evolutionary algorithm uses fuzzy rules to find suitable cropping window and low pest breeding conditions. This proposal identifies crop-sowing windows based on fuzzy logic with maximum crop yield and minimum pest growth by deploying IEEE 802.15.4 wireless IoT-enabled sensor network monitoring infrastructure in medium grass vegetation. Experiments are being done on rice and Sugarcane crops. The experiments were conducted in the agriculture field of Gwalior, Madhya Pradesh, India. The soil moisture, rainfall, temperature, etc., data were collected using the wireless sensor network deployed in the field. Fuzzy logic-based identification of appropriate planting seasons by IoT application development services helps farmers prevent the development of pests and proactively take precautions to achieve maximum yields.
Water wastage is a grave problem in irrigation due to outdated methods. This work illustrates how a well-structured Fuzzy rule base can eliminate the issue and utilize water at an optimized level. The Poyen’s Fuzzy Logic Controlled Automatic Irrigation (Poyen’s FCAI) efficiently manages the water requirement needs in irrigation processes taking into account the evapotranspiration (ET) loss and cultivating conditions. The Poyen’s FCAI essentially comprises two modules, the Wireless Sensor Network and Information Processing module to perform the assigned task effectively and efficiently. The Wireless Sensor Unit (WSU) accumulates the necessary data, determines the ET loss and runs the decision logic before conveying it to the execution unit, i.e. the Wireless Information Processing Unit (WIPU). The WIPU executes the decision by manipulating the water delivery system, ensuring that the field receives the optimum volume of water. The article illustrates the fuzzy model with simulation output. The model is field-tested with and without the control action over two seasons and in adjacent plots. The results show promising improvements in both water management and crop yield due to more accurate conditions. Hence we obtain a superior automatic irrigation prototype model for all soil types, across different growth stages and for all crops with an exhaustive lookup table in place.
Green criminology is a multidisciplinary issue dealing with ecological violations and complications. Green criminology can be ascribed as umbrella research managing diverse natural enactments and biological atrocities. In green criminology, a cognizant exertion is arranged to strengthen an equity structure for denial of biological harms and offences. This examination highlights a gap between the fundamental criminal equity framework and that which oversees the guidelines of biological offences. The fundamental focus of green criminology is to shield the worldwide ecology from green offenders. In the recent decades, different human acts have seriously harmed the nature worldwide by exercises like illicit logging, contamination of the biological system, unlawful animal killing, poaching, unlawful fishing, biopiracy and illicit exchanging of natural creatures. It is opinioned in this investigation that green criminology has emerged because of the unsafe humanistic activities in the ecosystem and weak ecology shielding legislations. It is suggested through this research that legitimate advances ought to be actualized at the world level to limit green crimes, that will be valuable for social equity and future generations.
The influence of mobile technologies on operational efficiency and effectiveness, and ultimately on shareholder value, is of management interest. Like many other industries, wildlife conservation is becoming an information-intensive enterprise. The opportunities for just in time delivery of information have significantly increased with device capability. The value of accurate, real-time data to different stakeholders is not to be underestimated in the wildlife sector, given the risk of crime syndicates targeting remote nature reserves containing high value assets such as rhino. An internet survey on phone and mobile technology use, ICTs, hard and software requirements and conservation challenges was conducted among private nature reserves, and a Technology Acceptance Model (TAM) applied to smartphone use in wildlife reserve management. Smartphone penetration on nature reserves exceeded 95%, of which 99 % had access to the internet. Apple and Samsung phones dominated, with phones primarily used for communication via email, WhatsApp and calls, and less so for social sharing and gaming. Networking with neighbouring reserves and law enforcement, and data capture / analytics, and integration of anti-poaching technology were central to perceived usefulness (PU) of smartphones. Technology capacity required varied with the most pressing challenges faced: reserves containing rhino required improved surveillance and security integrated mobile technology, and reserves excluding rhino required ecology orientated mobile technology. Collaboration among reserves with regards to smartphone-enabled data sharing platforms and systems is recommended for leveraging economies of scale in the pursuit of cost-effective, sustainable technology development and deployment.
Our agricultural image: as the agricultural production is dispersed, the agricultural sector in the economy was more diversified than it is in the connection, and the connection between the small-scale production, and the market is very bad [1]. We provide recommendations in relation to the tractor, to marketing, based on the cloud processing to provide the proper recommendations to the farmers [2]. We provide a system to inform the farmers about the crops that can be planted in any given season, and also to inform the farmers about the current fair market value of the product. This system can be very helpful for the younger generation to adapt to the traditional methods of agricultural machinery.
The report presents a system dependent [3] on support education for obtaining laws of the order if-then-else from a marked information collection. The component portions of the law are the information proportions of the marked information collection, particularly supplemented by a suitable interval of triggering and a mark [4] that attains for a class group. Originally, the data area is divided into handling terrazzo. The functionality attempts to form the greatest potential at right angle interims from terrazzo. Following the production of periods for every measurement, the course gets the honor for its distribution capacity [5]. This trust with the support of support must be implemented to develop its components. The proposed method’s effectiveness has been tested on five different classification problems: the Iris information collection, the concentric data, the 4 Gaussians, the Pima Indians collection, [6] and the Image Segmentation information collection.
In a real time system, monitoring and control of various parameters of the field is vital .In order to achieve high yields and quality , exact parameters of soils and its necessary inputs to soil need to be put in action. Pest and diseases are also important factors in decline of yield and quality. Considering the various applications of this area, the present paper explains the wireless multi-sensing node for remote monitoring and control system for agricultural applications. This is design with a number of good performance front-end devices and circuits suitable for various types of sensors. Any Sensor device elements can be directly connected without the need of extra circuits. The number of input sensors can be reconfigured with time to time as system demand. The paper describes development and the interface of high performance and low-cost typical features elements. The developed system displayed all the measures field parameters and corresponding set point values on the LCD interface and also are stored in external interface memory for future reference. The developed node can be connected to a personal computing system for decision support using wired RS-232 interface or wireless connectivity using the RF modem from Xbee.
Village agriculture is very important in Bangladesh. In emerging nations like our own, agriculture has a significant impact on national GDP. Basically, because of our current circumstances, the monsoons, which are agriculture's primary source of water, are insufficient. The irrigation system is used in agriculture as a solution to this issue. In this technique, the agricultural field will receive water depending on the type of soil. In agriculture, there are two factors to consider: the soil's moisture content and fertility. There are already a variety of irrigation options available to lessen the demand for rain. Electrical power on/off schedule controls this kind of method. The use of IoT to create a smart irrigation system is covered in this article. Our method uses hydro pumps to regulate multiple pumps at once, which saves time and energy. This system will significantly impact the national economy if we implement it.
Agribusiness is the foundation of Indian economy. A large portion of the number of inhabitants in the nation is legitimately or in a roundabout way subject to farming. Innovation in the technology can improve the outcomes in the area of Smart Farming. In this current period, there is a significant float in horticultural strategies from traditional methodologies. Smart Farming is one method of numerous to meet a 55 percent expansion in worldwide interest for agricultural items on current agrarian field by 2050 at diminished need of composts and efficient utilization of water assets. Energy and food are the main concerns of developing countries. With the presentation of large amount of assortments, persistent cropping system, expanded utilization of composts and chemicals along with high range of farm mechanization, the Smart Farming has become energy persistent. The impetus for the development of savvy cultivating has been satellite situating and route followed by Internet‐ of‐Things, creating immense data that can be utilized to enhance cultivating measures progressively. IoT based precision agriculture has increased a lot to build the profitability and yield in the farms through constant observing of agribusiness field boundaries. The information in the farm is gathered utilizing sensors such soil sensor, temperature and mugginess sensor, air quality sensor, and camcorder mounted on drones. The information from every sensor is then aggregated at the base station and sent to a gateway. In recent years Agro lands are being monitored by IoT and AI. These monitoring includes the growth of the crop and crop wellbeing. IoT technology helps in collecting the real time weather data of the yield growth with the help of the sensor nodes placed in the farm land. On the other hand AI depends on the spectral camera, which captures the images of the farm filed. These captured images are stored in the cloud, later these images will be used for examining the pests and disease contingency with the help of optimized AI algorithms. This chapter aims to provide an outline of how IoT can help in improvement of agricultural productivity to new sustainability heights. The first part will be focused on introduction to IoT in smart farming and its benefits. Second part will be Farming process using Artificial Intelligence. Third part will be focused on energy optimization in agriculture using Iot and Artificial Intelligence.
Volume 2 discusses nanotechnology use in non-thermal techniques such as high-pressure processing (HPP), pulsed electric fields (PEFs), pulsed light, ultraviolet, microwave, ohmic heating, electrospinning, and nano- and microencapsulation. This volume looks at the role and application of minimal processing techniques such as ozone treatment, vacuum drying, osmotic dehydration, dense phase carbon dioxide treatment, and high-pressure assisted freezing. The successful applications of nanotechnologies on juices, meat and fish, fruits and vegetable slices, food surface, purees, milk and milk products, extraction, drying enhancement, and encapsulation of micro-macro nutrients are also considered. The volume also presents several computer-aided techniques that are emerging in the food processing sector, such as robotics, radio frequency identification (RFID), three-dimensional food printing, artificial intelligence, etc. Significant role of food properties in design of specific food and edible packaging films have been elucidated.
Many parameters like temperature, soil moisture, light intensity, Humidity, Carbon dioxide (CO2) leads to the healthy growth of plants in greenhouse environment. Observing only few of those leads to improper growth of plants and minimize the yields. Every grower cannot visit the field and observe the parameters continuously. In order to monitor the parameters and give the approximate control to the greenhouse, we proposed this system. This system continuously monitors the plants and communicate the information to the grower through wireless Sensor Network (WSN), thus reducing the risk of staying at the field. The proposed system has three stations - Transmitter Station (TS), Control Station (CS), and Communication Station (CMS). The ZigBee plays a major role by enabling communication between the three stations. This implementation supports the farmers to simplify the management and to increase the crop production. The overall system has shown the benefits in price, volume, and strength.
The development of agriculture has experienced the transformation from Agriculture 1.0 to Agriculture 4.0, or from traditional agriculture to smart agriculture. Agriculture 1.0 is the traditional agriculture using human and animal labor as its main resource. With the development of industrial revolution, agricultural machines were emerging, which directly resulted in Agriculture 2.0, featured by agricultural mechanization. With the increasing application of computers, electronics, communication technology, and automation equipment in agriculture, agriculture has stepped into the 3.0 era, characterized by digital agriculture or precision agriculture. Agriculture 4.0, also called smart agriculture or precision agriculture V2.0, is characterized by the application of IoT (Internet of Things), big data, cloud computing, and robots in agriculture. Precision agriculture or smart agriculture relies on the acquisition of field information including the environment, crops, and soil, and the accuracy of sensing data is the cornerstone of smart agriculture applications. Soil and crop sensing technology involves the exploration of sensing mechanism, spectroscopy, biology, microelectronics, remote sensing, sensors, and information processing methods. The platforms of soil and crop sensing are also constantly upgrading and improving. Multidimensional perception fusion is realized by using platforms of different scales, such as satellites, unmanned aerial vehicles (UAVs), and ground vehicles integrated with multiple sensors. Intelligent, convenient, accurate, and energy-saving information acquisition technology will continue to be the research hotspots in the field of smart agriculture.KeywordsPrecision agricultureSmart agricultureCrop sensingSoil sensingICT
Healthcare is the most pivotal domain of every nation. With the sudden upraise of the COVID-19 pandemic, there has been a major concern for the healthcare industry to provide quality medical services to the common people. Vulnerable healthcare conditions have proven to be fatal for the patients. Conspicuously, it has become indispensable to assess the quality of healthcare services provided by the hospitals. The current paper focuses on analyzing healthcare service quality delivered by the hospitals and healthcare centers. Specifically, the presented framework utilizes Internet of Things (IoT) technology to acquire real-time ambient data inside smart hospitals. The quantification of the healthcare service is performed using Probability of Health Grade (PoHG) to classify data segments using the Probabilistic Bayesian Belief Model. Furthermore, the temporal data abstraction is performed for the numerical analysis of healthcare service quality in terms of the Health Quality Index (HQI). Finally, a 2-player game theory-inspired decision modeling is performed to analyze healthcare quality in a time-sensitive manner. The proposed framework is assessed using a simulated environment where 225,325 data segments are analyzed. Results are compared with state-of-the-art techniques in which enhanced performance measures are registered in terms of Classification Efficacy (93.74%), Decision-Making Efficiency (Coefficient of Determination (95%), Accuracy (97.53%), Mean Square Error(2.01%)), Root Mean Square Error(1.95%)), Temporal Delay (96.62s), and Reliability(91.58%).
Mobile phones are a snug manner of verbal exchange over an extended interval. Life by having cell phones is changing fast. Mobile phones in times of emergency Phones were a great help. Mobile phones are also referred to as lifesavers as helping human beings in emergencies. Mobile communication is both a sender and a receiver, which refers to the type of communication. Some other in the course of conversation. Wireless Verbal Transfer Networks Provide alerts, including voice, facts and includes multimedia, wires withoutuse; its cell communications is the main part. Over the past decade, industry, science and medicine (ISM) and unlicensed national information infrastructure Unlicensed bands such as (UNII) and Wi-Fi on Certified Bands on Networks Cell networks successfully deployed. Then, many wireless networks, utilities and Services are coming out. Also, wireless networks receive a carrier, in addition Scaling for extension, reduction in the cost of possession and offers many benefits along with many more. However, there are some risks and complications, including Security, information ratio, reliability, variety there are such. For ubiquitous communications call wireless and cellular networks improving. Wireless communication is the fastest growing sector in the field of communication.
Core body temperature is an important measure of animal thermal stress and thermoregulation. A shortrange telemetry system was evaluated in poultry, beef, and dairy cattle. This system provides good temperature accuracy, excellent temperature resolution, and adequate response time. However, this system would need some improvement before it could be implemented into the livestock industry
Tractors are the workhorses of the modern farm. By automating these machines, we can increase the productivity, improve safety, and reduce costs for many agricultural operations. Many researchers have tested computer-controlled machines for farming, but few have investigated the larger issues such as how humans can supervise machines and work amongst them. In this paper, we present a system for tractor automation. A human programs a task by driving the relevant routes. The task is divided into subtasks and assigned to a fleet of tractors that drive portions of the routes. Each tractor uses on-board sensors to detect people, animals, and other vehicles in the path of the machine, stopping for such obstacles until it receives advice from a supervisor over a wireless link. A first version of the system was implemented on a single tractor. Several features of the system were validated, including accurate path tracking, the detection of obstacles based on both geometric and non-geometric properties, and self-monitoring to determine when human intervention is required. Additionally, the complete system was tested in a Florida orange grove, where it autonomously drove seven kilometers.
Improved environment within horse-riding indoor arenas starts with an understanding of current conditions. Little information is available on environmental conditions within indoor arenas. Improved rider, instructor and horse comfort and health may be achieved with improved fresh air entry and distribution within the arena. Six indoor arenas were monitored with electronic temperature and humidity sensors in order to better define conditions within the facilities. There was large variation in the amount of ventilation (0, 0.3, 0.4, 1.4, 9.1 and 21.5 m3 opening per 100 m3 arena floor area) provided to indoor arenas for air quality and occupant comfort during winter conditions. The facilities are characterized in terms of a number of features, such as ventilation system, riding surface material, temperature and humidity levels, and management expertise. All but one arena met natural ventilation temperature guidelines most of the time; two arenas met well-ventilated temperature guidelines all the time. All but one arena was more humid, in terms of absolute humidity, than outdoor conditions. Moisture comes from water that is applied to suppress dust in the riding surface. Arenas attached directly to the horse stable had higher indoor humidity levels than arenas separated from the stable.
Core body temperature is an important physiological measure of animal thermoregulatory responses to environmental stimuli. A new telemetric body temperature measurement system was evaluated by three independent laboratories for its research application in poultry, swine, beef, and dairy cattle. In the case of poultry and swine, the system employs surger-free temperature sensors that are orally administered to allow short-term monitoring. Computational algorithms were developed and used to filter out spurious data. The results indicate that successful employment of the body-temperature measurement method - telemetric or other measurement systems such as rectal or tympanic method, will depend on the specific application. However, due to the cost of the system, the surgeries involved (in some applications), and the need for filtering of data, careful consideration needs to be given to ensure that telemetry is the ideal method for the experiment protocol.
Detailed knowledge of chewing and rumination activities is critical to fully understand the dietary factors affecting normal rumen function. An automatic system for the digital recording of the jaw movements in free-ranging grazing cattle has been described, but its ability to measure chewing activity of cattle housed in confinement and fed total mixed rations has not yet been evaluated. The eating and ruminating behaviors of eight lactating dairy cows were recorded simultaneously by a wireless automatic system and by 5-min interval observation over 24-h periods. Results indicated that both methods agreed on identification of eating and ruminating bouts. Mean differences between methods for total time eating (8.7 min +/- 12.8) and ruminating (42.9 min +/- 12.0) were significantly different. The time recorded by observation in both eating and rumination was 3.6 and 10.3% higher compared with the automatic system. Differences indicate inaccuracies in the observational method itself. The automatic system may prove useful in further studies examining eating and rumination activities in cattle.
Wearable systems for human and animal state-of-health determination share many design requirements. This paper discusses the design of a remote health monitoring system for cattle that hosts a suite of sensors and communicates wirelessly with a base station via Bluetooth telemetry.
The next several years will witness the evolution of sensor networks from simple test-and-report wired systems to intricate wireless information fabrics that connect our surroundings to the information super highway and cyberspace. These systems will be applied to agricultural monitoring, medical monitoring, intelligent space realization, automotive safety, personal area networks, and even wartime intelligence. To enable these applications research efforts will be focused on developing low-power, low-cost sensor technology and creating networks that self-assemble, self-anneal and self-heal into an emergent life-like system. The human nervous system with its 7-8 billion neurons represents a compelling model for such systems. Each wireless sensor device can be interpreted as a neuron with radio frequency (RF) connectivity. These devices are referred to as neuRFon™ devices and can sense the environment, process various stimulus, and transmit a request for action while consuming very little power and requiring minimal, if any, human intervention. This paper presents an overview of neuRFon™ technology and some of the associated challenges in the design and implementation of wireless sensor networks.
We describe a moving virtual fence algorithm for herding cows. Each animal in the herd is given a smart collar consisting of a GPS, PDA, wireless networking and a sound amplifier. Using the GPS, the animal's location can be verified relative to the fence boundary. When approaching the perimeter, the animal is presented with a sound stimulus whose effect is to move away. We have developed the virtual fence control algorithm for moving a herd. We present simulation results and data from experiments with 8 cows equipped with smart collars. I.
As the farm population of Japan continues to shrink and grow more elderly, it is important to find ways to increase agricultural productivity and save labor. This article describes the deployment of a wireless LAN in farm fields and a pilot program using the LAN to map plant growth and implement greenhouse remote control to raise productivity and save labor.
The trend towards high-capacity farm machines is continuing steadily. Apart from the classical
fields of application, complex self-propelled machines adopt new sectors. Remote service
systems are a promising means to achieve maximum availability and minimum break-down time,
which is of special importance in seasonal peak times. Further reasons for remote service are
expensive down times due to high machine acquisition costs and consequential charges in
following steps of the interrupted process.
This paper describes all tools and procedures used to structure and implement an
automatic data acquisition and control mobile laboratory network for crop production systems
data management and spatial variability studies in the Brazilian Center-West Region. It was set
up with base in remote sensing and microprocessor techniques, microelectronic devices,
sensors, controls, sampling systems, data loggers, portable microcomputers, automatic data
acquisition, RF communications link, and the global positioning system (GPS), allowing for the
acquisition of spatially related data during tilling, planting, and harvesting. Physical chemistries
and biological characteristics of the continuous soil-water-plant-atmosphere were monitored
along of the crop growth period, at field conditions, seeking the rationalization of the agricultural
inputs use and the performance improvement of agricultural systems. Some results are
presented.
The inductor-capacitor (LC) sensor, comprised of a thick- film printed LC resonant circuit the resonant frequency of which can be remotely detected with a loop antenna, has been used for the monitoring of temperature, humidity, atmospheric pressure, salt concentration, and complex permittivity, as well as the detection of bacteria in a liquid medium based upon changes in the complex permittivity due to the bacteria growth. Due to its low unit cost and wireless detection, the LC sensor is potentially suitable for commercial scale monitoring of food quality. This paper includes the operational principles and design criteria of the LC sensor, and illustrates the monitoring of bacteria growth in milk, meat, and beer.
In this communication, we present the HidroBus system, which was specially designed for centralized remote control and supervision of large areas of irrigated land, with a large number of nodes, a distance of tens of kilometers from the nodes to the control center and no electricity supply to the remote stations that are to control the irrigation hydrants. We also describe, as an example of the practical application of this system, the automation of the irrigation at Jumilla (Murcia, Spain), featuring real-time control of 1850 hydrants on an individual basis and the optimization of irrigation to demand necessities, together with low installation and operating costs. q 2001 Elsevier Science B.V. All rights reserved.
This research was conducted to develop a silage yield mapping system using DGPS, load cells, Bluetooth modules for wireless data transmission, and a moisture sensor. A silage yield mapping system was successfully developed and tested in a silage corn field. The system yielded an error in the range of 0.37 ~ 1.96% of total harvested crop, compared with measurements by a platform scale. A Bluetooth module (wireless transmission) was successfully implemented to transfer moisture sensor information to a host computer. A silage corn yield map was created for a site-specific crop management.
An analysis of the multispectral image-based precision agriculture technology as used in the US cotton belt was undertaken to identify bottlenecks which limit the delivery and use of this technology. One area in particular was identified: the movement of data and information nec-essary to implement variable rate applications. Solutions to reduce or eliminate this problem were explored. A new technology called wireless local area networking (or WLAN) was ex-plored. A test farm was selected, a system was designed and implemented, and the resulting implementation was successfully tested. The system wirelessly connected cotton pickers, spray equipment, variable rate fertilized application equipment, and hand-held personal digital assistant computers in the field, allowing for rapid bi-directional movement of data and information.
Greenhouse control computers are an essential part of modern greenhouse operation. Climate, irrigation and nutrient supply must be controlled, in an economical way, to produce the best crop conditions. Current research on CO2 enrichment and optimal growth strategies implies the use of powerful tools, either based on hardware or software. This paper describes the design and implementation of a distributed data acquisition and control system for computerised agricultural management systems that is being developed at Universidade of Tras-os-Montes and Alto Douro, Vila Real. Different communications platform concepts, such as Controller Area Network (CAN), Wireless Technologies, Ethernet and Internet tools supported by Transfer Control Protocol/Internet Protocol (TCP/IP) and e-mail tools supported by Simple Mail Transfer Protocol (SMTP) were used to achieve a network with a low-cost, flexible, and functional characteristics. The system management and maintenance tasks are divided into two types of performance levels. At a lower supervision level, a Local Controller placed in the greenhouses performs the monitoring/control and communications actions. The management decisions are performed at the higher level. The techniques and tools, which provide to the user a transparent, friendly and intuitive Graphical User Interface (GUI) will be presented.
Pl@nteInfo® (www.planteinfo.dk) is a decision support system, which uses the World Wide Web to supply farmers and agricultural advisers with just-in-time information and decision support for crop management. A subscription system enables personalised information. Background data are collected from different sources, processed by decision support models, and the results are integrated into personalised web pages with embedded graphics, expert interpretations and links to additional information. This article presents the system with its decision support facilities and subscription system, the architectural design of the system using collaborating web servers and the technical solutions for creating personalised information in real time. Through the example of Pl@nteInfo®, the article shows that it is possible to build web-based decision support systems, where personalised advice is given in real time, based on user profiles together with distributed data and decision models. The article also analyses the user acceptance of the system. This analysis showed that the farmer and adviser subscribers are very dedicated users. Both the activity patterns and the preferences of subjects in the system are significantly different between these subscriber types, with farmers generally searching specific advice and advisors using the system to keep their knowledge up-to-date.
A new concept for on-line surveillance of animal transports is presented, comprising telemetry and wireless data communication. The concept has two major objectives: (1) to improve animal disease prevention and control and (2) to enable monitoring of animal welfare during transport. The system allows on-line collection on the transport lorry of data with respect to animal identification, body temperature and geographical position. Concept and prototype system are described. Performance tests on data collection and transmission showed the technical feasibility of the prototype system, both under laboratory and semi-practical conditions. Necessary improvements and future use of the system are discussed.
Agriculture in the Information Society is analysed by a review of recent publications on the subject. The development of a future Network Society is foreseen to imply significant changes in the use of information technology (IT) in agriculture. Farmers' hitherto modest use of IT is explained by the economic argument, that simplification of farming methods and application of cheap externally produced inputs have been more efficient ways to reduce farming costs than IT. It is predicted that this situation will change due to restrictions on chemicals and certain production practises. Information technology will become important due to a need for a higher precision in the use of chemicals and in the care of farm animals, and due to demands for food documentation. The restrictions and demands will be enforced by governments and by the food industry. Farmers will want IT applications that support the operational aspects of farming, i.e. real-time decision support on high-bandwidth wireless Internet connections. E-mail and chat applications enriched by photos, videos and sound will become important elements in a revived agricultural extension service in a future Network Agriculture.
Field measurements in the environmental sciences still depend upon the pencil and paper notebook for data collection. Although robust, this method is labor-intensive and susceptible to recording and georeferencing errors during transcription. Recent advances in mobile computing and wireless communications allow the geoscientist to process and transmit data while still in the field, thereby minimizing human errors and time delays. We describe an integrated system developed for environmental and geolocation data acquisition that is intended to streamline the collection process. The system consists of software applications and hardware components that enable wireless, mobile and Internet computing during field campaigns. In particular, two-way transfer and display of collected data is achieved between the field site and a remote location, a concept referred to as field data streaming. A prototype system has been tested in field trials in Cambridge, Massachusetts, USA and Newcastle, New South Wales, Australia. Field studies demonstrate the noticeable gains in efficiency and precision achieved with the use of the field streaming technology. Potential applications include biogeochemical and hydrologic studies, water quality monitoring, emergency response to water-borne disasters and intensive field sampling campaigns.
Wireless temperature sensors (WTS) are measurement devices widely used by food industry to determine time-temperature history during typical processes, such as thermal sterilization. A mathematical model was developed to study, under certain hypotheses, how the insertion of (WTS) influence the heat transfer into conductive canned food.The considered system is mainly described by a can filled with a conductive food with a WTS fixed at the bottom or suspended in the container, to measure the temperature at the slowest heating point.The equations have been solved by means of the finite element method to predict the temperature in every point of the domain. The domain has been meshed in different ways, by increasing the node density where a better investigation is needed, such as around the WTS. The kinetics of microbial inactivation was coupled to the heat transfer model to analyse the processes in terms of the sterilizing value.Simulation results show that the influence of the temperature sensor is related to the relative dimensions of can and WTS, as well as to the WTS position into the container.
We were asked to try to improve the performance of quality assurance inspectors in a food processing plant. These workers walk around a very large, very loud, football field-sized plant and take food samples at various processing points. The workers pick up a sample, make a measurement (for example, temperature), wipe their hands on a paper towel, then use a pen and clipboard to write the measurement on a paper inspection form. At the end of the shift, the quality assurance inspectors give their paper forms to the quality assurance manager. For other members of the management team (such as the plant manager) to see the inspection data, the forms must be photocopied or the data must be typed into a networked computer. We faced several challenges in our effort to improve the performance of the quality assurance inspectors. The inspectors need a data collection system that is portable and allows inspectors to enter data without using their hands. The system must also provide the data to the plant management team as the inspectors actually gather the data. Finally, the use of sound to enter or receive information is a major challenge in the plant's noisy environment.
Suppose we are given some fixed (but unknown) subset X of a set# , and our object is to learn as much as possible about the elements of X by asking binary questions. Specifically, each question is just a function F:# #{0, 1},andthe answer to F is just the value F (X i )forsome X i # X, (determined, for example, by a potentially malevolent but truthful, adversary). In this paper, we describe various algorithms for solving this problem, and establish upper and lower bounds on the e#ciency of such algorithms. 1
New welfare regulations will impose surveillance systems so that information on the quality of transport conditions is available. Moreover a route description is useful for optimisation of transport logistics, but also in relation to estimating of sanitary risk and food safety, including traceability of individual animals. Therefore a transport surveillance system has been developed which is integrating the following information: individual identification of animals, (un)loading place and time, air quality (temperature, relative humidity, emissions), vibration and behaviour of the animals. These data are collected by telemetry and GPS, and are transmitted to a dispatch centre by GSM. Hence, information is available on-line and on disk, so that the driver can be informed and corrected at the spot. Dynamic route optimization of cattle collection from farms and logistical activities of abattoirs are considered in relation to animal welfare. Another instrumentation package that comprises sensors of heart rate and vibration on the animal has been integrated. These sensors can be mounted on animals and the data is transferred to a database through a wireless network. Comprehensive field measurement has been made to evaluate the system and found that the package performs well. Hence, advice will be generated for vehicle manufacturers, hauliers, farmers, slaughterhouses and retailers.
The desire for reduced operation costs, high quality products and services, a better monitoring of items for a targeted intervention in case of critical situations and the increasing demand for security and safety from final consumers sets high requirements for well structured traceability systems. Advances in information technology permit synchronization between physical and information flows and coordination of activities among supply chain partners. Bar code and radio frequency identification (RFID) systems are examples of such technologies that permit us to collect data about logistics transactions of items, store and organize them in order to use this information in enterprises' management control, decision analysis and strategic planning systems. Within a company, the use of a specific item identification technology or the decision of switching from a technology to another is an important decision since it could have expensive consequences. The purpose of the paper is to provide a framework for identifying principles and functionalities of a traceability system in the context of a global supply chain. Using assessment criteria obtained by this analysis, we evaluate the performance of bar code and RFID systems. Finally, we describe benefits (measured as reduction in costs, improvement in the customer service level, etc.) that RFID technology can provide to supply chain processes.
Military, commercial and agricultural autonomous/non-autonomous
vehicles are designed to operate in the vicinity of people. The wireless
personal safety radio device (WPSRD) described in this paper is worn by
personnel and installed on the autonomous vehicle. It can initiate
various actions in response to the information about the location or
moving direction of personnel or vehicles. Such actions include shutting
the vehicle down or warning personnel in the field via visual and audio
alarm signals from the WPSRD. When an individual perceives danger to
persons or property, the stop button on the WPSRD device may be pressed,
issuing an immediate command to slow/stop the vehicle. The relative
distance is estimated from the relative amplitude strength from the
priori known unit locations
This paper presents the use of surface acoustic wave resonators
(SAWRs) in passive remote identification and sensor system in the
European 433.92 MHz ISM-band. The identification device consists of a
SAWRs parallel circuitry and is connected via matching network to the
Tx/Rx antenna. The narrowband interrogation was the main criteria for
the device development. An integrated sensor function was added by
sensitive SAWR. Depending on application a direct peak frequency change
or a differential frequency method are feasible. Theoretical and
experimental results of the SAW resonator identification tag (RESTAG)
with 5 and 12 bits respectively are presented and discussed. The device
was developed and optimized for the identification and temperature
measurement
Modern concepts on methods and techniques for the management and
control of agricultural systems-such as greenhouse and animal live
stocks-claim for the use of computer systems. Tasks like climate,
irrigation and nutrient supply must be controlled, in an economically
way, to produce the best crop/living conditions. To comply with these
objectives, it is necessary to apply adequate control actions as the
result of an integrated system that co-ordinates each action according
with specific combination of different sensor inputs. Moreover, this
control must be often performed from a remote site. This paper describes
the design and implementation of an integrated network that links
several communications platforms, as different as controller area
network (CAN), wireless technology and Transfer Control
Protocol-Internet Protocol (TCP-IP). The main goal is to develop a
system that guarantees a low-cost, high performance and flexible
distributed control system with an increased functionality. The user
interacts with this distributed control system using a transparent and
intuitive graphical user interface, (GUI) accessible from remote places
This paper describes the implementation of a wireless data
acquisition network for agricultural applications based on the Microchip
PIC16C71, and the Intel 87C592 microcontrollers. The system uses a set
of solar powered wireless data-acquisition stations (SPWAS) linked by
radio frequency to a base station (BS). The base station has as main
functions the control of the data-acquisition stations and the storage
of the data collected by them. The network has been applied to collect
outdoor and indoor climate data from a set of greenhouses located at
Universidade de Tras-os-Montes e Alto Douro (UTAD), in the northwest of
Portugal. Experimental tests have been done since mid June 1996, and the
results obtained show that the communications to the BS were performed
without errors or loss of data
Based on wireless communication, radio frequency identification (RFID) tags store identification data and transmit that to a receiver-from which they also draw their power. They incorporate the use of electromagnetic or electrostatic coupling in the RF portion of the electromagnetic spectrum to uniquely identify an object, animal or person. RFID is seen as the successor to the ubiquitous barcode. The antenna in the reader uses RF waves to transmit a signal that activates the transponder in the tag, which then transmits data back to the antenna.
Smart Dust/Mote Training Seminar
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AwirelessLANforcollaborativeoff-roadvehicleautomation
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Emergentwirelesssensornetworklimitations:apleaforadvancementincoretechnologies
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Upchurch, Design and Construction of a Wireless Infrared Thermometry System. The USDA Annual Report Project Number: 6208-21000-012-03 A mathematical model to study the influence of wireless temperature sensor during assessment of canned food sterilization
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Mahan, J., Wanjura, D., 2004. Upchurch, Design and Construction of a Wireless Infrared Thermometry System. The USDA Annual Report. Project Number: 6208-21000-012-03. May 01, 2001–September 30, 2004. Marra, F., Romano, V., 2003. A mathematical model to study the influence of wireless temperature sensor during assessment of canned food sterilization. J. Food Eng. 59, 245–252.
Temperature and humidity in indoor riding arenas during cold weather. ASAE Paper No.: 03-4090. The American Society of Agriculture Engineers
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Automatic Spraying for Nurseries. USDA Annual Report Project Number: 3607-21620-006-03 Wireless safety personnel radio device for collision avoidance system of autonomous vehicles
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Charles, K., Stenz, A., 2003. Automatic Spraying for Nurseries. USDA Annual Report. Project Number: 3607-21620-006-03. September 22, 2000–August 31, 2003. USDA, USA. Chung, Y.C., Olsen, S.L., Wojcik, L., Song, Z., He, C., Adamson, S., 2001. Wireless safety personnel radio device for collision avoidance system of autonomous vehicles. In: Digest of 2001 IEEE Antennas and Propagation Society International Symposium, Boston, MA. USA, July 8–13, pp. 121–124.
Wireless robust robot for agricultural applications
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Hirakawa, A.R., Saraiva, A.M., Cugnasca, C.E., 2002. Wireless robust robot for agricultural applications. In: Proceedings of the World Congress of Computers in Agriculture and Natural Resources, Iguacu Falls, Brazil, March 13–15, pp. 414–420.
Editorial: this changes everything—market observers quantify the rapid escalation of wireless sensing and explain its effects. Wireless for Industry
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A friendly man-machine visualization agent for remote control of an autonomous tractor GPS guided
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Ribeiro, A., Garcia–Perez, L., Garcia-Alegre, Guinea, M.C., 2003. A friendly man-machine visualization agent for remote control of an autonomous tractor GPS guided. In: The Proceedings of the 4th European Conference in Precision Agriculture, Berlin, Germany, June 14–19.
Developing a wireless LAN for high-speed transfer of precision agriculture information
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McKinion, J.M., Jenkins, J.N., Willers, J.L., Read, J.J., 2003. Developing a wireless LAN for high-speed transfer of precision agriculture information.
Vision of the future for smart packaging for brand owners
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Chandler, S., 2003. Vision of the future for smart packaging for brand owners. In: Proceedings of the International Conference on Smart and Intelligent Packaging, Barcelona, Spain, October 28–29, pp. 253–269.
Portable and mobile instrument for continuous stable climate measurement
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Silage yield monitoring system. ASAE Paper No.: 02-1165. The American Society of Agriculture Engineers
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Lee, W.S., Burks, T.F., Schueller, J.K., 2002. Silage yield monitoring system. ASAE Paper No.: 02-1165. The American Society of Agriculture Engineers, St. Joseph, Michigan, USA.
Microbial sensor tags The 2003 IFT (The Institute of Food Engineering) Annual Meeting Book of Abstracts
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Wentworth, S.M., 2003. Microbial sensor tags. In: The 2003 IFT (The Institute of Food Engineering) Annual Meeting Book of Abstracts, Chicago, Illinois, USA, July 12–16.