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Agriculture plays a significant role in most countries and there is an enoromous need for this industry to become "Smart". The Industry is now moving towards agricultural modernization by using modern smart technologies to find solutions for effective utilization of scarce resources there by meeting the ever increasing consumtion needs of global po...
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... Data generated by sensors could be easily analyzed and processed by agricultural personnel, even in remote areas, leveraging cloud computing technologies [15], [16]. Another study explored the use of a wireless sensor network to track soil moisture levels, temperature, and humidity [17]. The data were transmitted to the system, and a sleep-wake plan was implemented to optimize node capacity. ...
Agriculture, the foundation of human civilization, has relied on manual practices in the face of unpredictable weather for millennia. The contemporary era, however, witnesses the transformative potential of the Internet of things (IoT) in agriculture. This paper introduces an innovative IoT-driven smart agriculture system empowered by Arduino technology, making a significant contribution to the field. It integrates key components: a temperature sensor, a soil moisture sensor, a light-dependent resistor, a water pump, and a Wi-Fi module. The system vigilantly monitors vital environmental parameters: temperature, light intensity, and soil moisture levels. Upon surpassing 30°C, an automatic cooling fan alleviates heat stress, while sub-300CD light levels trigger light-emitting diode lighting for optimal growth. Real-time soil moisture data is relayed to the “Blynk” mobile app. Temperature thresholds align with specific crops, and users can manage the water pump via Blynk when manual intervention is required. This work advances agricultural practices, optimizing water management by crop type. Through precise coordination of soil moisture, temperature, and light intensity, the system enhances productivity while conserving water resources and maintaining fertilizer balance.
... Despite this, a significant proportion of farmers worldwide continue to rely on traditional farming methods that often result in suboptimal yields. To address these challenges, the concept of smart agriculture, which aims to enhance productivity and efficiency through the automation of agricultural practices, has gained significant attention [3]. ...
Drones have been attracting significant attention in the field of agriculture. They can be used for various tasks such as spraying pesticides, monitoring pests, and assessing crop growth. Sensors are also widely used in agriculture to monitor environmental parameters such as soil moisture and temperature. Due to the high cost of communication infrastructure and radio-wave modules, the adoption of high-density sensing systems in agriculture is limited. To address this issue, we propose an agricultural sensor network system using drones and Optical Camera Communication (OCC). The idea is to transmit sensor data from LED panels mounted on sensor nodes and receive the data using a drone-mounted camera. This enables high-density sensing at low cost and can be deployed in areas with underdeveloped infrastructure and radio silence. We propose a trajectory control algorithm for the receiving drone to efficiently collect the sensor data. From computer simulations, we confirmed that the proposed algorithm reduces total flight time by 30% compared to a shortest-path algorithm. We also conducted a preliminary experiment at a leaf mustard farm in Kamitonda-cho, Wakayama, Japan, to demonstrate the effectiveness of the proposed system. We collected 5178 images of LED panels with a drone-mounted camera to train YOLOv5 for object detection. With simple On–Off Keying (OOK) modulation, we achieved sufficiently low bit error rates (BERs) under 10−3 in the real-world environment. The experimental results show that the proposed system is applicable for drone-based sensor data collection in agriculture.
... Tian et al. discussed the use of computer vision technology in agricultural automation [15]. In order to boost agricultural productivity, particularly in terms of quality and competitiveness, technology utilisation is required especially in terms of superiority and effectiveness [16]. The accessibility of technological advancements like deep learning and machine learning is also essential for enhancing farmer welfare and piquing the interest of the younger generation in developing diverse derivative business opportunities [17][18][19]. ...
... Automation becomes crucial in addressing these challenges, streamlining IoT processes, reducing errors, optimizing costs, and meeting stringent QoS requirements, particularly for time-sensitive applications. In conventional farming, farmers spend a significant amount of time monitoring and assessing crops, as highlighted in [43] and [44], making smart agriculture essential to optimize farming practices and minimize manual labor. Fig. 1 depicts the comprehensive architecture of our proposed framework, seamlessly built on top of an existing edge computing framework, namely Flotta. ...
As the Internet of Things (IoT) evolves rapidly across various industries, the number of IoT protocols and applications is growing with vast number of heterogeneous components and entities. In setups with thousands of IoT devices, manual deployment of applications and device registration become impractical due to their time-consuming and costly nature, as well as the requirement for background knowledge of IoT devices and protocols. Furthermore, IoT devices often have resource constraints that prevent them from running complex software. Therefore, there is a significant need to enhance and optimize edge computing systems for IoT, making them suitable and dynamic for automated IoT device registration and heterogeneous application deployment. In this article, we present an edge-based framework designed to facilitate the automated registration of diverse wireless IoT devices and the deployment of IoT applications. To validate our approach, we use a smart irrigation system enhanced with a containerized machine learning model as a proof of concept. Our evaluation of the implemented prototype demonstrates that our system is scalable and feasible.
... Protocols for conveying information are the foundation of IoT agricultural networks and applications. They are accustomed to trading all farm-related data or information across the web (Al-Sarawi et al., 2017a;Navulur & Prasad, 2017). Telecommunication is used to connect sensors, actuators, and other IoT devices that are deployed in fields and greenhouses. ...
... Recently, the bioenergy based on the food-crops market is increasing, also. Even before a decade, only the production of ethanol utilized 110 million [16][17][18][19][20]. In the above-mentioned series of research work, it has been described that IOT technology can be used to enhance agriculture products. ...
The rapid population growth is a compelling surge need for food which results in a shift towards smart farming practices. Moreover, agriculture is facing with several issues such as shrinking natural resources, limitation of cultivable land, unpredictable weather conditions, increase in crop diseases. Consequently, the Internet of Things (IoT) and artificial intelligence (AI) are being associated with agriculture to reduce operational efforts while increasing productivity. Radio frequency identification, wireless sensor networks (WSN), cloud computing, end-user apps, and middleware systems are a few of the technologies that are integrated into the Internet of Things. In this paper, numerous applications and challenges of IoT have been discussed. Further, an ecosystem for agriculture is presented which discusses that how IoT is solving different challenges faced by the farmers.
... We believe that the stability of the development of agriculture and its branches, as well as the reduction in crisis duration, is affected by innovation technologies and the elaboration of resistant species of crops, pesticides, herbicides, and, in current conditions, the digitalization instruments (Schwab et al, 2018;Goel et al, 2021). For instance, Agriculture 4.0, the fourth design of agrotechnologies, envisages the creation of climate-resistant agriculture, which would ensure longterm stable performance of plant production based on rational management of technological processes and nutrients with the purpose of promoting the increase in organic carbon and the growth of plants in soil and minimization of exhausts in the production processes (Prause, 2021;Navulur et al, 2017). Both domestic and foreign researchers state that this is a novel way of enlarging the volumes and quality of agricultural products via the economy of such resources as labour, seeds, fertilizers, and water (Navulur, 2017;Lins et al, 2020;Manushkina et al, 2020;Kucher et al, 2014). ...
... For instance, Agriculture 4.0, the fourth design of agrotechnologies, envisages the creation of climate-resistant agriculture, which would ensure longterm stable performance of plant production based on rational management of technological processes and nutrients with the purpose of promoting the increase in organic carbon and the growth of plants in soil and minimization of exhausts in the production processes (Prause, 2021;Navulur et al, 2017). Both domestic and foreign researchers state that this is a novel way of enlarging the volumes and quality of agricultural products via the economy of such resources as labour, seeds, fertilizers, and water (Navulur, 2017;Lins et al, 2020;Manushkina et al, 2020;Kucher et al, 2014). Obviously, the strategic development of plant production in the period of postwar rebuilding will be oriented on the implementation of smart technologies, which reduce dependence on non-renewable or ecologically harmful resources and are based on ecoagroculture, permaculture, low expenses, resource-and moistureeffi cient technologies (El Bilali et al, 2018;Quintero-Angel et al, 2018;Schnebelin et al, 2021). ...
Aim. To determine the consequences of the cyclic development in the agrarian sector and evaluate the shifts in the structure and the performance of plant production branches due to the course of the transformational and agrarian crises and inter-crisis periods, to disclose the specificities of anti-crisis regulation in the agrarian sector in the postwar time. Methods. Common scientific methods were applied, including historical and logical, dialectic and systemic analysis, theoretical generalization, analysis and synthesis, variation dynamics, comparison, grouping, indexing, and table methods. Results. The cyclic character of the development in the agrarian sector and its impact on plant produc- tion were studied, and the results demonstrated that agrarian crises are an imminent stage of this process, and their “trough” is a starting point to launch a new cycle. It was found that the prolonged nature of agrarian crises inhibited the restoration cycle so much that the temporal breaks with the cycles of previous periods decreased considerably, and the periods of their complete revolution shortened due to which the scientists distinguish just two phases of crises now instead of traditional four phases: recession and uprising. It was determined that during the transition to new forms of management, there was an obvious destruction of the material resources of plant production with the refusal to keep to the crop rotation order. Still, the redistribution of the land and their division into shares stimulated the organization of modern agrarian enterprises yet delayed the agrarian and land reforms considerably. Due to this factor and other reasons, agricultural plant production at the “trough” of the transformational crisis decreased twice. The analysis demonstrated that the restoration of plant production occurred 12 years after the institutional crisis, followed by its registered rise until the moment of the Russian aggression – up to 156 %, and the development of the industry was closely related to the cyclic character of the functioning in the agrarian sector in general. Due to military actions, the manufacture of plant products has been dropping rapidly for the past two years. It was found that the results of the basic year were achieved differently in terms of different crops: the results for grains, grain legumes, and technical crops were achieved only in 2008; for vegetables and potatoes – in 2000, the yield of sunflower constantly increased, even despite agrarian crises; the performance of sugar beet decreased more than four times in 2021; the results for fruit and berries did not match those of 1990. The main directions of restoring the agrarian resource potential and renewing the manufacture of plant products in the postwar period were suggested. Conclusions. Modern processes of agricul- tural production are subject to the cyclic character of development, the trends of which are clearly copied in the plant production development. It was proven that agriculture reached the level of 1990 by the production volumes only in 2019, and the specificity of its development lies in the fact that after a short descending trend, there was a transition to the ascending trend, improving the situation considerably, but it was often broken by the lower part (“trough”) of agrarian crises and local drops (every other year). It was found that the restoration of plant production after a deep institutional crisis was registered in 2011, and in the subsequent years, there was a clear copying of the tendencies in the development of agrarian crises, but in terms of different crops, the rises from the “trough” of the transformational crisis took place in different time periods. The evaluations confirm that in plant production, the “trough” of each subsequent agrarian crisis was higher than that of the previous one, but it was followed by the ascending trend of the production, the exception being the peak of 2021, followed by the dramatic drop, caused by the Russian aggression. It was empirically proven that the cyclicity in the manifestation of the agrarian crises is characterized by the follow- ing time periods: from 1990 to 1999 – 10 years, from 2000 to 2010 – 10 years, and there were two crises, five years long each, during the subsequent 10-year-long period. It was rationalized that the main factors of shorter time periods in the crisis manifestation are as follows: global climate change, smart technologies, and a failure to comply with scientifically grounded requirements of crop rotations, which conditioned the domination of export-oriented crops in the structure of areas under crop, etc. The priorities of the postwar restoration of the plant production industry were substantiated; among these, the time-urgent investment into the de-mining processes in agricultural fields and the quality restoration of the latter was highlighted, including the distribution of sustainable production practices, the introduction of moisture- and resource-efficient technologies, precision agriculture, smart-technologies, the measures aimed at minimizing the losses of agricultural products in the process of producing, storing the products and managing food wastes. There is a need to establish a system of reacting to the manifestations of crisis phenomena, which should be based on analytical evaluations and scientifically grounded predicted scenarios.
... To overcome these numerous difficulties and produce more with less land, new technology-based approaches are required. In order to better understand the crop conditions, farmers in traditional farming practices visit their fields often during the crop's life as part of ordinary farming chores [9]. Farmers may identify ongoing field operations without physically being there thanks to the accurate field view provided by today's sensor and communication technologies. ...
... Farmers that practice ecological farming must check farms to assess crop status. Furthermore, knowing farm status and farm management take about 70% of farmers' time [3]. Current advances in internet of things (IoT), communication and sensor technologies enable distant agricultural field observation from any place [4]. ...
p> Adoption of the internet of things (IoT) is moving forward quickly because of the developments in communication protocols and technology involving sensors. The IoT is promoting real-time agricultural field monitoring from any distant place. For the IoT to be implemented effectively there are a number of agricultural issues related to less power usage and long-distance transfer of data are to be addressed. By using LoRa, which is a wireless communication system for IoT applications, these difficulties can be avoided when sending information from fields of crops to a web server. Acustomized sensor node and LoRa are used in this work to transmit continuously updated information to a remote server. Monitoring the quality of water, and reducing wasteful use of water are the main goals. </p
... Lately, a modern greenhouse construction has been designed, and IOT solution is being employed for long-term operation. Sensors capture temperature, relative humidity, and light intensity, [1] which are then adjusted by a fan, evaporation system, and shade curtain via IOT operation [2]. The greenhouse is now set up for hydroponic vegetable culture as well as organic strawberry, melon, and flowering plant production Since 2010, Thailand has used electronic sensors and data communication devices with digital technology to apply automatic control systems. ...
This research focuses on developing an automated agricultural greenhouse that employs photovoltaic (PV) electricity and a monitoring system based on the technology of the Internet of Things (IoT). The Anto IoT platform was applied to enable real-time monitoring and control of the agricultural greenhouse environment in this system. In addition, the system used a grid-connected PV system to provide sustainable energy. The LoRa module and 3G module were used for wireless communication between the system components and the Anto IoT platform. For real-time monitoring and controlling of the environmental parameters, the IoT sensors were applied such as temperature, humidity, electrical conductivity, and pH of fertilizer. The use of renewable energy sources such as the 900 Wp of grid-connected PV system provides a reliable and cost-effective source of energy to power the system by reducing grid energy consumption by 23.6%. The results show that the proposed approach can be used to implement sustainable agricultural practices while also increasing the productivity of crops. Moreover, this accuracy technology can assist in reducing labor costs and managing expenses while enhancing productivity in terms of both quantity and quality since it can give users real-time information, which it can be used timely agricultural decisions.
