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Smart Agriculture: Software Platform for Telematics Monitoring in Farm Machinery
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The Internet of Things (IoT) technology and devices represent an exciting field in computer science that is rapidly emerging worldwide. The demand for automation and efficiency has also been a contributing factor to the advancements in this technology. The proliferation of IoT devices coincides with advancements in wireless networking technologies, driven by the enhanced connectivity of the internet. Today, nearly any everyday object can be connected to the network, reflecting the growing demand for automation and efficiency. This paper reviews the emergence of IoT devices, analyzed their common applications, and explored the future prospects in this promising field of computer science. The examined applications encompass healthcare, agriculture, and smart cities. Although IoT technology exhibits similar deployment trends, this paper will explore different fields to discern the subtle nuances that exist among them. To comprehend the future of IoT, it is essential to comprehend the driving forces behind its advancements in various industries. By gaining a better understanding of the emergence of IoT devices, readers will develop insights into the factors that have propelled their growth and the conditions that led to technological advancements. Given the rapid pace at which IoT technology is advancing, this paper provides researchers with a deeper understanding of the factors that have brought us to this point and the ongoing efforts that are actively shaping the future of IoT. By offering a comprehensive analysis of the current landscape and potential future developments, this paper serves as a valuable resource to researchers seeking to contribute to and navigate the ever-evolving IoT ecosystem.
The competent software architecture plays a crucial role in the difficult task of big data processing for SQL and NoSQL databases. SQL databases were created to organize data and allow for horizontal expansion. NoSQL databases, on the other hand, support horizontal scalability and can efficiently process large amounts of unstructured data. Organizational needs determine which paradigm is appropriate, yet selecting the best option is not always easy. Differences in database design are what set SQL and NoSQL databases apart. Each NoSQL database type also consistently employs a mixed-model approach. Therefore, it is challenging for cloud users to transfer their data among different cloud storage services (CSPs). There are several different paradigms being monitored by the various cloud platforms (IaaS, PaaS, SaaS, and DBaaS). The purpose of this SLR is to examine the articles that address cloud data portability and interoperability, as well as the software architectures of SQL and NoSQL databases. Numerous studies comparing the capabilities of SQL and NoSQL of databases, particularly Oracle RDBMS and NoSQL Document Database (MongoDB), in terms of scale, performance, availability, consistency, and sharding, were presented as part of the state of the art. Research indicates that NoSQL databases, with their specifically tailored structures, may be the best option for big data analytics, while SQL databases are best suited for online transaction processing (OLTP) purposes.
With the advent and growth of modern technologies in this 21st century, information is a vital source for knowledge growth. The fifth law of library science by S.R. Ranganathan – “Library is the growing organism” suggests that the library is dynamic in nature that defines its goals to expand its boundaries for their creativity and innovativeness. As the information continues to expand and accelerates there should be a feasible way to communicate the information-rich to the end-users by the academic libraries through Mobile Apps, Websites, Social Networking Sites, Short Messaging Services (SMS), Email-Marketing, Web Services and much more. Over the last few decades, there is a big shift in the mobility and connectedness in the nature of information in a very dramatic way. Growth of modern technologies& digital platform enables the information to be consumed through handheld/portable devices – the mobile way, which considerably more commonplace than desktops & can be accessed anywhere and anytime without any boundaries. Progressive Web Application (PWA) is made exactly for this. PWA is a mobile-first approach and was introduced by Google in 2015. It uses modern web technologies to create mobile web experiences that look a like native mobile applications. The application of mobile technology helps libraries to improve and enhance libraries products and services. Users can access libraries services from anywhere without depending on physical library and library staff. PWAs does not require any installation and are cost-effective. This chapter introduces PWA and its features that can support the academic libraries in delivering their services and facilities with ease.
Technological advancements have led to an increased use of the internet of things (IoT) to enhance the resource use efficiency, productivity, and cost-effectiveness of agricultural production systems, particularly under the current scenario of climate change. Increasing world population, climate variations, and propelling demand for the food are the hot discussions these days. Keeping in view the importance of the abovementioned issues, this manuscript summarizes the modern approaches of IoT and smart techniques to aid sustainable crop production. The study also demonstrates the benefits of using modern IoT approaches and smart techniques in the establishment of smart- and resource-use-efficient farming systems. Modern technology not only aids in sustaining productivity under limited resources, but also can help in observing climatic variations, monitoring soil nutrients, water dynamics, supporting data management in farming systems, and assisting in insect, pest, and disease management. Various type of sensors and computer tools can be utilized in data recording and management of cropping systems, which ensure an opportunity for timely decisions. Digital tools and camera-assisted cropping systems can aid producers to monitor their crops remotely. IoT and smart farming techniques can help to simulate and predict the yield production under forecasted climatic conditions, and thus assist in decision making for various crop management practices, including irrigation, fertilizer, insecticide, and weedicide applications. We found that various neural networks and simulation models could aid in yield prediction for better decision support with an average simulation accuracy of up to 92%. Different numerical models and smart irrigation tools help to save energy use by reducing it up to 8%, whereas advanced irrigation helped in reducing the cost by 25.34% as compared to soil-moisture-based irrigation system. Several leaf diseases on various crops can be managed by using image processing techniques using a genetic algorithm with 90% precision accuracy. Establishment of indoor vertical farming systems worldwide, especially in the countries either lacking the supply of sufficient water for the crops or suffering an intense urbanization, is ultimately helping to increase yield as well as enhancing the metabolite profile of the plants. Hence, employing the advanced tools, a modern and smart agricultural farming system could be used to stabilize and enhance crop productivity by improving resource use efficiency of applied resources i.e., irrigation water and fertilizers.
App development is a steadily growing industry. Progressive web apps (PWAs) constitute a technology inspired by native and hybrid apps; they use web technologies to create web and mobile apps. Based on a service worker, a caching mechanism, and an app shell, PWAs aim to offer web apps with features and user interfaces similar to those of native apps. Furthermore, technological development has created a greater need for accessibility. An increasing number of websites, even government ones, are overlooking the need for equal access to new technologies among people with disabilities. This article presents, in a systematic review format, both PWAs and web accessibility and aims to evaluate PWAs’ effectiveness as regards the corresponding accessibility provided.
Smart farms, as a part of high-tech agriculture, collect a huge amount of data from IoT devices about the conditions of animals, plants, and the environment. These data are most often stored locally and are not used in intelligent monitoring systems to provide opportunities for extracting meaningful knowledge for the farmers. This often leads to a sense of missed transparency, fairness, and accountability, and a lack of motivation for the majority of farmers to invest in sensor-based intelligent systems to support and improve the technological development of their farm and the decision-making process. In this paper, a data-driven intelligent monitoring system in a cloud environment is proposed. The designed architecture enables a comprehensive solution for interaction between data extraction from IoT devices, preprocessing, storage, feature engineering, modelling, and visualization. Streaming data from IoT devices to interactive live reports along with built machine learning (ML) models are included. As a result of the proposed intelligent monitoring system, the collected data and ML modelling outcomes are visualized using a powerful dynamic dashboard. The dashboard allows users to monitor various parameters across the farm and provides an accessible way to view trends, deviations, and patterns in the data. ML models are trained on the collected data and are updated periodically. The data-driven visualization enables farmers to examine, organize, and represent collected farm’s data with the goal of better serving their needs. Performance and durability tests of the system are provided. The proposed solution is a technological bridge with which farmers can easily, affordably, and understandably monitor and track the progress of their farms with easy integration into an existing IoT system.
Smart Farming is a new and emerging domain representing the application of modern technologies into agriculture, leading to a revolution of this classic domain. CLUeFARM is a web platform in the domain of smart farming which main purpose is to help farmers to easily manage and supervise their farms from any device connected to the Internet, offering some useful services. Cloud technologies evolved a lot in recent years and based on this growth, microservices are more and more used. If for the server side, the scalability and reusability are solved in high proportion by microservices, on the client side of web applications, there was no independent solution until the recent emergence of web components. They can be seen as the microservices of the front-end. Microservices and web components are usually used isolated one of each other. This paper proposes and presents the functionality and implementation of a dependable workflow management service by using an end-to-end microservices approach.
At present, the old production management mode has become a stumbling block to the development of enterprises, and the high-end manufacturing technology is still not mature enough. This research mainly discusses the intelligent manufacturing management system based on data mining in artificial intelligence energy-saving resources. The enterprise business management system cannot accurately and timely grasp the actual situation of the production site, and the accuracy and feasibility of the upper-level planning cannot be guaranteed. At the same time, on-site personnel and equipment cannot get practical production plans and production instructions in time, resulting in product backlogs and excessive inventory. On the other hand, equipment is idle and resources are wasted, and the workshop scheduling system loses the corresponding scheduling role. The development of this system is mainly composed of front-end technology, back-end technology and front-end and back-end interaction technology. The interface design of the front end is mainly completed by the windows form application in c#. The interaction between the front and back ends is mainly realized by programming in each control of the form application. Back-end technology is the core content of the system, mainly including two key technologies: mixed programming of C #. Net and MATLAB and C # connecting SQL Server database. The system mainly includes five sub-functional modules: order management, material management, mixed model assembly line balance, assembly line logistics scheduling and system management. Order management and material management are the basis of the system, which provides parameter input for the balance of assembly line and logistics scheduling. The balance of mixed model assembly line is the core function of the system. The balance of mixed model assembly line is carried out by calling the intelligent algorithm written in MATLAB, and the optimal assembly scheme of workstation is displayed to the front end of the system, which reflects the intelligent characteristics of production control system for intelligent manufacturing. The logistics scheduling of assembly line takes the balance result of mixed model assembly line as the premise, takes the balance result as the task sequence input of logistics scheduling, and optimizes the operation efficiency of logistics system (driving path and running time of AGV). The operation results show that the comprehensive energy consumption of 10,000 yuan industrial output value is 401.19 kg standard coal/10,000 yuan, a year-on-year decrease of 6.96%. This study is helpful to the fine management of manufacturing industry.
Internet of Things (IoT) can be seen as the electricity of 21st century. It has been reshaping human life daily during the last decade, with various applications in several critical domains such as agriculture. Smart farming is a real-world application in which Internet of Things (IoT) technologies like agro-weather stations can have a direct impact on humans by enhancing crop quality, supporting sustainable agriculture, and eventually generating steady growth. Meanwhile, most agro-weather solutions are neither customized nor affordable for small farmers within developing countries. Furthermore, due to the outdoor challenges, it is often a challenge to develop and deploy low-cost yet robust systems. Robustness, which is determined by several factors, including energy consumption, portability, interoperability, and system’s ease of use. In this paper, we present an agile AI-Powered IoT-based low-cost platform for cognitive monitoring for smart farming. The hybrid Multi-Agent and the fully containerized system continuously surveys multiple agriculture parameters such as temperature, humidity, and pressure to provide end-users with real-time environmental data and AI-based forecasts. The surveyed data is ensured through several heterogeneous nodes deployed within the base station and in the open sensing area. The collected data is transmitted to the local server for pre-processing and the cloud server for backup. The system backbone communication is based on heterogeneous protocols such as MQTT, NRF24L01, and WiFi for radio communication. We also set up a user-friendly web-based graphical user interface (GUI) to support different user profiles. The overall platform design follows an agile approach to be easy to deploy, accessible to maintain, and continuously modernized.
Investment in technological research is imperative to stimulate the development of sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and sensor networks, robotics, artificial intelligence, big data, cloud computing, etc. foster the transition towards the Agriculture 4.0 era. This fourth revolution is currently seen as a possible solution for improving agricultural growth, ensuring the future needs of the global population in a fair, resilient and sustainable way. In this context, this article aims at characterising the current Agriculture 4.0 landscape. Emerging trends were compiled using a semi-automated process by analysing relevant scientific publications published in the past ten years. Subsequently, a literature review focusing these trends was conducted, with a particular emphasis on their applications in real environments. From the results of the study, some challenges are discussed, as well as opportunities for future research. Finally, a high-level cloud-based IoT architecture is presented, serving as foundation for designing future smart agricultural systems. It is expected that this work will positively impact the research around Agriculture 4.0 systems, providing a clear characterisation of the concept along with guidelines to assist the actors in a successful transition towards the digitalisation of the sector.
The Internet of Things (IoT) has tremendous success in health care, smart city, industrial production and so on. Protected agriculture is one of the fields which has broad application prospects of IoT. Protected agriculture is a mode of highly efficient development of modern agriculture that uses artificial techniques to change climatic factors such as temperature, to create environmental conditions suitable for the growth of animals and plants. This review aims to gain insight into the state-of-the-art of IoT applications in protected agriculture and to identify the system structure and key technologies. Therefore, we completed a systematic literature review of IoT research and deployments in protected agriculture over the past 10 years and evaluated the contributions made by different academicians and organizations. Selected references were clustered into three application domains corresponding to plant management, animal farming and food/agricultural product supply traceability. Furthermore, we discussed the challenges along with future research prospects, to help new researchers of this domain understand the current research progress of IoT in protected agriculture and to propose more novel and innovative ideas in the future.
Cloud Computing is a new era that helps organizations to move fast and adopts different services that accelerate building and hosting their services and reach customers and third parties quickly. However, there are challenges related to Cloud Computing that the Services Providers must consider and implement. This paper highlights the Cloud Computing Legal, Contractual and Security challenges. In addition, it gives some suggested solutions for some of the highlighted key challenges.
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