Agricultural Internet Of Things Research Articles

A Survey on the Role of IoT in Agriculture for the Implementation of Smart Livestock Environment

The Internet of Things (IoT) is an emerging paradigm that is transforming real-world things (objects) into smarter devices. IoT is applicable to a variety of application domains including healthcare, smart grid, and agriculture. This domain has started revolutionizing the agriculture industry by providing smart solutions for precision farming, greenhouse management, and livestock monitoring. This article aims to present a comprehensive survey on the role of IoT in the Livestock field by categorizing and synthesizing existing research work in this area. To this end, a detailed discussion has been provided on IoT network infrastructure, topologies and platforms employed for livestock management. In addition, a list of communication protocols and connections of IoT-based livestock systems with relevant technologies have also been explored. Furthermore, numerous IoT-based livestock monitoring, controlling, and tracking applications have been discussed. Apart from this, it also analyses distinct security issues in IoT-based livestock field and developed a collaborative security model to detect and minimize the security risk. Lastly, pertinent open research challenges in the domain of IoT-based livestock management have been presented with future research directions.

Applications of the internet of things in agriculture

The article examines the methods of implementing Internet of Things technologies in the agricultural sector, suggests the use of artificial intelligence and neural networks in combination with the Internet of Things to improve the results of growing various plants. The advantages of neural networks, which are able to process large arrays of data on the activity of agricultural formations much faster and more efficiently than an experienced specialist, are also considered. However, for this, the primary information for training the network should be prepared in a format that is understandable for it. Obtaining up-to-date and objective information about the condition of plants using the Internet of Things will improve the exchange of information between specialists and expert consultants. Modern agriculture needs to have a high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. IoT is one of the most popular tools of this kind. It is widely used in solving various classification and prediction tasks. For some time IoT also been used in the broadly defined field of agriculture. It can form part of the precision farming and decision support systems. IoT and artificial neural networks can replace the classical methods of modeling, and are one of the main alternatives to classical mathematical models. The spectrum of the applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible.

MHADBOR: AI-Enabled Administrative-Distance-Based Opportunistic Load Balancing Scheme for an Agriculture Internet of Things Network

In this article, we present a supervised machine learning multipath and administrative-distance-based load balancing algorithm for an Agriculture Internet of Things (AG-IoT) network. The proposed algorithm is known as an artificial intelligence or simply AI-enabled multihop and administrative-distance-based opportunistic routing (MHADBOR) algorithm, which processes the collected information from source to the destination by means of multihop count and administrative-distance-based communication infrastructure in the network. Beside that, we used cluster heads (CH), microbase stations ($\boldsymbol {\Re BS}$ℜBS), and macrobase stations ($\boldsymbol {\aleph BS}$ℵBS) in the network with a frequent rate to effectively utilize the administrative distance while managing the deployed network traffic in a congestionless communication environment. In addition, the MHADBOR algorithm empowers the participating devices to practice the administrative distance rather than hop count communication when they are in the vicinity of network special components, e.g., CH and $\boldsymbol {\Re BS}$ℜBS outcome statistics of the MHADBOR algorithm in the simulation environment exhibit an extraordinary improvement in contention, congestion, communication, and computing costs, accompanied by throughput and end-to-end (E2E) delay and packet loss ratio in the deployed AG-IoT network.

SimulateIoT-FIWARE: Domain Specific Language to Design, Code Generation and Execute IoT Simulation Environments on FIWARE

Systems based on the Internet of Things (IoT) are continuously growing in many areas such as smart cities, home environments, buildings, agriculture, industry, etc. This system integrates heterogeneous technologies into a complex architecture of interconnected devices capable of communicating, processing, analysing or storing data. There are several IoT platforms that offer several capabilities for the development of these systems. Some of these platforms are Google Cloud’s IoT Platform, Microsoft Azure IoT suite, ThingSpeak IoT Platform, Thingworx 8 IoT Platform or FIWARE. However, they are complex IoT platforms where each IoT solution has to be developed ad-hoc and implemented by developers by hand. Consequently, developing IoT solutions is a hard, error-prone and tedious task. Thus, increase the abstraction level from which the IoT systems are designed helps to tackle the underlying technology complexity. In this sense, model-driven development approaches can help to both reduce the IoT application time to market and tackle the technological complexity to develop IoT applications. In this paper, we propose a Domain-Specific Language based on SimulateIoT for the design, code generation and simulation of IoT systems which could be deployed on FIWARE infrastructure (an open-source IoT platform). This implies not only designing the IoT system for a high abstraction level and later on code generation, but also designing and deploying an additional simulation layer to simulate the system on the FIWARE infrastructure before final deployment. The FIWARE IoT environment generated includes the sensors, actuators, fog nodes, cloud nodes and analytical characteristics, which are deployed as microservices on Docker containers and composed suitability to obtain a service-oriented architecture. Finally, two case studies focused on a smart building and an agricultural IoT environment are presented to show the IoT solutions deployed using FIWARE.

Economic Benefit Evaluation and Analysis Based on Intelligent Agriculture Internet of Things

There has been a consensus on the development of ecological agriculture to promote the leap from traditional agriculture to ecological agriculture, but the unavoidable fact is that the development of ecological agriculture is still relatively slow at the present stage and has not formed a major climate and great influence. The rise of the Internet is a technology that has promoted the transformation and upgrading of modern agriculture, changed the traditional agricultural production mode, and accelerated the scientific and technological integration of information. In view of the characteristics and difficulties of agriculture, this paper builds an Agricultural Internet of Things (IoT) management system to realize the integrated management of Internet equipment and realize the management of environmental data, video data, and agricultural expert knowledge. Then from perception technology, transmission technology, and the perspective of three intelligent information processing technologies, this paper introduces the present state of agricultural IoT, analyzes the Internet of Things to the economic benefits of agricultural production, to research the problems of China’s agricultural development of the Internet of Things, and puts forward China’s agricultural Internet of the future research emphasis and direction of development.

Smart Agriculture and Smart Farming using IoT Technology

It has become easier to access agriculture data in recent years as a result of a decline in digital breaches between agricultural producers and IoT technologies. These future technologies can be used to boost productivity by cultivating food more sustainably while also preserving the environment, thanks to improved water use and input and treatment optimization. The Internet of Things (IoT) enables the production of agricultural process-supporting systems. Referred to as remote monitoring systems, decision support tools, automated irrigation systems, frost protection systems, and fertilisation systems, respectively. Farmers and researchers must be provided with a detailed understanding of IoT applications in agriculture as a result of the knowledge described above. This study is about using Internet of Things (IoT) technologies and techniques to enhance agriculture. This article is meant to serve as an introduction to IoT-based applications in agriculture by identifying need for such tools and explaining how they support agriculture.

Data curation in the Internet of Things: A decision model approach

Current Internet of Things (IoT) scenarios have to deal with many challenges especially when a large amount of heterogeneous data sources are integrated, that is, data curation. In this respect, the use of poor-quality data (i.e., data with problems) can produce terrible consequence from incorrect decision-making to damaging the performance in the operations. Therefore, using data with an acceptable level of usability has become essential to achieve success. In this article, we propose an IoT-big data pipeline architecture that enables data acquisition and data curation in any IoT context. We have customized the pipeline by including the DMN4DQ approach to enable us the measuring and evaluating data quality in the data produced by IoT sensors. Further, we have chosen a real dataset from sensors in an agricultural IoT context and we have defined a decision model to enable us the automatic measuring and assessing of the data quality with regard to the usability of the data in the context.

The Internet of Things in Agriculture - the advantages and opportunities

The Internet of Things (IoT) has become increasingly popular in the recent decade. The Internet of Things helps people live and work smarter, as well as gain complete control over their lives. The concept of the IoT went widely into practice in different fields – Infrastructure, Production, Healthcare, Banks, Smart cities, Insurance, Media, Retail, Connected homes / Smart buildings, Agriculture, and many more. Modern agriculture can show its potential and importance by using these innovative technologies. The measuring devices, ensuring the transformation of data for the external environment into machine-readable data, at the same time filling the computing environment with significant information are very important. A wide range of measuring devices is used, from elementary sensors (e.g. temperature, pressure, illumination), consumption meters (e.g. smart meters) to complex integrated measuring systems. Satellites, drones, wireless sensor networks, analytical farming devices systems, farm management systems, big data applied to the farm are very useful and applicable in smart farming. The Internet of Things is a huge opportunity for farmers to monitor their crops and increase productivity, to monitor their livestock, to manage all the processes in their work and to take decisions at the right time. The article analyzes issues related to the modern IoT methods and their usage in general and in the area of agriculture. The main goal is to analyze the current state of IoT and its potential in areas of rural development and agriculture in the Republic of Bulgaria.

The role of the Internet of Things as direction for the development of agriculture 4.0 for rural areas

The article discusses trends and opportunities for the development of the digitalization of agriculture. The potential of the Internet of Things (IoT) for agriculture is innovative. The rationale for this is the creation of cloud platform solutions determines the grounds for this research. Particular attention is paid to quantitative and qualitative trends in the development of the Internet of Things in agricultural production. The article analyses the benefits of the Internet of Things for agriculture and rural development. The industrial Internet of Things helps to improve the competitiveness, efficiency and safety of agricultural production. IoT platforms and mobile apps allow to control and track production along the entire value chain. They also help to make decisions with a high level of risk in agricultural production. Significant amount of the information available in the agriculture is not fully utilized. Digitalization of agriculture improves efficiency and productivity in the industry. The Internet of Things in agriculture is a promising direction of technological breakthrough for a rational resource-saving agriculture 4.0.

Scalable Privacy-preserving Geo-distance Evaluation for Precision Agriculture IoT Systems

Precision agriculture has become a promising paradigm to transform modern agriculture. The recent revolution in big data and Internet-of-Things (IoT) provides unprecedented benefits including optimizing yield, minimizing environmental impact, and reducing cost. However, the mass collection of farm data in IoT applications raises serious concerns about potential privacy leakage that may harm the farmers’ welfare. In this work, we propose a novel scalable and private geo-distance evaluation system, called SPRIDE, to allow application servers to provide geographic-based services by computing the distances among sensors and farms privately. The servers determine the distances without learning any additional information about their locations. The key idea of SPRIDE is to perform efficient distance measurement and distance comparison on encrypted locations over a sphere by leveraging a homomorphic cryptosystem. To serve a large user base, we further propose SPRIDE+ with novel and practical performance enhancements based on pre-computation of cryptographic elements. Through extensive experiments using real-world datasets, we show SPRIDE+ achieves private distance evaluation on a large network of farms, attaining 3+ times runtime performance improvement over existing techniques. We further show SPRIDE+ can run on resource-constrained mobile devices, which offers a practical solution for privacy-preserving precision agriculture IoT applications.

Internet of Things for Agricultural Applications: The State of the Art

The advent of the Internet of Things (IoT) inspired various new and enhanced sets of applications in multiple domains including agriculture. The recent drive in the adoption of IoT technologies offers a major enhancement for the agricultural sectors in terms of efficiency and scalability. In this article, we investigate the specific issues and challenges associated with IoT, and review various IoT architectures, communication, middleware, and information processing technologies. We, then, discuss few IoT applications for agriculture-presenting various case studies to thoroughly analyze the solutions along with their design and implementation related parameters. Consequently, we provide a comprehensive review of the available simulation tools, data sets, and testbeds which provisions experimentation with IoT in agriculture. We enumerate open issues and challenges present in enabling IoT for agriculture. Finally, this article concludes while giving directions for future research.

Implementasi IoT dalam Otomasi Pengontrolan Kondisi Lingkungan dan Pemberian Pakan: Efeknya Terhadap Parameter Efisiensi Peternakan

Nowday 35% of Indonesians buy poultry products every week. However, 95% of Indonesia farms are small open houses often built from bamboo using manual feeding and watering systems. The problem related to the manual feeding and watering system is the high mortality rate of poultry, which is an average of 8%. The use of IoT (Internet of Things) in agriculture and livestock is increasingly popular. This research implemented IoT on a poultry farm to automatically control environmental conditions based on sensor readings and measure feed level and water consumption. It also monitored chicken weight via a digital scale. This study also measured the farm efficiency parameters before and after IoT implementation, namely FCR, IP, and mortality rates. The results showed that the performance of IoT in poultry farms could increase efficiency. After IoT implementation, the FCR value decreased from 1.46 to 1.38, which led to an increase in the FE value to 72%. The IP score increased to 391.1. The mortality rate of chickens decreased from 3.67% to 2.35%. Also, the average weight of chickens at harvest is 1460gr. the mortality rate of chickens decreased from 3.67% to 2.35%. Also, the average weight of chickens at harvest is 1460gr.

Iot Technology-Based Smart Distribution Framework for the Recognition of Vulnerabilities

The Internet of Things (IoT) transforms everybody’s life through functionality like control and tracking of linked intelligent devices. Smart towns, houses, vehicles, factories, e-healthcare to intelligent control systems, commuting, clothing, agriculture, and many more size IoT applications. The adaptation of these instruments is increasing rapidly, generating considerable data for visualization and interpretation. These systems are also vulnerable to various security risks and issues alongside easy human life, which not only concern consumers for their adoption in sensitive environments such as e-health, smart homes, and so on but also represent a risk for IoT nutrition in the next few days. The Internet of Things (IoT) transforms everybody’s life through functions like the tracking and surveillance of the associated intelligent objects. Smart cities, houses, vehicles, factories, e-healthcare, commuting, wearable tech, agriculture, and more are all IoT technologies. The adaptation of such instruments is exponentially increasing, which produces considerable data for processing and analysis. These systems are thus vulnerable to various threats and safety challenges alongside facilitating human life, not only causing concern to the consumers for their use in centralized locations including such e-health and intelligent home, etc but also posing a risk to IoT nutrition in the coming days. Moreover, a detailed competitive study between the suggested technique and other related schemes reveals that a better deal is reached with the suggested Method in comparison with other schemes between the safety and accessibility features, connectivity, and computing costs.

Exploration of research on Internet of Things enabled smart agriculture

Since we have required so much food to be a major economic country in the world, existing or traditional farming methods and storage methods are not adequate to increase production and maintenance for future purposes. The Internet of Things in Agriculture leads to creativity in areas such as Crop Maintenance and Tracking, Animal Farming, Fishing, Millet Crops, and so on. This paper investigates the different technologies, protocols, sensors used in recent research in sustainable farming.

Design and Implementation on Patchouli Growth Environment Monitoring System Based on IoT

With the development of the times, the concept of "interconnection of all things" has been deeply rooted in the hearts of people. As an early and developing Internet technology, the Internet of things(IoT) has shown its infinite potential in many fields of social life. In agriculture, the agricultural IoT is coverring a growing number of fields: greenhouse planting, climate factor collection, climate prediction and so on. Based on this idea, the design idea of "patchouli growth environment monitoring system" is put forward. In this paper, the medicinal plant "patchouli" is studied, and its medicinal value and growth factors are discussed. Meanwhile, based on zigbee technology, we design a set of feasible monitoring scheme including hardware and software. The hardware part used ZigBee wireless network design, mainly relies on the cc2530 chip and the esp8266 wifi chip to carry on the wireless distance transmission to the sensor data. It interacts between OneNET cloud server and mysql database through MQTT protocol, TCP/IP protocol and HTTP protocol.

Deep Learning-Based Intrusion Detection for Distributed Denial of Service Attack in Agriculture 4.0

Smart Agriculture or Agricultural Internet of things, consists of integrating advanced technologies (e.g., NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm operations to improve the quality and productivity of agricultural products. The convergence of Industry 4.0 and Intelligent Agriculture provides new opportunities for migration from factory agriculture to the future generation, known as Agriculture 4.0. However, since the deployment of thousands of IoT based devices is in an open field, there are many new threats in Agriculture 4.0. Security researchers are involved in this topic to ensure the safety of the system since an adversary can initiate many cyber attacks, such as DDoS attacks to making a service unavailable and then injecting false data to tell us that the agricultural equipment is safe but in reality, it has been theft. In this paper, we propose a deep learning-based intrusion detection system for DDoS attacks based on three models, namely, convolutional neural networks, deep neural networks, and recurrent neural networks. Each model’s performance is studied within two classification types (binary and multiclass) using two new real traffic datasets, namely, CIC-DDoS2019 dataset and TON_IoT dataset, which contain different types of DDoS attacks.

Retracted: Soil monitoring and evaluation system using EDL‐ASQE: Enhanced deep learning model for IoT smart agriculture network

SummaryThe enormous growth of the Internet of Things (IoT) network provides abundant support to agriculture and development, which states the future scope of IoT‐based agriculture. In a recent scenario, agriculture IoT can be integrated with sensors, communication protocols, and microcontrollers for automated process executions to increase productivity. Moreover, deep learning effectiveness produces appropriate results and solves several real‐time issues related to agriculture‐based advancements. The proposed system presents the design of an IoT network communication system to estimate the soil conditions. Soil quality is an important factor in modernized agriculture, productivity enhancement, and hydrological cycles. By the soil quality analysis, the accurate prediction is very significant for sensible usage of resources. An enhanced deep learning model for IoT network‐based automated soil quality evaluation observes the complex soil features and meteorological factors with those concerns. Here, the real‐time samples are collected from the local area sensor network for analysis. The deep learning model is developed with big data fitting ability for soil quality prediction. The weight factors (W.F.) are derived for measuring the soil quality accurately. The proposed IoT network‐based agriculture structure allows a flexible approach to different types of crops and implementation in agricultural areas. Experimental results obtained in the laboratory and onsite confirmed the performance and reliability of the system. The result evaluations are carried out based on precision, accuracy, and processing time, and results show that the model achieves better results than compared models.

DESIGN OF AN INTELLIGENT IRRIGATION SYSTEM FOR A JUJUBE ORCHARD BASED ON IoT

This research aimed to develop an information acquisition and intelligent irrigation decision system based on the agricultural Internet of Things (IoT). The system consists of a field control terminal and a remote client, realizing control, real-time display, alarm, and other functions. The user may apply the upper and lower limit of soil relative water content as the irrigation decision threshold. The system automatically controls irrigation according to the threshold. In the calculation and analysis part of the system, the programming software Keil 5 was used for data collection and monitoring, database comparison, calculation and analysis, irrigation decision, and other functions.

Emerging Trends in the use of IoT in Agriculture and Food Supply Chain Management: A Theoretical Analysis

The last decade has seen the Internet of Things (IoT) taking the world by storm. IoT has the ability to provide a wide range of services in real-time without any form of human intervention. Its most recent application is in the field of agriculture and food supply chain management. The use of IoT in agriculture and food supply chain management is expected to boost agriculture production as well as improve the quality of food products supplied to customers among other things. The use of IoT in agriculture and food supply chain management has however, raises several issues and concerns including those relating to privacy.

Design of Plant Breeding System Based on one M2M Standard

With the continuous upgrading of the Internet of Things, cloud platform and intelligent control technology, the development of plant cultivation has become intelligent. Aiming at the problems of low intelligent degree of environmental monitoring, in this paper, combined with agricultural Internet of Things, a plant cultivation system based on one M2M platform was designed and developed. In addition, this paper takes succulent seedlings as the experimental object and designs a succulent seedling cultivation system to achieve the control expectation of this plant cultivation system.