Crop Yield Estimation Using the Internet of Things
30 Jan 2021-Journal of Information & Knowledge Management (World Scientific Publishing Company)-Vol. 20, pp 2140006
TL;DR: In this article, the authors proposed that the Internet of Things (IoT) in the current era is liable for its drastic transforming impact on human life, especially in the agricultural sector.
Abstract: Internet of Things (IoT) in the current era is liable for its drastic transforming impact on human life, especially in the agricultural sector. IoT has transformed conventional agriculture into sma...
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TL;DR: In this paper , the authors investigated the tools and equipment used in applications of wireless sensors in IoT agriculture, and the anticipated challenges faced when merging technology with conventional farming activities, and this technical knowledge is helpful to growers during crop periods from sowing to harvest.
Abstract: Smart farming is a development that has emphasized information and communication technology used in machinery, equipment, and sensors in network-based hi-tech farm supervision cycles. Innovative technologies, the Internet of Things (IoT), and cloud computing are anticipated to inspire growth and initiate the use of robots and artificial intelligence in farming. Such ground-breaking deviations are unsettling current agriculture approaches, while also presenting a range of challenges. This paper investigates the tools and equipment used in applications of wireless sensors in IoT agriculture, and the anticipated challenges faced when merging technology with conventional farming activities. Furthermore, this technical knowledge is helpful to growers during crop periods from sowing to harvest; and applications in both packing and transport are also investigated.
14 citations
25 Jun 2022
TL;DR: This survey examines several techniques based on crop prediction in the IoT network based on publication year, research technique, implementation tools, performance measures and achievement of the research methodologies towards crop prediction techniques in IoT network.
Abstract: In the agriculture domain, the main issues determined are knowledge deficiencies regarding alterations in climate. As each crop poses its own climatic features, but the issues confronted in agriculture are managed using precise farming methods. The precision farming assists in fulfilling the demand for food, maintaining crop productivity, and increasing the yield rate. In India, the emerging needs require sustainable agriculture. The two main issues in agriculture are the selection of crops and altering climatic conditions, which are solved by examining prediction and monitoring techniques, but there is no solution for the crop suggestion. This survey examines several techniques based on crop prediction in the IoT network. This study utilizes 25 research papers focused on several methods, and review of researches based on the classical technique is devised. The assessment is done based on publication year, research technique, implementation tools, performance measures and achievement of the research methodologies towards crop prediction techniques in IoT network. At the end, the research gaps and issues of the existing techniques are devised in such a way that the motivation for developing an effective method for crop prediction techniques in IoT network is revealed.
1 citations
26 Dec 2022
TL;DR: In this article , the YOLO approach is used in Matlab ® employing Image Labeler that detect an object, identify tomatoes, and count the quantity of tomatoes in real time.
Abstract: Agriculture undoubtedly among the most significant and popular practiced employment in India, & it plays crucial role in the growth of our country. In the passing year, there's been tremendous advancement throughout the computer vision domain of object identification. A further breakthrough is the utilization of computer vision applications in agricultural to boost precision farming. This project demonstrates object identification in both pictures and videos, which might be useful for farmers to recognize and count the same thing taken in a photo or in real time. The YOLO approach is used in Matlab ® employing Image Labeler that detect an object, identify tomatoes, and count the quantity of tomatoes
26 Dec 2022
TL;DR: In this article , the YOLO approach is used in Matlab ® employing Image Labeler that detect an object, identify tomatoes, and count the quantity of tomatoes in real time.
Abstract: Agriculture undoubtedly among the most significant and popular practiced employment in India, & it plays crucial role in the growth of our country. In the passing year, there's been tremendous advancement throughout the computer vision domain of object identification. A further breakthrough is the utilization of computer vision applications in agricultural to boost precision farming. This project demonstrates object identification in both pictures and videos, which might be useful for farmers to recognize and count the same thing taken in a photo or in real time. The YOLO approach is used in Matlab ® employing Image Labeler that detect an object, identify tomatoes, and count the quantity of tomatoes
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TL;DR: The main objective of this paper is to provide an overview of Internet of Things, architectures, and vital technologies and their usages in the authors' daily life and this manuscript will give good comprehension for the new researchers and facilitate knowledge accumulation in efficiently.
Abstract: One of the buzzwords in the Information Technology is Internet of Things (IoT). The future is Internet of Things, which will transform the real world objects into intelligent virtual objects. The IoT aims to unify everything in our world under a common infrastructure, giving us not only control of things around us, but also keeping us informed of the state of the things. In Light of this, present study addresses IoT concepts through systematic review of scholarly research papers, corporate white papers, professional discussions with experts and online databases. Moreover this research article focuses on definitions, geneses, basic requirements, characteristics and aliases of Internet of Things. The main objective of this paper is to provide an overview of Internet of Things, architectures, and vital technologies and their usages in our daily life. However, this manuscript will give good comprehension for the new researchers, who want to do research in this field of Internet of Things (Technological GOD) and facilitate knowledge accumulation in efficiently.
1,062 citations
TL;DR: A cross-layer-based channel access and routing solution for sensing and actuating is proposed for monitoring and controlling agriculture and farms in rural areas and reduces network latency up to a certain extent.
Abstract: Internet of Things (IoT) gives a new dimension in the area of smart farming and agriculture domain. With the use of fog computing and WiFi-based long distance network in IoT, it is possible to connect the agriculture and farming bases situated in rural areas efficiently. To focus on the specific requirements, we propose a scalable network architecture for monitoring and controlling agriculture and farms in rural areas. Compared to the existing IoT-based agriculture and farming solutions, the proposed solution reduces network latency up to a certain extent. In this, a cross-layer-based channel access and routing solution for sensing and actuating is proposed. We analyze the network structure based on coverage range, throughput, and latency.
356 citations
TL;DR: The results from the review were compiled into an IoT architecture that represents a wide range of current solutions in agro-industrial and environmental fields that are motivated by the need to identify application areas, trends, architectures and open challenges in these two fields.
Abstract: Systematic literature review of IoT applications in agro-industry and environment during 20062016.Clustering of IoT applications into four domains: monitoring, control, prediction, and logistics.Visualization of key technologies used to develop the IoT applications.Discussion of trends and open challenges.Proposal of an IoT architecture for agro-industrial and environmental applications based on the research findings. This paper reviews agro-industrial and environmental applications that are using Internet of Things (IoT). It is motivated by the need to identify application areas, trends, architectures and open challenges in these two fields. The underlying survey was developed following a systematic literature review using academic documents written in English and published in peer-reviewed venues from 2006 to 2016. Selected references were clustered into four application domains corresponding to: monitoring, control, logistics, and prediction. Implementation-specific details from each selected reference were compiled to create usage distributions of sensors, actuators, power sources, edge computing modules, communication technologies, storage solutions, and visualization strategies. Finally, the results from the review were compiled into an IoT architecture that represents a wide range of current solutions in agro-industrial and environmental fields.
336 citations
TL;DR: The paper proposes the advantages of having ICT in Indian agricultural sector, which shows the path for rural farmers to replace some of the conventional techniques by utilizing water resource efficiently and also reducing labour cost.
Abstract: Agriculture sector in India is diminishing day by day which affects the production capacity of ecosystem. There is an exigent need to solve the problem in the domain to restore vibrancy and put it back on higher growth. The paper proposes an e-Agriculture Application based on the framework consisting of KM-Knowledge base and Monitoring modules. To make profitable decisions, farmers need information throughout the entire farming cycle. The required information is scattered in various places which includes real time information such as market prices and current production level stats along with the available primary crop knowledge. A knowledge dataflow model is constructed connecting various scattered sources to the crop structures. The world around is getting automated replacing manual procedures with the advancement of technology, since it is energy efficient and engross minimal man power. The paper proposes the advantages of having ICT in Indian agricultural sector, which shows the path for rural farmers to replace some of the conventional techniques. Monitoring modules are demonstrated using various sensors for which the inputs are fed from Knowledge base. A prototype of the mechanism is carried out using TI CC3200 Launchpad interconnected sensors modules with other necessary electronic devices. A comparative study is made between the developed system and the existing systems. The system overcomes limitations of traditional agricultural procedures by utilizing water resource efficiently and also reducing labour cost.
204 citations
TL;DR: This study presents a smart agriculture IoT system based on deep reinforcement learning which includes four layers, namely agricultural data collection layer, edge computing layer, agricultural data transmission layer, and cloud computing layer.
Abstract: Smart agriculture systems based on Internet of Things are the most promising to increase food production and reduce the consumption of resources like fresh water. In this study, we present a smart agriculture IoT system based on deep reinforcement learning which includes four layers, namely agricultural data collection layer, edge computing layer, agricultural data transmission layer, and cloud computing layer. The presented system integrates some advanced information techniques, especially artificial intelligence and cloud computing, with agricultural production to increase food production. Specially, the most advanced artificial intelligence model, deep reinforcement learning is combined in the cloud layer to make immediate smart decisions such as determining the amount of water needed to be irrigated for improving crop growth environment. We present several representative deep reinforcement learning models with their broad applications. Finally, we talk about the open challenges and the potential applications of deep reinforcement learning in smart agriculture IoT systems.
202 citations