Lattice: A Vision for Machine Learning, Data Engineering, and Policy Considerations for Digital Agriculture at Scale

Chaterji, Somali; DeLay, Nathan D.; Evans, John; Mosier, Nathan S.; Engel, Bernard A.; Buckmaster, Dennis R.; Ladisch, Michael R.; Chandra, Ranveer

doi:10.1109/ojcs.2021.3085846

Cited by 23 publications

(13 citation statements)

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“…Among the major problems to be remitted, one is the security of the big data [139][140][141]. IoT devices accumulate huge data from an agricultural IoT system, which can be viewed by an unauthorized access due to the paucity of the necessary security protocols by some of the IoT providers [142,143]. Hence, the data may suffer manipulation or other ownership problems.…”

Section: Major Obstacles For Implementation Of Iot and Smart Techniquesmentioning

confidence: 99%

Application of Smart Techniques, Internet of Things and Data Mining for Resource Use Efficient and Sustainable Crop Production

et al. 2023

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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.

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Section: Major Obstacles For Implementation Of Iot and Smart Techniquesmentioning

confidence: 99%

Application of Smart Techniques, Internet of Things and Data Mining for Resource Use Efficient and Sustainable Crop Production

et al. 2023

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“…Regarding data security, the obtained information from IoT systems in farms is collected, processed, and commercially exploited by service providers to varying degrees. Therefore, one of the most important problems of policies regards the validity and legal status of farm data [130]. In reality, these data are of great value when aggregated and analyzed for large-scale agricultural activities.…”

Section: Technical Problemsmentioning

confidence: 99%

IoT-Enabled Smart Agriculture: Architecture, Applications, and Challenges

et al. 2022

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The growth of the global population coupled with a decline in natural resources, farmland, and the increase in unpredictable environmental conditions leads to food security is becoming a major concern for all nations worldwide. These problems are motivators that are driving the agricultural industry to transition to smart agriculture with the application of the Internet of Things (IoT) and big data solutions to improve operational efficiency and productivity. The IoT integrates a series of existing state-of-the-art solutions and technologies, such as wireless sensor networks, cognitive radio ad hoc networks, cloud computing, big data, and end-user applications. This study presents a survey of IoT solutions and demonstrates how IoT can be integrated into the smart agriculture sector. To achieve this objective, we discuss the vision of IoT-enabled smart agriculture ecosystems by evaluating their architecture (IoT devices, communication technologies, big data storage, and processing), their applications, and research timeline. In addition, we discuss trends and opportunities of IoT applications for smart agriculture and also indicate the open issues and challenges of IoT application in smart agriculture. We hope that the findings of this study will constitute important guidelines in research and promotion of IoT solutions aiming to improve the productivity and quality of the agriculture sector as well as facilitating the transition towards a future sustainable environment with an agroecological approach.

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“…The data lifecycle in agriculture consists of data generation, warehousing, cleaning, annotation, and processing to optimize or improve agricultural production while maintaining the quality of the environment (Chaterji et al., 2020). In the following section, we briefly describe each of these steps.…”

Section: Applications Of Iot In Digital Agriculturementioning

confidence: 99%

Internet of Things (IoT) in digital agriculture: An overview

et al. 2023

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Climate change, land degradation, and limited land and water resources have challenged our ability to meet the food demand of a rapidly growing population. To tackle this challenge, modern agricultural systems are relying on new technologies like the Internet of Things (IoT) to improve agricultural productivity and resource use efficiency. Although IoT has gained considerable attention in the last few years, the key concepts of IoT and their applicability across different domains of agriculture are still new to many researchers, practitioners, managers, and policymakers. In this paper, we provide a comprehensive review of the use of different IoT platforms, wireless sensor networks, and other associated technologies like remote sensing, cloud computing, and big data analytics in digital agriculture. The review also explores the use of communication technologies, microcontrollers, and machine learning in smart irrigation and decision support systems. The necessity of interoperability (data transfer and communication without human interference) among devices is discussed in detail with regard to facilitating and exchanging agricultural data more effectively. The discussion also includes opportunities and challenges in standardizing IoT; developing energy‐efficient and affordable technologies; and improving data collection, transfer, storage, processing, security, anonymity, and privacy. This paper further calls for collaborative research in sensor and communication technologies in the agricultural sector.

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Lattice: A Vision for Machine Learning, Data Engineering, and Policy Considerations for Digital Agriculture at Scale

Cited by 23 publications

References 50 publications

Application of Smart Techniques, Internet of Things and Data Mining for Resource Use Efficient and Sustainable Crop Production

Application of Smart Techniques, Internet of Things and Data Mining for Resource Use Efficient and Sustainable Crop Production

IoT-Enabled Smart Agriculture: Architecture, Applications, and Challenges

Internet of Things (IoT) in digital agriculture: An overview

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