Deployment of Autonomous Vehicles in Agricultural and using Voronoi Partitioning

Tahilyani, Shailendra; Saxena, Surabhi; Karras, D.A.; Gupta, Shashi Kant; Dixit, Chandra Kumar; Haralayya, Bhadrappa

doi:10.1109/ickecs56523.2022.10060773

Cited by 3 publications

(1 citation statement)

References 20 publications

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“…Innovative algorithms, including SAGA for UAV selection and NSPGGA and DCXGA for coverage optimization, outperform existing methods. The paper [108] discusses the increasing need for agricultural mechanization. The paper introduces a Voronoi-based partitioning algorithm for finding optimal paths for intelligent vehicles and compares its results with various greedy approaches in solving the traveling salesperson problem for agricultural applications.…”

Section: Coverage Deployment For Suavsmentioning

confidence: 99%

Navigation and Deployment of Solar-Powered Unmanned Aerial Vehicles for Civilian Applications: A Comprehensive Review

Li,

Fang,

Verma

et al. 2024

Drones

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Unmanned aerial systems and renewable energy are two research areas that have developed rapidly over the last few decades. Solar-powered unmanned aerial vehicles (SUAVs) are likely to become dominant in the near future. They have the advantage of low cost and safe operation features that mitigate the barriers to their use in various environments. Developing effective algorithms for navigating and deploying SUAVs is essential for implementing this technology in real-life applications. Effective navigation and deployment algorithms also ensure the safety and efficiency of SUAV operations. This comprehensive review paper summarizes some state-of-the-art SUAV applications and provides an overview of the navigation and deployment algorithms for SUAVs. Some commonly used energy-harvesting models are described as well. Finally, some interesting and promising directions for future SUAV research are suggested.

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Section: Coverage Deployment For Suavsmentioning

confidence: 99%

Navigation and Deployment of Solar-Powered Unmanned Aerial Vehicles for Civilian Applications: A Comprehensive Review

Li,

Fang,

Verma

et al. 2024

Drones

View full text Add to dashboard Cite

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Smart Agriculture: Current State, Opportunities, and Challenges

Ahmed,

Shabbir,

Naqvi

et al. 2024

IEEE Access

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A Comprehensive Review of LiDAR Applications in Crop Management for Precision Agriculture

Farhan,

Yin,

Chen

et al. 2024

Sensors

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Precision agriculture has revolutionized crop management and agricultural production, with LiDAR technology attracting significant interest among various technological advancements. This extensive review examines the various applications of LiDAR in precision agriculture, with a particular emphasis on its function in crop cultivation and harvests. The introduction provides an overview of precision agriculture, highlighting the need for effective agricultural management and the growing significance of LiDAR technology. The prospective advantages of LiDAR for increasing productivity, optimizing resource utilization, managing crop diseases and pesticides, and reducing environmental impact are discussed. The introduction comprehensively covers LiDAR technology in precision agriculture, detailing airborne, terrestrial, and mobile systems along with their specialized applications in the field. After that, the paper reviews the several uses of LiDAR in agricultural cultivation, including crop growth and yield estimate, disease detection, weed control, and plant health evaluation. The use of LiDAR for soil analysis and management, including soil mapping and categorization and the measurement of moisture content and nutrient levels, is reviewed. Additionally, the article examines how LiDAR is used for harvesting crops, including its use in autonomous harvesting systems, post-harvest quality evaluation, and the prediction of crop maturity and yield. Future perspectives, emergent trends, and innovative developments in LiDAR technology for precision agriculture are discussed, along with the critical challenges and research gaps that must be filled. The review concludes by emphasizing potential solutions and future directions for maximizing LiDAR’s potential in precision agriculture. This in-depth review of the uses of LiDAR gives helpful insights for academics, practitioners, and stakeholders interested in using this technology for effective and environmentally friendly crop management, which will eventually contribute to the development of precision agricultural methods.

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Deployment of Autonomous Vehicles in Agricultural and using Voronoi Partitioning

Cited by 3 publications

References 20 publications

Navigation and Deployment of Solar-Powered Unmanned Aerial Vehicles for Civilian Applications: A Comprehensive Review

Navigation and Deployment of Solar-Powered Unmanned Aerial Vehicles for Civilian Applications: A Comprehensive Review

Smart Agriculture: Current State, Opportunities, and Challenges

A Comprehensive Review of LiDAR Applications in Crop Management for Precision Agriculture

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