An intelligent WSN-UAV-based IoT framework for precision agriculture application

• Published in: Computers & electrical engineering Vol. 100; p. 107912
• Main Authors: Singh, Pradeep Kumar, Sharma, Amit
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.05.2022; Elsevier BV
• Subjects: Agriculture; Climate change; Computer architecture; Data processing; Food; Internet of Things; Internet of Things (IoT); Performance evaluation; Productivity; Spraying; Trajectory planning; Unmanned aerial vehicles; Unmanned aerial vehicles (UAVs); Wireless sensor networks; Wireless Sensor Networks (WSNs); Data processing; Wireless Sensor Networks (WSNs); Internet of Things (IoT); Unmanned aerial vehicles (UAVs); Trajectory planning
• ISSN: 0045-7906; 1879-0755
• DOI: 10.1016/j.compeleceng.2022.107912

•Integration of WSN-UAV in Precision Agriculture.•Optimized trajectory design for efficient crop monitoring.•Performance evaluation in terms of sensing and monitoring crops.•Intelligent decision-making for spraying tasks to increase crop productivity.•The quality of extracted data is increased through multiple hierarchical steps of data processing.•Time response of network shows the reduction in communication cost, which allows lower latency for decision-making.•Coverage efficiency of 96.3% is achieved and has high potential in agricultural applications. Climate change has introduced many challenges, which affect various sectors including agriculture. The major challenge lies in increasing food productivity while confronting climatic changes. The recent advent of Information and Communication Technology (ICT) provides a solution to increase food productivity and address climate change issues in the agricultural domain. The growth of Wireless Sensor Networks (WSNs), Internet of Things (IoT) technologies, and particularly the introduction of Unmanned Aerial Vehicles (UAVs) leads to the development of economical precision agriculture applications. This article presents a platform for managing agricultural crop information collected through multi-rotor UAV. The Django framework is utilized to design the information service system to collect the crop information and position information from UAV in real-time. An extensive performance evaluation is conducted for sensing and monitoring crops exploiting the proposed architecture. The proposed architecture presents a coverage efficiency of 96.3% and has high potential in agricultural applications such as crop health monitoring, spraying fertilizers, and pesticides. [Display omitted]