Trajectory Design for UAV-Based Data Collection Using Clustering Model in Smart Farming

Sensors

卷:22

Zouheir Trabelsi¹  Kadhim Hayawi²  Asad Malik³  Tariq Qayyum³ 

[1] College of Information Technology, United Arab Emirates University, Abu Dhabi P.O. Box 17551, United Arab Emirates;

[2] College of Technological Innovation, Zayed University, Abu Dhabi P.O. Box 144534, United Arab Emirates;

[3] Department of Computing, School of Electrical Engineering and Computer Science, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan;

关键词: clustering;    fog computing;    smart farming;    swarm UAVs;    IoT;    sensors;   

DOI  :  10.3390/s22010037

来源: DOAJ

【 摘 要 】

Unmanned aerial vehicles (UAVs) play an important role in facilitating data collection in remote areas due to their remote mobility. The collected data require processing close to the end-user to support delay-sensitive applications. In this paper, we proposed a data collection scheme and scheduling framework for smart farms. We categorized the proposed model into two phases: data collection and data scheduling. In the data collection phase, the IoT sensors are deployed randomly to form a cluster based on their RSSI. The UAV calculates an optimum trajectory in order to gather data from all clusters. The UAV offloads the data to the nearest base station. In the second phase, the BS finds the optimally available fog node based on efficiency, response rate, and availability to send workload for processing. The proposed framework is implemented in OMNeT++ and compared with existing work in terms of energy and network delay.

【 授权许可】

Unknown