Advanced UAV-WSN System for Intelligent Monitoring in Precision Agriculture

Area of Science:

• Agricultural Science
• Computer Science
• Engineering

Background:

• Global food demand necessitates advancements in agricultural technology for increased productivity and sustainability.
• Precision agriculture requires sophisticated monitoring and decision-making tools for efficient crop management.

Purpose of the Study:

• To present a hierarchical structure integrating unmanned aerial vehicles (UAVs) with federated wireless sensor networks (WSNs) for enhanced crop monitoring.
• To evaluate the efficacy of this collaborative UAV-WSN-IoT system in precision and ecological agriculture.

Main Methods:

• Designing optimized UAV trajectories for efficient data collection.
• Implementing in situ data processing algorithms (consensus and symbolic aggregate approximation) at the network level.
• Integrating UAVs with intelligent ground WSNs and the Internet of Things (IoT) for data management.

Main Results:

• The collaborative UAV-WSN-IoT system demonstrated robust and efficient data collection, control, analysis, and decision-making.
• Optimized UAV trajectories and network-level data processing effectively managed network load and latency.
• The system proved successful in increasing performance for both precision and ecological agriculture applications.

Conclusions:

• The integration of UAVs and WSNs offers a powerful solution for modern agricultural monitoring.
• This collaborative approach significantly improves the efficiency and effectiveness of precision agriculture practices.
• The developed system contributes to sustainable agriculture by optimizing resource management and crop yields.