A Novel Air-to-Ground Communication Scheme for Advanced Big Data Collection in Smart Farming Using UAVs

Abstract

The evolution of Flying Ad Hoc Networks (FANETs) demands the development of advanced routing protocols that can address the unique challenges associated with Unmanned Aerial Vehicle (UAV) missions. This paper proposes a novel Air-to-ground, Energy-awaRe, mission-Oriented protocol, leveraging Fuzzy Logic (AERO-FL), to enhance UAV cooperation and optimize network performance in deterministic scanning operations. The study focuses on a Smart Farming (SF) scenario for extensive crop surveillance, which traditionally relies on a single UAV. This conventional approach is often inefficient because of its inability to enable real-time data transmission and its vulnerability to operational failures. The proposed system replaces the single UAV approach with a cooperative FANET comprising multiple UAVs, significantly reducing mission completion time while facilitating real-time data transmission through the cooperation of aerial and ground nodes. The simulation results demonstrate that AERO-FL outperforms established routing protocols in key performance metrics. These findings underscore the potential of AERO-FL in a variety of scanning applications, including traffic monitoring, environmental observation, disaster response, and military operations. By enabling UAV cooperation in a mission-oriented routing framework, this study provides a foundation for future research aimed at achieving full FANET capabilities.

Keywords

• Flying ad hoc networks
• air-to-ground communication
• routing protocols
• fuzzy logic
• smart agriculture
• network simulations