Fog-Enabled IoT Robotic System for Efficient Date Palm Monitoring in Moroccan Oases

Abstract

Date palms are a vital resource in the oases of Morocco, providing economic and ecological benefits to local communities. However, monitoring these trees at scale presents challenges, particularly in rural areas where traditional IoT-based agricultural systems rely on extensive sensor networks. These systems face significant limitations, including high deployment costs, network coverage issues, and energy constraints. To address these challenges, we propose an agricultural robot equipped with multiple IoT sensors to monitor date palm health and environmental parameters, reducing the need for widespread fixed sensors. To overcome the latency, bandwidth, and energy inefficiencies associated with cloud-based solutions, the system integrates the fog computing paradigm. Fog computing brings computational resources closer to the data source, enabling real-time processing and decision-making while reducing network congestion. Using iFogSim, we evaluate the proposed system on key metrics, including latency, energy consumption, and network performance. The results demonstrate significant improvements over traditional approaches, highlighting the potential of IoT-based robotic systems combined with fog computing to revolutionize date palm monitoring in remote oases.