Smart visual sensors for real time weather and ground conditions recognition for agricultural robotics

The dynamic and unpredictable nature of environmental elements, such as weather and ground conditions, profoundly influences the efficiency of agricultural robots. Real-time environmental perception is an enabling technology for several agricultural automatic systems, facilitating precise scheduling of tasks like planting, harvesting, and irrigation. Drawing inspiration from successful applications of computer vision in crop health monitoring and AI-driven weather impact prediction, in this paper we propose a system for simultaneous recognition of weather and ground conditions based on computer vision techniques. The system can run in real-time onboard smart cameras, making it affordable at low cost. After providing a detailed description of its architecture and methodology, we conduct extensive experiments to demonstrate the effectiveness of the system in real-world conditions and its significance in advancing agricultural robotics, fostering sustainable farming practices by optimizing resource utilization, and mitigating environmental impact.