Development and Performance Evaluation of a Solar-Powered Computer Vision and IoT-Enabled Autonomous Multi-Functional Agricultural Robot

Irrigation and pesticide application are the major agricultural practices that contribute to the increase of crop yield and sustainable crop management. Conventional water sprinklers and pesticide sprayers are widely used. However, most of these systems are based on conventional energy sources and require significant human involvement for operational decision making. Furthermore, the lack of advanced monitoring and autonomous control is often the cause of a wasteful use of water and agrochemicals. To address these limitations, this paper proposes to design and evaluate a multipurpose smart farming robot (MpSFR) with integrated autonomous control system, which can perform pesticide spraying and irrigation.The proposed MpSFR is a battery-powered, photovoltaic-powered robotic platform that integrates computer vision (CV) with Internet of Things (IoT) sensors for automated decision making and real-time field monitoring. The robot is modeled by a mobile platform with an intelligent control unit, a programmable pumping system, a solar photovoltaic module, a rechargeable battery and a liquid storage tank. Computer vision subsystem assesses crop health and detects symptoms of pests to apply pesticides as needed. Soil moisture sensors constantly monitor soil moisture levels in the field to estimate irrigation needs. The nozzle assembly is controlled by two servo motors for horizontal and vertical movements with accurate spraying and good crop canopy coverage. Furthermore, the system can be easily switched between irrigation and pesticide spraying modes using an infrared remote control within a range of 5 m.Field testing was done to assess the operational performance of the robot including its solar energy harvesting, battery charging/discharging functions, and autonomous watering and spraying functions. The results showed reliable operation, economical energy consumption, and efficient automation of water and pesticide application, indicating the potential of the developed MpSFR to improve precision agriculture, reduce labor costs, and promote sustainable farming practices.