GPS-Guided Solar Robot for Smart Lawn Maintenance with Live Streaming

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Peram Tharun Kumar Reddy
Gollakandriga Lohith
Kavitha K

The growing demand for efficient and sustainable lawn maintenance systems has led to the development of automated solutions that minimize human effort and environmental impact. Conventional grass-cutting methods rely heavily on manual operation or fuel-powered machines, which are not only labor-Intensive but also contribute to noise and air pollution. To address these limitations, this study presents a GPS-guided solar-powered robotic system integrated with Internet of Things (IoT) technology and live video monitoring.


The proposed system is designed using an ESP32 microcontroller, which enables wireless communication and real-time control. A solar panel combined with a Maximum Power Point Tracking (MPPT) charge controller is used to optimize energy harvesting and ensure efficient battery charging. The system is equipped with ultrasonic sensors for obstacle detection, allowing the robot to navigate safely in dynamic environments. Additionally, a GPS module is incorporated to provide accurate location tracking, enabling efficient area coverage and navigation.


Furthermore, an ESP32-CAM module is used to provide live video streaming, allowing users to monitor the robot remotely. The integration of IoT facilitates real-time data transmission and remote control through a web interface. Experimental analysis shows that the system operates with stable voltage levels, efficient energy utilization, and reliable performance in real-time conditions. The results confirm that the proposed system offers a cost-effective, eco-friendly, and intelligent solution for automated lawn maintenance applications.

GPS-Guided Solar Robot for Smart Lawn Maintenance with Live Streaming. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(3), 1311-1323. https://doi.org/10.51583/IJLTEMAS.2026.150300114

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GPS-Guided Solar Robot for Smart Lawn Maintenance with Live Streaming. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(3), 1311-1323. https://doi.org/10.51583/IJLTEMAS.2026.150300114