Smart Solar Grass Cutting Robot

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Authors: Ms.Mitali S. Chavan, Ms.Tanvi S. Mestry, Ms Bhumika S. Satardekar, Ms.Malini B. Warang, Ms.Gauri N. Rawool, Mrs.Shital A. Palav
Cited by: 0

Abstract

Agriculture is increasingly facing challenges such as labour shortages, rising fuel costs, and the need for environmentally sustainable practices. Traditional methods of grass cutting, seed sowing, and irrigation require continuous human effort and are often inefficient, time-consuming, and expensive. To overcome these limitations, automation combined with renewable energy has emerged as an effective solution. The Smart Solar Grass Cutting Robot (SSGCR) is designed as a multi-functional agricultural robot that operates using solar energy. The system integrates several farming operations such as grass cutting, seed sowing, water or pesticide spraying, and soil moisture monitoring into a single robotic platform. The robot is powered by a solar panel coupled with a rechargeable battery, enabling it to function independently without relying on fossil fuels or grid electricity. An Arduino Uno microcontroller serves as the central control unit, coordinating the operation of motors, sensors, and actuators. Wireless control is achieved using a Bluetooth module, allowing the user to operate the robot through a smartphone application. Obstacle detection is implemented using ultrasonic sensor to ensure safe and reliable operation in real agricultural environments. The proposed system reduces manual labour, minimizes operational costs, and decreases environmental pollution. Experimental results and observations indicate efficient task execution, low power consumption, and improved safety. The Smart Solar Grass Cutting Robot provides a cost-effective, eco-friendly, and user-friendly solution for modern agriculture and lawn maintenance, particularly suitable for rural and remote areas.

Fields of Study & Subjects

Smart Agriculture and AI Arduino and IoT Applications Agricultural Engineering and Mechanization

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
8 February 2026