MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202641007456 A) filed by G Ashwin Prabhu; Dr. A Kalyan Charan; Dr. Pallavi Khare; Dr. C Venkateshwar Reddy; Mr. K V Sai Pavan; Mr. Aleddula Abhishek Reddy; and Mr. M Bhargava Chandra, Chennai, Tamil Nadu, on Jan. 26, for 'design of modular agricultural robotic system (mars) for plant health monitoring.'
Inventor(s) include Dr. A Kalyan Charan; Dr. Pallavi Khare; Dr. C Venkateshwar Reddy; Mr. K V Sai Pavan; Mr. Aleddula Abhishek Reddy; and Mr. M Bhargava Chandra.
The application for the patent was published on Feb. 13, under issue no. 07/2026.
According to the abstract released by the Intellectual Property India: "Modern agriculture is undergoing a significant transformation driven by the adoption of smart technologies to address challenges such as labor shortages, crop health degradation, climate variability, and the growing demand for sustainable food production. In this context, agricultural robotics combined with artificial intelligence (AI) and sensor-based monitoring has emerged as a promising solution for precision farming. This paper presents the design and development of a Modular Agricultural Robotic System (MARS) aimed at efficient plant health monitoring and real-time environmental data acquisition. The proposed MARS platform integrates AI/ML-based image processing techniques to assess plant leaf conditions and classify them as healthy or diseased at an early stage. In addition to visual inspection, the system continuously monitors key environmental parameters such as temperature and humidity, which play a crucial role in crop growth and disease propagation. The collected data are processed both locally using edge computing and remotely through cloud connectivity, enabling real-time visualization, long-term storage, and advanced data analytics for informed decision-making. A distinguishing feature of the MARS platform is its modular mechanical design, which allows flexible configuration and easy adaptation to different agricultural tasks and field conditions. The robot is capable of traversing uneven terrains, including muddy, sandy, and rocky surfaces commonly encountered in farmlands. The modular architecture also facilitates future upgrades and scalability without major structural modifications. By combining robotics, artificial intelligence, edge computing, and cloud-based analytics, the proposed system significantly reduces manual intervention, enhances early disease detection, and improves overall farm productivity. The MARS platform offers a reliable, scalable, and cost-effective solution for precision agriculture, contributing toward sustainable farming practices and intelligent crop management in modern agricultural ecosystems."
Disclaimer: Curated by HT Syndication.
