MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541123411 A) filed by Dr. Mithun B Patil; Vijay Anappa Sangolgi; Vaishnavi Ramchandra Mashale; and Vardhan Anil Chinta, Kalaburagi, Karnataka, on Dec. 8, 2025, for 'multi-layer perception meets convolution: detecting lumpy skin disease with resmlp-cnn.'

Inventor(s) include Dr. Mithun B Patil; Vijay Anappa Sangolgi; Vaishnavi Ramchandra Mashale; and Vardhan Anil Chinta.

The application for the patent was published on Jan. 2, under issue no. 01/2026.

According to the abstract released by the Intellectual Property India: "A system and method to detect Lumpy Skin Disease (LSD) in cattle at an early stage and foretell its contagion utilize a hybrid AI model combined with sensor networks created by the Internet of Things (IoT). This innovation is at the forefront of the traditional detection methods, which rely on manual observations that are inaccurate and delayed and on laboratory tests, which are slow and expensive. These methods are the primary reasons behind farmers' significant economic losses due to milk production decrease, infertility, and cattle death. The hybrid model gist goes as it uses Residual Multi-Layer Perceptron (ResMLP) to handle tabular environmental data (temperature, humidity, geospatial metrics, etc.) and Convolutional Neural Network (CNN) to deal with the spatial features of livestock (skin nodule imagery captured via IoT-enabled cameras). The combination of data from different sources improves the forecast of the outbreak at an early stage. The system comprises IoT hardware, such as temperature/humidity sensors, GPS trackers, RFID readers, and solar-powered CCTV, for real-time on-field monitoring of cattle health. The data is sent to a cloud-based web platform (LSD Detect), which automatically issues risk alerts to farmers, veterinarians, and government agencies, thus, allowing quick intervention and disease surveillance on a large scale. The organizational diagram specifies software applications (e.g., feature display, prevention factors, veterinary advisory) and hardware integration (e.g., sensors, CCTV), whereas hardware and software modules support deployment and data analysis."

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