Intellectual Property India Publishes Patent Application for Design And Development Of An Ai-Based Dental Disease Detection System Using Esp32-Cam And Deep Learning

MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202621056667 A) filed by Sayali Harish Zade; Mr. Rahul Walde; Mr. Sandesh Lokhande; Dr. Pradnya Morey; Dr. Harna Bodele; Prof. Avinash Ikhar; Prof. Sumedh Jadhav; Dr. Shrikant Sonekar; Dr. Pravin Kshirsagar; Mr. Chetan Chandel; and Mr. Pranay Bhawarkar on May 04, 2026, for Design And Development Of An Ai-Based Dental Disease Detection System Using Esp32-Cam And Deep Learning.

Inventors include Sayali Harish Zade; Dr. Shrikant Sonekar; Dr. Pravin Kshirsagar; Mr. Chetan Chandel; Mr. Pranay Bhawarkar; Mr. Rahul Walde; Mr. Sandesh Lokhande; Dr. Pradnya Morey; Dr. Harna Bodele; Prof. Avinash Ikhar; and Prof. Sumedh Jadhav.

The application for the patent was published on July 31, 2026, under issue no. 31/2026.

Abstract: The early detection of dental diseases, such as tooth cracks, is important to avoid severe complications and tooth loss. However, the current diagnostic procedures for detecting tooth cracks and other dental diseases rely on manual inspection and radiographic examination. These procedures might not detect minor cracks and changes in the tooth. These procedures also require expensive equipment and special dental clinics, which might not be feasible for people living in remote areas and rural regions of the country. The present project proposes the design and development of an AI-based system for the detection of dental diseases, using the ESP32-CAM module and the YOLO model. This system works by using the ESP32-CAM module to capture images of the teeth and then transmitting the images to a system for analysis. The images captured by the ESP32-CAM module use the YOLO model to analyze the images and detect tooth cracks by highlighting the abnormal areas of the images. This system works by using the Internet of Things (IoT) and the power of deep learning to create a system for the diagnosis of dental diseases. This system works by using a web interface to display the results of the detection. The system seeks to develop a low-cost, portable, and intelligent dental screening system to improve early diagnosis, accessibility to dental healthcare, and assist dentists in efficiently detecting dental abnormalities.

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