IJITEST_20261112155825_IJITEST-2026-027 20261112155825 International Journal of Innovative Trends in Engineering Science and Technology editor@ijitest.org Felix Academic Publications International Journal of Innovative Trends in Engineering Science and Technology IJITEST 3139-6887 05 2026 1 3 Yeduvaka Aslesha Likitha D vignan's Institute of Information and Technology CH. Swapna Priya vignan's Institute of Information and Technology Aishwarya A vignan's Institute of Information and Technology Anusha Somu B vignan's Institute of Information and Technology Safavath Mahalakshmi Bai C. vignan's Institute of Information and Technology Oral cancer is a dangerous health issue that touches thousands of lives annually, particularly in areas with poor access to healthcare centers. Early detection is critical to boosting survival rates, yet numerous individuals lack access to early diagnosis. In this research, we present a smart, light-weight solution through the application of MobileNetV2, a deep learning algorithm with high efficiency and speed. We have developed a simple web application wherein users can input photos of the oral cavity, and the system will immediately tell if there are cancer signs. With the utilization of a pre-trained MobileNetV2 model, our method provides accuracy in addition to running without any issues on low-power devices such as smartphones. The aim is to develop a useful device that can assist physicians and health workers—particularly in remote or underserved communities—and aid in the early detection of oral cancer, when it is most curable. 05 05 2026 121 125 https://creativecommons.org/licenses/by/4.0/ 10.5281/zenodo.24037943 https://ijitest.org/article/ijitest-2026-027 https://ijitest.org/api/files/published/IJITEST-2026-027-published.pdf