AI-Powered Tablet Identification and Information Extraction System Using Image Recognition and Optical Character Recognition

AI-Powered Tablet Identification and Information Extraction System Using Image Recognition and Optical Character Recognition

연구 분야: Safety

학회: 2025 6th International Conference on Recent Advances in Information Technology (RAIT)

The smart healthcare monitoring system of today’s contemporary computing environment enables early fall detection prediction. The health care service sector benefits greatly from the Internet of Things-based health model, which enhances data processing and prediction. It takes too much time and effort to move reports or data from one location to another, and it will result in significant latency and energy problems. Edge computing offers ways to deal with these kinds of risks. This article outlines the problems, services, and applications of the smart healthcare system. Additionally, suggest a CNN-based prediction model that makes advantage of edge computing and Internet of Things concepts. For rapid response times and resource availability, edge computing makes use of local servers at IoT endpoints. Additionally, the purpose of edge devices is to use edge servers to deliver fast health-prediction results to physicians and patients. It is possible to assess the suggested mechanism by applying performance metrics like accuracy and error rate.