Harnessing the Power of Artificial Intelligence and the Internet of Things for Improved Epidemic Forecasting

Abstract

The resurgence of infectious diseases demands innovative forecasting and management strategies. Integrating artificial intelligence (AI) with the internet of things (IoT) offers a groundbreaking approach to epidemic prediction. This study highlights the combined power of AI algorithms and IoT technology in creating sophisticated epidemic models. The authors explore cutting-edge AI methods, like machine learning and deep learning, to analyze vast epidemiological data from IoT devices, including wearables and mobile phones. This integration facilitates early outbreak detection, precise risk evaluation, and prompt interventions. Additionally, they address ethical and privacy issues related to health data, promoting careful information handling. This analysis shows that AI and IoT synergy not only sharpens epidemic forecasting but also boosts public health response efficiency, aiding in epidemic control and enhancing global health security.