An AI-Based Intelligent System for Early Urban Health Risk Assessment

Abstract: Rapid urbanization and changing environmental conditions can affect public health in many ways. Factors such as temperature, humidity, rainfall, and air quality may increase the risk of different diseases. This research proposes an AI-Based Community Health Risk Assessment System to predict possible health risks in a community. The proposed system collects real-time and historical environmental data and uses Machine Learning to analyze the data and predict health risks. Based on the prediction, the system can provide early warnings and help authorities take preventive actions. The system also includes health risk hotspot detection feature to identify high risk areas in city based on environmental conditions and predicted health risk. In addition, the system collects combined symptoms reports from citizens and collects them with environmental data and health risk prediction. Using this information, the system generates AI based community health advisories to provide useful health warnings and guidance Overall, the system combines health risk prediction, early warning, hotspot detection, and health advisories in a single platform. It can help health authorities identify high-risk areas, take preventive measures, and make better data-based decisions to improve community health and safety.

Keywords: Artificial Intelligence, Machine Learning, Community Health, Health Risk Prediction, Environmental Data, Hotspot Detection, Early Warning System, Citizen Symptom Reports, Smart City, Public Health.