International Journal of Science, Engineering and TechnologyAuthors: Dr Raj Kumar, Ayush Kumar Anand, Harivansh Sharma, Devansh Rohila, Aman Jaiswal
Abstract: The rapid rise in digital health records has sparked a strong need for smart tools that convert unprocessed body data into practical medical decisions. This study introduces the Health Monitoring Dashboard (HMD), a unified web application combining data analytics, interactive visualization, and rule-based health insights. Developed using Microsoft Power BI, the platform leverages its built-in data connectors, DAX (Data Analysis Expressions) for metric calculations, Power Query for data transformation, and AI-powered visuals for predictive analytics. The interface features six components: filtering user conditions, aggregating key performance metrics, displaying time-based trends and cross-data relationships, applying rule-driven health thresholds, and offering an interactive machine learning testing environment via Power BI's integration with Azure Machine Learning. Tests confirm the system accurately handles inputs such as heart rate, blood pressure, sleep habits, steps taken, and physical activity with near-real-time dashboard refresh. Future improvements include direct integration with wearable device APIs (Fitbit, Garmin), secure cloud deployment via Power BI Service and Azure, row-level security for multi-user access, and advanced ML model integration through Azure ML pipelines. The results demonstrate that accessible BI tools can build reliable healthcare analytics systems and offer a replicable blueprint for others.
