Locating Patient Health Data Theft Using Gradient Boosting with Hybrid Microwave Transmission-Based Wearable Device

The research article addresses the intersection of healthcare monitoring and crime prevention via wearable devices in hospital settings. It proposes a system leveraging blockchain, decision-making algorithms, and wireless communication, particularly IoT and gradient-boosting approaches. Existing health care monitoring lacks real-time intervention capabilities, and conventional crime prevention methods are often reactive rather than proactive. The revolutionary combination of gradient boosting and hybrid microwave transmission-based wearable devices is the ultimate solution to combat patient health data theft. With this cutting-edge technology, this research can confidently detect and prevent unauthorised access to sensitive healthcare information, ensuring the safety and privacy of patients. The proposed system ensures continuous health monitoring and prompt interventions while enhancing crime prevention through mobile data analysis. Blockchain and decision-making algorithms are integrated to securely store patient data and enable authorised personnel access for review. IoT and gradient-boosting algorithms facilitate real-time health monitoring and accurate prediction of crime-related patterns through mobile data analysis. The proposed gradient boosting algorithm has an RMSE of 0.105 and an MAE of 0.010, suggesting great prediction accuracy. With a V AF score of 96% and an R-squared score of 0.94, it captures data variability while demonstrating predictive solid power. This comprehensive strategy utilises cutting-edge technology to enhance healthcare monitoring via wearable devices, contribute to crime prevention, and address crucial concerns in healthcare and public safety.