Secured HealthCare M-IoT
Sohan Dixit, Bhomaram Dewasi, Mahesh Pawale, Vaishnavi Mahajan, Shweta Bawiskar
Department of Computer Engineering
Genba Sopanrao Moze College of Engineering, Balewadi, Pune 45
-------------------------------------------------------------***--------------------------------------------------------------
Abstract - As wireless technology continues to grow in the healthcare industry, medical devices have become increasingly connected, enabling real-time monitoring and diagnosis for patients. However, this connectedness also poses security risks, putting sensitive data and patient safety at risk.
One solution to these vulnerabilities is the use of Body Sensor Networks (BSNs), which are designed to operate autonomously and connect various medical devices. BSNs utilize sensors and implants inside and/or outside the human body to provide opportunities for flexible operations and cost savings for both healthcare workers and patients.
The suggested system for BSNs includes an Android application and a Raspberry Pi unit with cloud connectivity and secure data access, providing real-time acquisition and analysis of various important parameters of the patient. By enabling seamless data collection, sharing, and storage, the system offers a high-quality patient experience while also supporting medical personnel in delivering effective care. Additionally, by eliminating manual data collection, the system helps to reduce human error and improve accuracy.
Overall, the implementation of intelligent health monitoring systems, such as BSNs, is a critical step towards ensuring patient safety and securing sensitive medical data. With the ability to collect, store, and analyze data in real-time, BSNs offer a unique service that can only be provided by a system that supports medical personnel from delivery to delivery.
Keywords - Body Sensor Network (BSN), Medical Devices, Wireless Technology, Security Vulnerabilities, Connectedness, Healthcare Sector, Real-time Monitoring, Data Analysis, Patient Safety, Cloud Connectivity, Android Application, Raspberry Pi, Intelligent Health Monitoring, Flexible Operations, Cost Savings, Manual Data Collection, Mass Monitoring.
