AI-Driven Predictive Health Monitoring and Early Warning Systems for Enhanced Soldier Safety in IoT-Enabled Wearable Devices

¹ Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad, Telangana, India.
² Department of Applied Sciences, New Horizon College of Engineering, Bangalore, India.
³ Radiology Techniques Department, College of Medical Technology, The Islamic University, Najaf, Iraq.
⁴ Lloyd Law College, Plot No. 11, Knowledge Park II, Greater Noida, Uttar Pradesh, 201308, India.
⁵ Lovely Professional University, Phagwara, India
⁶ Department of Electrical and Electronics Engineering, Vardhaman College of Engineering, Hyderabad, Telangana, India

^* Corresponding Author: nallashirisha@mlrinstitutions.ac.in

Abstract

For modern military operations regarding the safety and the situational awareness of soldiers in combat is paramount. In this paper we proposed an IoT based Soldier Status Monitoring System (SSMS) to address the Soldier Status issue to increase the battlefield awareness by provide real time soldier location tracking, health monitoring and alerts to the soldiers who are in danger. Multiple smart sensors like gas sensors, motion sensors, biometric sensors, metal detectors are integrated in helmet and boots of each soldier into the system. In the end, an IoT feeds soldiers’ locations back to a centralized command via GPS communications. In addition, an SOS switch enables soldiers to invoke an emergency channel. Using predictive analytics and machine learning, the system is able to identify early indications of danger or degradation to health that could mean increasing soldier safety. End to end encryption ensuresdata security and energy harvesting technology eases the burden of energy application on the computing device. This system represents a comprehensive solution to making soldiers safer, able to better communicate, and more operationally efficient on the modern battlefield.