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

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...

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Main Authors: Sirisha N., V Revathi, Albawi Ali, Gupta Navya, Singh Navdeep, Krishnamoorthy Murugaperumal
Format: Article
Language:English
Published: EDP Sciences 2025-01-01
Series:E3S Web of Conferences
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Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/19/e3sconf_icsget2025_03003.pdf
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author Sirisha N.
V Revathi
Albawi Ali
Gupta Navya
Singh Navdeep
Krishnamoorthy Murugaperumal
author_facet Sirisha N.
V Revathi
Albawi Ali
Gupta Navya
Singh Navdeep
Krishnamoorthy Murugaperumal
author_sort Sirisha N.
collection DOAJ
description 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.
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id doaj-art-e243d4a4565a46629989f90ed9e7bedc
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issn 2267-1242
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series E3S Web of Conferences
spelling doaj-art-e243d4a4565a46629989f90ed9e7bedc2025-08-20T03:04:30ZengEDP SciencesE3S Web of Conferences2267-12422025-01-016190300310.1051/e3sconf/202561903003e3sconf_icsget2025_03003AI-Driven Predictive Health Monitoring and Early Warning Systems for Enhanced Soldier Safety in IoT-Enabled Wearable DevicesSirisha N.0V Revathi1Albawi Ali2Gupta Navya3Singh Navdeep4Krishnamoorthy Murugaperumal5Department of Computer Science and Engineering, MLR Institute of TechnologyDepartment of Applied Sciences, New Horizon College of EngineeringRadiology Techniques Department, College of Medical Technology, The Islamic UniversityLloyd Law CollegeLovely Professional UniversityDepartment of Electrical and Electronics Engineering, Vardhaman College of EngineeringFor 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.https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/19/e3sconf_icsget2025_03003.pdfsmart soldier monitoringiot-based soldier trackingreal- time health monitoringpredictive analytics for soldier safetybattlefield iot systems
spellingShingle Sirisha N.
V Revathi
Albawi Ali
Gupta Navya
Singh Navdeep
Krishnamoorthy Murugaperumal
AI-Driven Predictive Health Monitoring and Early Warning Systems for Enhanced Soldier Safety in IoT-Enabled Wearable Devices
E3S Web of Conferences
smart soldier monitoring
iot-based soldier tracking
real- time health monitoring
predictive analytics for soldier safety
battlefield iot systems
title AI-Driven Predictive Health Monitoring and Early Warning Systems for Enhanced Soldier Safety in IoT-Enabled Wearable Devices
title_full AI-Driven Predictive Health Monitoring and Early Warning Systems for Enhanced Soldier Safety in IoT-Enabled Wearable Devices
title_fullStr AI-Driven Predictive Health Monitoring and Early Warning Systems for Enhanced Soldier Safety in IoT-Enabled Wearable Devices
title_full_unstemmed AI-Driven Predictive Health Monitoring and Early Warning Systems for Enhanced Soldier Safety in IoT-Enabled Wearable Devices
title_short AI-Driven Predictive Health Monitoring and Early Warning Systems for Enhanced Soldier Safety in IoT-Enabled Wearable Devices
title_sort ai driven predictive health monitoring and early warning systems for enhanced soldier safety in iot enabled wearable devices
topic smart soldier monitoring
iot-based soldier tracking
real- time health monitoring
predictive analytics for soldier safety
battlefield iot systems
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/19/e3sconf_icsget2025_03003.pdf
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