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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM67665

AI-Powered Smart Safety Jacket for Industrial Application

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM67665

Volume:

10 |

10 |

Oct 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM67665

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Dr.Ranjit Bobate

Dr.Ranjit Bobate

Electronics and Communication

Priyadarshini College of Engineering , Nagpur

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Bhushan Shende

Bhushan Shende

Electronics and Communication

Priyadarshini College of Engineering , Nagpur

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Piyush Sarode

Piyush Sarode

Electronics and Communication

Priyadarshini College of Engineering , Nagpur

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Anurag Takote

Anurag Takote

Electronics and Communication

Priyadarshini College of Engineering , Nagpur

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Harsh Bansod

Harsh Bansod

Electronics and Communication

Priyadarshini College of Engineering , Nagpur

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Abstract

Industrial workers are frequently exposed to hazardous conditions such as gas leakage, poor air quality, physical accidents, excessive temperature, and delayed emergency response. Conventional safety equipment mainly provides passive protection and does not continuously monitor the health and surrounding conditions of workers. To address this problem, this paper presents an AI-powered smart safety jacket designed for real-time worker monitoring and emergency assistance.The proposed system integrates multiple sensors with an ESP32 microcontroller to continuously collect physiological and environmental information. A MAX30102 sensor is used for heart-rate and blood-oxygen monitoring, while a DS18B20 sensor measures body temperature. MQ-2 and MQ-135 sensors are used to detect combustible gases, smoke, and changes in air quality. An MPU6050 inertial measurement unit is incorporated for detecting abnormal motion and possible worker falls. A GPS module provides the worker's location, while a GSM module enables emergency communication through SMS. In addition, a buzzer, LED indicators, and vibration motor provide immediate local alerts to the worker.

KEYWORDS

Smart Safety Jacket Artificial Intelligence ESP32 Worker Safety Fall Detection Health Monitoring Gas Detection GPS GSM IoT Anomaly Detection.

Cite This Article

Dr.Ranjit Bobate, Bhushan Shende, Piyush Sarode, Anurag Takote, Harsh Bansod, "AI-Powered Smart Safety Jacket for Industrial Application," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 10, pp. 1-4, Oct 2026. https://doi.org/10.55041/IJSREM67665

Full Article/Conclusion

This paper presented an AI-powered smart safety jacket for monitoring industrial workers and detecting unsafe conditions. The proposed system combines health monitoring, environmental sensing, fall detection, GPS tracking, and GSM-based emergency communication using an ESP32. The jacket monitors heart rate, SpO₂, temperature, gas, air quality, and worker movement. When an abnormal condition is detected, the buzzer, LED, and vibration motor provide an immediate warning. In an emergency, GPS provides the worker's location and GSM sends an alert to a predefined contact. The proposed system provides an additional safety layer for workers and can help reduce the delay in emergency response. Future work can focus on improving AI-based detection, increasing battery life, and testing the system under different industrial conditions.

References

[1]  F. Wu, T. Wu, and M. R. Yuce, “Design and implementation of a wearable sensor network system for IoT-connected safety and health applications,” in Proc. IEEE 5th World Forum on Internet of Things (WF-IoT), 2019, pp. 87–90.  [2]   Y. Zhang, X. Wang, and H. Liu, “Development of a real-time wearable fall detection system in the context of Internet of Things,” IEEE Internet of Things Journal, vol. 9, no. 21, pp. 21999–22007, Nov. 2022, doi: 10.1109/JIOT.2022.3181701. [3]     D. Mohanapriya, S. K. Kabilesh, J. Nandhini, A. S. Sagayaraj, G. Kalaiarasi, and B. Saritha, “IoT-enabled smart helmet for site workers,” in Proc. IEEE/International Conference, 2022. [4]  S. R. Kawale, S. Mallikarjun, D. V. Gowda, K. D. V. Prasad, R. Shekhar, and N. V. Anil Kumar, “Design and implementation of an AI and IoT-enabled smart safety helmet for real-time environmental and health monitoring,” in Proc. 2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS),   2024,doi: 10.1109/ICITEICS61368.2024.10625126.  [5]    C. K. P. Chandrasena, “Design and implementation of a GSM-based IoT smart safety helmet for construction workers,” International Journal of Research and Innovation in Applied Science, vol. 10, no. 12, pp. 560–567, 2026, doi: 10.51584/IJRIAS.2025.10120042.  [6]         “Smart safety helmet for mining workers with environmental monitoring and alert system,” in IEEE Conference Publication, 2025. [7]     “IoT based wearable device for workers in industrial scenarios,” in IEEE Conference Publication, 2019. [8]    O. Ojetola, E. Gaura, and J. Brusey, “Fall detection with wearable sensors—SAFE (SmArt Fall dEtection),” in Proc. IEEE International Conference, 2011, pp. 318–321, doi: 10.1109/IE.2011.38.  [9]     S. R. Patnaik, K. Singh, V. Udutalapally, and D. Das, “iCAP: An IoT based wearable for real-time accidental fall detection and health monitoring of remote maintenance workers,” in Proc. 2022 IEEE 7th International Conference for Convergence in Technology (I2CT), 2022, doi: 10.1109/I2CT54291.2022.9825406. [10]   F. Wu, T. Wu, and M. R. Yuce, “An IoT-based wearable sensor network system for safety and health monitoring of industrial workers,” in IEEE World Forum on Internet of Things, 2019.

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Publication Date

10/5/2026

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Double-Blind Peer Review

Review Rounds: 2

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