Jul 2026· International Journal of Advanced Research in Science, Communication and Technology· 0 citations· 3 references
TL;DR
The development of an AI and Internet of Things (IoT) enabled Smart Safety Harness System for enhancing working at height safety in industrial applications with significant potential for application in construction, manufacturing, petrochemical, power, mining, and infrastructure industries.
Abstract
Working at height is one of the leading causes of occupational fatalities and serious injuries across construction and industrial sectors. Despite the implementation of engineering controls, administrative procedures, work permit systems, safety training, and personal protective equipment (PPE), fall-related accidents continue to occur, primarily due to unsafe acts, human error, and non-compliance with safety harness anchoring requirements. Conventional safety monitoring methods rely heavily on manual supervision, making it difficult to ensure continuous compliance during high-risk operations. Therefore, there is a growing need for intelligent and technology-driven safety solutions that can provide real-time monitoring and early warning to prevent fall accidents.
This research presents the development of an AI and Internet of Things (IoT) enabled Smart Safety Harness System for enhancing working at height safety in industrial applications. The proposed system integrates sensor-based monitoring, AI communication, and real-time alert mechanisms to detect improper anchoring or unsafe usage of the safety harness. Whenever a deviation is identified, the system immediately generates an audio-visual warning to the worker while simultaneously transmitting the information to the supervisor for corrective action. In addition, all safety violations are automatically recorded in a centralized database for trend analysis, safety performance evaluation, and continuous improvement.
The study adopts a systematic methodology involving hazard identification, working at height survey, risk assessment, evaluation of existing engineering and administrative controls, validation of technological solutions, and implementation of an intelligent fall protection system. High-risk activities such as roof sheet installation, scaffold erection, maintenance work, pipeline installation, and structural construction are analyzed to identify critical areas where smart wearable technology can significantly improve safety performance. The proposed approach follows the hierarchy of risk control by strengthening engineering controls while minimizing dependence on manual observation and human intervention.
The outcome of this research is the development of a reliable, economical, and intelligent fall prevention system capable of reducing workplace injuries, improving PPE compliance, minimizing human error, and supporting proactive safety management. The integration of Artificial Intelligence, IoT, and smart wearable technology establishes a modern framework for industrial safety that enables real-time monitoring, predictive safety analytics, and data-driven decision-making. The proposed system has significant potential for application in construction, manufacturing, petrochemical, power, mining, and infrastructure industries, thereby contributing to the advancement of Industrial Safety Engineering and promoting a sustainable "Zero Harm" safety culture.
ABSTRACT
Firefighting is an inherently hazardous occupation, with numerous incidents each year resulting in injuries and fatalities among fire service personnel. To mitigate these risks and enhance operational efficiency, this paper presents the design and development of an IoT-Based Firefighting Robot that integrates autonomous fire detection and suppression capabilities with remote control via Bluetooth communication.
The system leverages Internet of Things (IoT) technologies for real-time monitoring and control, enabling the robot to navigate hazardous environments and extinguish fires autonomously or under manual operator control when required. Equipped with flame sensors for fire detection, a fire extinguishing mechanism, and Bluetooth-based communication, the robot can be operated from a safe distance using an Android application, allowing precise intervention in critical situations.
This hybrid approach combines the strengths of autonomous decisionmaking with human supervision, offering enhanced flexibility and safety in firefighting operations. The system is particularly suited for industrial settings and environments where the risk of accidental fires is high, enabling rapid response while minimizing human exposure to danger. The proposed solution demonstrates the effectiveness of IoT-enabled robotics in improving fire safety, offering a scalable and reliable approach to safeguarding lives, property, and critical infrastructure.
Keywords: DC motor, Flame sensors, Firefighting, Pump, Robot.
G. Sahithi, D. K. S. Rao· International Scientific Jou...· 0 citations
Mining remains one of the most hazardous industries due to the continuous exposure of workers to toxic gases, extreme environmental conditions, and health-related risks. This paper presents an IoT-enabled Smart Mining Helmet with Health and Safety Monitoring designed to improve worker protection through real-time environmental and physiological monitoring. The proposed system is built around the ESP32 microcontroller and integrates an MQ135 gas sensor for hazardous gas detection, an LM35/DS18B20 temperature sensor for temperature monitoring, a pulse sensor for heart rate measurement, and an IR eye-blink sensor for detecting worker fatigue or unconsciousness. The collected sensor data are processed by the ESP32 and transmitted wirelessly via Wi-Fi to a centralized monitoring system for continuous supervision. Whenever any monitored parameter exceeds predefined safety thresholds, the system immediately activates a buzzer and sends alert notifications, enabling rapid response to potential emergencies. Experimental evaluation demonstrates that the proposed system accurately monitors environmental and physiological conditions while providing reliable real-time alerts under both normal and hazardous scenarios. Compared with conventional mining safety systems, the proposed solution offers integrated health monitoring, continuous remote monitoring, and enhanced emergency response capabilities at a low implementation cost. The developed smart helmet provides an effective, scalable, and reliable solution for improving occupational safety in mining environments and can be extended to other hazardous industries such as construction, oil and gas, and chemical manufacturing.
kalpana V. Yojana rupa, Naga Durga Sahith Jonnalagadda, Harshita Boddepalli et al.· International Journal of Sci...· 0 citations
Occupational Safety and Health (OSH) remain major concerns in the construction industry, which continues to report high numbers of accidents, injuries, and fatalities worldwide. Despite the availability of modern safety practices and advanced technologies, the industry still struggles to maintain safe working conditions. The current review adopts the Joanna Briggs Institute (JBI) scoping review methodology and is reported in accordance with the PRISMA-ScR reporting guidelines. Three stages of screening were carried out and finally 76 articles were selected for this study. This review paper aims to understand the key causes of safety issues and explores various strategies to reduce risks on construction sites. It examines common hazards, such as falls, electrocutions, and equipment-related incidents, along with the factors that contribute to them—including poor safety culture, worker fatigue, inadequate training, and weak management support. The paper highlights the growing role of technology in improving safety, including the use of IoT devices, Building Information Modeling (BIM), robotics, and virtual/augmented reality (VR/AR). These innovations offer promising solutions for real-time monitoring, immersive training, and risk prediction. Based on the findings, several practical recommendations are proposed to enhance safety culture, update regulations, improve management practices, and invest in continuous training. While technology holds great potential, its success depends on proper implementation and organizational commitment. This study provides a critical overview about the current state of modern safety technologies in construction industry. It highlights the significance of integration of these technologies into construction industry to improve safety. Finally, it provides a foundation for future research and offers insights for policymakers, industry professionals, and researchers aiming to build safer construction environments. The findings of this review contribute to the advancement of Sustainable Development Goal (SDG) 3 (Good Health and Well-being) and SDG 8 (Decent Work and Economic Growth) by highlighting strategies and emerging technologies aimed at improving occupational health and safety in the construction industry.
Recent statistics on work-related non-fatal and fatal injuries show that falls from height (FFH) are the leading causes, having a negative impact on socio-economic levels. Among industrial sectors, the construction industry has the highest rate of fatal injuries. Although safety harnesses, personal protective equipment (PPE), and collective protection systems are mandated by national laws, these tools have been insufficient to effectively address the problem. Smart wearable technologies and advanced materials can help predict and react to FFH events. This work proposes the design of a new fallimpact-mitigation wearable airbag to protect the front and back of the user, integrated into a technical vest. The system is activated by a falling-risk-estimation algorithm that can distinguish between voluntary movements and accidental falls. The device meets level-2 protection requirements according to EN1621-4, offering protection to users falling from 1.5 to 4 m. The proposed apparatus naturally extends this to types of falls from the same level.
S. Leggieri, Christian Di Natali, Fabio Colombo et al.· International Conference on...· 0 citations
Workers in the oil and gas industry, construction, and mining are routinely exposed to life-threatening hazards that existing safety systems are too slow and too limited to address. Traditional safety approaches rely on manual reporting and passive physical protection, leaving critical gaps in real-time detection and emergency response. This paper presents the design, development, and evaluation of an Internet of Things (IoT) powered smart safety helmet, named the BEYOND HELMET, built specifically for oil and gas field workers in Nigeria.
The system integrates an ESP32 microcontroller, an MPU-6050 inertial measurement unit for fall detection, an MQ-7 gas sensor for carbon monoxide monitoring, a DHT22 temperature and humidity sensor, a SEN-11574 pulse rate sensor for heart rate monitoring, a NEO-6M GPS module for precise location tracking, a SIM800L GSM module for SMS-based emergency alerts, an ESP32-CAM camera for visual confirmation, and a 16x2 LCD display for local status output. All sensor data are processed onboard and transmitted in real time to supervisors through an IoT monitoring platform structured in JavaScript Object Notation (JSON) format.
Testing results indicate that the system achieves fall detection accuracy of approximately 95%, carbon monoxide hazard detection accuracy of approximately 90%, and abnormal heart rate detection accuracy of approximately 92%. Emergency alerts are dispatched in under 10 seconds compared to the 10 to 20 minutes typical of manual reporting systems, representing a response time reduction of 70 to 85%. The prototype was assembled at a total cost of approximately 43,400 Nigerian Naira, making it highly affordable and scalable for large industrial deployments. The results demonstrate that the BEYOND HELMET offers a comprehensive, cost-effective, and proactive safety solution for workers in hazardous environments.
O. S. Ogboro, Kehinde O. Adegboye, Chi-ife D. Ileka et al.· SPE Nigeria Annual Internati...· 0 citations
Cooking-related accidents from unattended electric stoves, overheating, and power restoration after load shedding are a growing safety concern in Zimbabwean households. Most stoves lack intelligent safety mechanisms, and existing smart technologies are often expensive, internet-dependent, or unsuitable for unstable electricity supplies.
This project developed and evaluated a low-cost stove for the Zimbabwean context. The system utilises an Arduino-based architecture integrated with LM35 temperature sensors, PIR motion sensors, relay modules, and GSM modules for SMS alerts via local networks. The system continuously monitors for overheating, prolonged usage, and human presence, automatically disconnecting power when hazards are detected. A critical safety feature prevents the stove from automatically restarting after load-shedding power restoration.
Adopting a Design Science Research (DSR) methodology, the prototype underwent component, integration, and field testing in five Bindura households. Results indicate the system achieved 91.7% hazard detection reliability with an average response time of 7.3 seconds, successfully meeting the project target of under 10 seconds. At a cost of USD $42.30, the system is significantly more affordable than commercial alternatives. User feedback confirmed high satisfaction, particularly regarding the automatic shutdown and load-shedding protection features, despite minor challenges with false alarms and motion detection sensitivity.
The study concludes that a low-cost, embedded safety system is technically feasible and appropriate for Zimbabwean households. This project highlights the necessity of designing technology solutions that prioritize local environmental and economic conditions over imported smart home systems. Future work will focus on improving sensor sensitivity, reducing false alarms, and expanding compatibility with various stove types.
Kudakwashe C Bamusi, M. Mavhemwa· International Journal of Lat...· 0 citations