Real-time site safety risk assessment and intervention for on-foot building construction workers using RFID-based multi-sensor intelligent system

Throughout the last several years, the number of detrimental accidents is still considered high and not going below a certain verge. One of the main problems that may put people's safety in danger is the lack of real-time detection, assessment, and recognition of predictable safety risks. Current real-time risk identification solutions are limited to proximity sensing, which lacks in providing meaningful values of the overall safety conditions in real-time.The overall objective of this research is to envision, design, develop, assemble, and examine an automated intelligent real-time risk assessment (AIR) system. A holistic safety assessment approach is followed to include identification, prioritization, detection, evaluation, and control at risk exposure time. Multi-sensor technologies based on Radio-Frequency Identification (RFID) are integrated with a risk assessment intelligent system. The intelligent system is based on fuzzy fault tree analysis (FFTA), a deductive approach that comprehensively systemizes possible concurrent basic and conditional risk events, not risk symptoms, from major subgroups of triggering, enabling, and environment-related risks. System prototype is developed and examined for functionality and deployment requirements to prove the concept for on-foot building construction worker at site.The experimental examination results showed that the AIR system was able to detect, assess, and sound deliver combined evaluation of concurrent diverse risks presented in a worker's range at real-time of exposure. The AIR system performance has met the criteria of validity, significance, simplicity, representation, accuracy, and precision and timeliness. The reliability of the AIR system to deliver quantitative values of risk proximity was limited due to the RF signal attenuation caused by different materials at site. Nevertheless, AIR system was reliable in real-time assessment and declaration of risk types, values, and proximity in a subjective linguistic fashion (Near/Far). The main conclusion is that AIR wearable system can be used as an effective prognostic risk assessment tool that can empower workers with realistic recognition and measurability of risk exposure at exposure time. This can enhance adequate responses and proactive decisions of risk control, accident prevention, and health protection.The wearable AIR assessment system is an addition to the state-of-the-art of proximity sensing and risk detection systems which left concurrently presented risks either unrecognized or misestimated. The main contribution of the AIR system is that the risk assessment resultant value (1) represents the combined evaluation of concurrently presented risks, (2) is a linguistic meaningful assessment value delivered to the exposed person in real-time of exposure. The main contribution of the AIR intelligent system is that it overcomes assessment misestimation by (i) proposing an enhanced rotational fuzzy set model to host the subjective risk values into quantifiable values, which helps in overcoming fuzzy sets rounding and misrepresentation; (ii) building an inclusive risk breakdown structure that helps in combating assessment underestimation related to overlooking influential concurrent risks; (iii) suggesting logical operations to combine concurrent residual risk values while distinguish between static risk (non-moving) and dynamic (moving) risks, and taking into consideration the effectiveness of safety precautions and measures that may reduce or eliminate risks, which can overcome assessment overestimation (false alarms). The collective use of different sensing technologies, that can be integrated with the AIR intelligent system, is a contribution that can be expanded in future research.