Real-time site safety risk assessment and intervention method using the RFID-based multi-sensor intelligent system.

BACKGROUND: One of the main problems that may put people's safety in danger is the lack of real-time detection, evaluation, and recognition of predictable safety risks. Current real-time risk identification solutions are limited to proximity sensing, which lack providing the exposed person with risk-specific information in real-time. Combined values of concurrently presented risks are either unrecognized or underestimated. OBJECTIVE: This study goes beyond the proximity sensing state-of-the-art by envisioning, planning, designing, developing, assembling, and examining an automated intelligent real-time risk (AIR) assessment system. METHODS: A holistic safety assessment approach is followed to include identification, prioritization, detection, evaluation, and control at risk exposure time. Multi-sensor technologies based on RFID are integrated with a risk assessment intelligent system. System prototype is developed and examined to prove the concept for on-foot building construction workers. RESULTS: The evaluation of AIR assessment system's performance proved its validity, significance, simplicity, representation, accuracy, precision, and timeliness. The reliability of providing quantitative proximity values of risk can be limited due to the signal attenuation; however, it can be reliable in providing risk proximity in a subjective linguistic fashion (Near/Far). CONCLUSION: The main contributions of the AIR assessment system are that the mobile wearable device can provide a linguistic meaningful risk assessment resultant value, the value represents the combined evaluation of concurrently presented risks, and can be sound delivered to the exposed person in real-time of exposure. Therefore, AIR system can be used as an effective prognostic risk assessment tool that can empower workers with real-time recognition and measurability of risk exposure.

Short-term influence of coal mine reclamation using coal combustion residues on groundwater quality.

Two full-scale coal mine reclamation projects using coal combustion residues (CCRs) were recently carried out at highwall pit complexes near the Conesville and Cardinal coal-fired power plants owned by American Electric Power. The environment impacts of the reclamation projects were examined by regularly monitoring the leaching characteristics of the backfilling CCRs and the water quality of the uppermost aquifers underlying the sites. With over five years of field monitoring, it shows that the water quality at both demonstration sites had changed since the reclamation began. By analyzing the change of the hydrogeochemical properties, it was concluded that the water quality impact observed at the Conesville Five Points site was unlikely due to the seepage of FGD material leachates. Reclamation activities, such as logging, grading, and dewatering changed the hydrogeological conditions and resulted in the observed water quality changes. The same hydrogeological effect on water quality was also found at the Cardinal Star Ridge site during the early stage of the reclamation (approximately the first 22months). Subsequent measurements showed the water quality to be strongly influenced by the water in the reclaimed highwall pit. Despite the changes to the water quality, the impacts are insignificant and temporary. None of the constitutes showed concentration levels higher than the regulatory leaching limits set by the Ohio Department of Natural Resources' Division of Mineral Resources Management for utilizing CCRs in mined land reclamation. Compared to the local aquifers, the concentrations of eleven selected constituents remained at comparable levels throughout the study period. There are four constituents (i.e., As, Be, Sb, and Tl) that exceeded their respective MCLs after the reclamation began. These detections were found shortly (i.e., within 2years) after the reclamation began and decreased to the levels either lower than the respective detection limits or similar to the background levels.