Toward Wi-Fi-Enabled Real-Time Communication for Proactive Safety Systems in Highway Work Zones: A Case Study
Publication: Construction Research Congress 2022
ABSTRACT
Given the fatal risks that highway workers encounter, securing the safety of highway work zones is one of the most pressing issues in the highway maintenance and operation community. Recent advances in Artificial Intelligence, Augmented Reality, and the Internet of Things (IoT) suggest that departing from current reactive safety systems to predictive and sophisticated solutions is feasible. To this end, real-time communication among the utilized agents plays a crucial role in the success of such systems. Therefore, in this paper, we investigate the challenges and requirements of establishing a local IoT system in highway work zones. To this end, we devised a case study to design a network among multiple endpoints and measured the latency of real-time communication among the utilized devices based on different network architectures. Our results indicate that in the most crowded network, 4 endpoints were able to wirelessly communicate with an average latency of 10 milliseconds at farthest distance. We also identified distance, the number of endpoints, and heavy moving objects as the potential barriers impacting network performance. Overall, this paper contributes to the body of knowledge by providing preliminary insights toward utilizing IoT networks in the context of highway work zones.
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REFERENCES
AGC (Associated General Contractors of America). (2019). 2019 highway work zone safety survey. Associated General Contractors of America – AGC.
Awolusi, I., and Marks, E. D. (2019). “Active work zone safety: preventing accidents using intrusion sensing technologies.” Frontiers in built environment, 5, 21.
Awolusi, I., Nnaji, C., Marks, E., and Hallowell, M. (2019). “Enhancing construction safety monitoring through the application of internet of things and wearable sensing devices: A review.” Computing in civil engineering 2019: Data, sensing, and analytics, 530–538.
Bouanaka, C., Benlahrache, N., Benhamaid, S., and Bouhamed, E. (2020). “A review of iot systems engineering: Application to the smart traffic lights system.” 2020 International Conference on Advanced Aspects of Software Engineering (ICAASE), IEEE, 1–8.
Dhingra, S., Madda, R. B., Patan, R., Jiao, P., Barri, K., and Alavi, A. H. (2020). “Internet of things-based fog and cloud computing technology for smart traffic monitoring.” Internet of Things, 100175.
Ditty, M., Karandikar, A., and Reed, D. (2018). “Nvidia xavier soc.” Hot Chips 2018 (Aug).
Ferrari, P., Sisinni, E., Brandão, D., and Rocha, M. (2017). “Evaluation of communication latency in industrial iot applications.” 2017 IEEE International Workshop on Measurement and Networking (M&N), IEEE, 1–6.
FHWA (Federal Highway Administration). (2018). “Facts and statistics—work zone safety.” Federal Highway Administration (FHWA).
Gambatese, J. A., Lee, H. W., Nnaji, C. A., et al. (2017). “Work zone intrusion alert technologies: Assessment and practical guidance.”, Oregon. Dept. of Transportation. Research Section.
George, A., Ravindran, A., Mendieta, M., and Tabkhi, H. (2021). “Mez: An adaptive messaging system for latency-sensitive multi-camera machine vision at the iot edge.” IEEE Access, 9, 21457–21473.
Habibnezhad, M., Puckett, J., Jebelli, H., Karji, A., Fardhosseini, M. S., and Asadi, S. (2020). “Neurophysiological testing for assessing construction workers’ task performance at virtual height.” Automation in Construction, 113, 103143.
Hasanzadeh, S., and de la Garza, J. M. (2020). “Productivity-safety model: debunking the myth of the productivity-safety divide through a mixed-reality residential roofing task.” Journal of construction engineering and management, 146(11), 04020124.
Hourdos, J. (2012). Portable, non-intrusive advance warning devices for work zones with or without flag operators.
Kanan, R., Elhassan, O., and Bensalem, R. (2018). “An iot-based autonomous system for workers’ safety in construction sites with real-time alarming, monitoring, and positioning strategies.” Automation in Construction, 88, 73–86.
Lee, H., Yang, K., Kim, N., and Ahn, C. R. (2020). “Detecting excessive load-carrying tasks using a deep learning network with a gramian angular field.” Automation in Construction, 120, 103390.
Mills, N., De Silva, D., and Alahakoon, D. (2020). “Generating situational awareness of pedestrian and vehicular movement in urban areas using iot data streams.” IEEE Internet of Things Journal, 7(5), 4395–4402.
Nnaji, C., Gambatese, J., Lee, H. W., and Zhang, F. (2020). “Improving construction work zone safety using technology: A systematic review of applicable technologies.” Journal of traffic and transportation engineering (English edition), 7(1), 61–75.
Raptis, T. P., Passarella, A., and Conti, M. (2018). “Performance analysis of latency-aware data management in industrial iot networks.” Sensors, 18(8), 2611.
Rujikietgumjorn, S., and Watcharapinchai, N. (2017). “Vehicle detection with sub-class training using r-cnn for the ua-detrac benchmark.” 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), IEEE, 1–5.
Shafique, K., Khawaja, B. A., Sabir, F., Qazi, S., and Mustaqim, M. (2020). “Internet of things (iot) for next-generation smart systems: A review of current challenges, future trends and prospects for emerging 5g-iot scenarios.” Ieee Access, 8, 23022–23040.
Stoyanova, M., Nikoloudakis, Y., Panagiotakis, S., Pallis, E., and Markakis, E. K. (2020). “A survey on the internet of things (iot) forensics: challenges, approaches, and open issues.” IEEE Communications Surveys & Tutorials, 22(2), 1191–1221.
Yang, X., Yu, Y., Shirowzhan, S., Li, H., et al. (2020). “Automated ppe-tool pair check system for construction safety using smart iot.” Journal of Building Engineering, 32, 101721.
Zhou, C., and Ding, L. (2017). “Safety barrier warning system for underground construction sites using internet-of-things technologies.” Automation in Construction, 83, 372–389.
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Published online: Mar 7, 2022
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