Abstract
The Singapore WSH (Workplace Safety and Health) Council states that 6 out of 17 fatal injuries in the first half of the year 2019 are from the Construction industry and that the top 3 causes of the fatal and major injuries are mainly falling from heights, machinery-related injuries and slips, trips or falls. The government does come up with various frameworks to reduce such accidents and incidents, incorporating the 4 main factors: policy, personnel, process and incentive factors. However, it has been found that still almost 25% of the safety hazards go unnoticed by the workers. One must understand that hazard identification at site is a visual search and analysis process which can be hindered by various human factors such as the workers’ physiological and psychological state of mind, attention span, bias and risk tolerance levels. This paper explores the possibilities of coupling AI with IoT to overcome those challenges.
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References
William, J.A.W., Janocha, J.: Comparing fatal work injuries in the United States and the European Union: Monthly Labor Review: U.S. Bureau of Labor Statistics (2014). https://www.bls.gov/opub/mlr/2014/article/comparing-fatal-work-injuries-us-eu.htm. Accessed 27 Jan 2021
Ministry of Manpower. Workplace safety and health reports and statistics. Ministry of Manpower Singapore. https://www.mom.gov.sg/workplace-safety-and-health/wsh-reports-and-statistics. Accessed 27 Jan 2021
Teo, E.A.L., Ling, F.Y.Y., Chong, A.F.W.: Framework for project managers to manage construction safety. Int. J. Project Manag. 23(4), 329–341 (2005)
Hinze, J.: Safety incentives: do they reduce injuries? Pract. Period Struct. Des. Constr. 7(2), 81–84 (2002)
Lai, D.N.C., Liu, M., Ling, F.Y.Y.: A comparative study on adopting human resource practices for safety management on construction projects in the United States and Singapore. Int. J. Project Manag. 29(8), 1018–1032 (2011)
Tixier, A.J.-P., Hallowell, M.R., Rajagopalan, B., Bowman, D.: Automated content analysis for construction safety: a natural language processing system to extract precursors and outcomes from unstructured injury reports. Autom. Constr. 62, 45–56 (2016)
Tixier, A.J.-P., Hallowell, M.R., Rajagopalan, B., Bowman, D.: Application of machine learning to construction injury prediction. Autom. Constr. 69, 102–114 (2016)
Baker, H., Hallowell, M.R., Tixier, A.J.-P.: AI-based prediction of independent construction safety outcomes from universal attributes. Autom. Constr. 118 (2020). http://ezproxy.newcastle.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S0926580519310386&site=eds-live. Accessed 1 Oct 2020
Jeelani, I., Asadi, K., Ramshankar, H., Han, K., Albert, A.: Real-time vision-based worker localization & hazard detection for construction. Autom. Constr. 121 (2021). http://ezproxy.newcastle.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S0926580520310281&site=eds-live. Accessed 1 Jan 2021
Chakkravarthy, R.: Artificial intelligence for construction safety. Prof. Saf. 64(1), 45 (2019)
Tamura, T.: Wearable units. In: Tamura, T., Chen, W. (eds.) Seamless Healthcare Monitoring, pp. 212–217. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-69362-0_8
ADXL330 Datasheet. Analog Devices, Inc. (2007)
3D-Data with Stereo Vision White Paper. IDS Imaging Development Systems GmbH (2020)
NXP QN902X Datasheet. NXP Semiconductors N.V. (2018)
Hazelcast—The Leading In-Memory Computing Platform. Hazelcast. https://hazelcast.com/. Accessed 31 Jan 2021
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Palaniappan, K., Kok, C.L., Kato, K. (2021). Artificial Intelligence (AI) Coupled with the Internet of Things (IoT) for the Enhancement of Occupational Health and Safety in the Construction Industry. In: Ahram, T.Z., Karwowski, W., Kalra, J. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2021. Lecture Notes in Networks and Systems, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-030-80624-8_4
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