Date of Award

2022

Degree Name

Engineering

College

College of Engineering and Computer Sciences

Type of Degree

M.S.E.

Document Type

Thesis

First Advisor

Dr. Ammar Alzarrad, Committee Chairperson

Second Advisor

Dr. Isaac Wait

Third Advisor

Dr. James Bryce

Abstract

Many safety and health risks are faced daily by workers in the field of construction. There is unpredictability and risk embedded in the job and work environment. When compared with other industries, the construction industry has one of the highest numbers of worker injuries, illnesses, fatalities, and near-misses. To eliminate these risky events and make worker performance more predictable, new safety technologies such as the Internet of Things (IoT) and Wearable Sensing Devices (WSD) have been highlighted as effective safety systems. Some of these Wearable Internet of Things (WIoT) and sensory devices are already being used in other industries to observe and collect crucial data for worker safety in the field. However, due to limited information and implementation of these devices in the construction field, Wearable Sensing Devices (WSD) and Internet of Things (IoT) are still relatively underdeveloped and lacking. The main goal of the research is to develop a conceptual decision-making framework that managers and other appropriate personnel can use to select suitable Wearable Internet of Things (WIoT) devices for proper application/ implementation in the construction industry. The research involves a literature review on the aforementioned devices and the development and demonstration of a decision-making framework using the Fuzzy Analytic Hierarchy Process (FAHP).

Subject(s)

Construction workers – Protection.

Construction workers – Accidents.

Construction workers – Wounds and injuries – Prevention.

Internet of things – Safety measures.

Wearable technology – Risk assessment.

Wearable technology – Safety measures.

Engineering – Management.

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