Acceptability Evaluation of a Developed Thermal Infrared Device for Fire Risk Management: Using the Unified Theory of Acceptance and Use of Technology (UTAUT) Model

Acceptability Evaluation of a Developed Thermal Infrared Device for Fire Risk Management: Using the Unified Theory of Acceptance and Use of Technology (UTAUT) Model

Celbert M. Himang (Cebu Technological University, Philippines), Harrold U. Beltran (University of the Immaculate Conception, Philippines), Lanndon Ocampo (Cebu Technological University, Philippines), Jose Maria S. Garcia II (Cebu Technological University, Philippines), Rosein A. Ancheta Jr. (Cebu Technological University, Philippines), Melanie M. Himang (Cebu Technological University, Philippines), Egberto F. Selerio Jr. (University of San Jose-Recoletos, Philippines), and Ella Joyce I. Luzano (University of San Jose-Recoletos, Philippines)
Copyright: © 2020 |Pages: 25
DOI: 10.4018/IJSKD.2020070101
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A novel thermal infrared device was developed to measure wire temperature in application to fire risk management. Findings show that the device is as effective as the conventional thermocouple thermometer. The technology adoption of the device was also assessed using the unified theory of acceptance and use of technology (UTAUT) model. From the assessment, it was found out that user age has a negative effect on the UTAUT constructs on performance expectancy (PE), the effort expectancy (EE), and facilitating condition (FC). Moreover, the user gender was found to have an adverse effect on PE. Furthermore, the construct which has the highest positive effect on the user behavioral intention (BI) is social influence (SI) with a value of 0.552. All the factors have values greater than or equal to 0.7 thresholds for Cronbach's alpha, 0.5 for composite reliability, and 0.5 for average variances.
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1. Introduction

Fires are considered a phenomenon proceeding from a pre-combustion, through the combustion, and finally to the post-combustion stage (Ni et al., 2008). Various means of preventing fires are suggested in the current literature. Some prevention methods involve the detection of the fire after it has ignited (e.g., Gottuk et al., 2002; Ni et al., 2008; Bakhoum, 2012; Yuan et al., 2015). Some methodologies involve flame detectors that respond to radiant energy of less than 4000 or above 7000 A (Gaur et al., 2019). However, the important goal of fire prevention is to identify a developing emergency as early as possible, which means that the ideal method to proactively troubleshoot fires is to prevent it from the pre-combustion process. On this note, thermal sensors were developed to detect a fire before it has ignited. Various thermal sensing innovations have been developed to prevent fire incidents proactively (e.g., Wang et al., 2005; Juang et al., 2010; Jevtić & Blagojević, 2011; Hoff, 2017); however, despite its importance, very little attention has been given to thermal sensing for electrical initiated fires (EIF) prevention in the current literature.

EIF were involved in 24% of structure fires (Campbell, 2018) and is one of the fatal fire disaster categories with over 12.3% fatality rate (Xiong et al., 2015). Thus, it is crucial to prevent EIF considering the hazards that they pose to residences and industries. EIF can be initiated by overheated old as well as new wiring (Shea, 2011; Courty & Garo, 2017). Shea (2011) documented various failure modes that cause EIF. Among the identified failure modes are series and parallel arcing faults, bundled extension cords under rugs, abused NM-B at a load center entrance, broken wires, and loose connections, which can quickly occur in households; hence, the warranted attention on the matter. However, although the causes of EIF are directly associated with wire temperature more than other factors (Fisher et al., 2015), the current literature reveals that the acquisition of accurate wire thermal data is often tricky.

Several works have been published in the last decade about EIF. Most of these works are experimentally engaging with pyrolysis and thermal degradation of cables (e.g., Passalacqua et al., 2013; Mo et al., 2013; Fisher et al., 2015; Courty & Garo, 2017). In this mechanism, wire temperature is often measured inside the wire bundle with a thermocouple that is connected to a data acquisition unit (e.g., Shea, 2011; Passalacqua et al., 2013; Mo et al., 2013; Fisher et al., 2015; Courty & Garo, 2017). However, this measurement method suffers efficiency, which may not be suitable for residential and industrial applications, particularly in real-time wire thermal surveillance and detection.

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