Human Factors and Facial Recognition Technology in Emergency Response: An Integrative Review

Abstract

Facial Recognition Technology (FRT) has the potential to enhance emergency response by improving efficiency, reducing response times, and potentially saving lives. It is important to explore both the benefits and challenges of implementing FRT in emergency response protocols and identify the gaps in research on its application in emergency response. This integrative review collected articles from 2010 onwards through keyword searches in titles and abstracts across multiple databases, with inclusion and exclusion criteria applied, focusing on English-language peer-reviewed articles mentioning specific keywords related to emergency services and facial recognition. Data collection involved converting PDFs to plain text and coding--both human and non-human--for thematic analysis refined over rounds of close readings for accuracy. The results reveal positive and mixed findings regarding FRT in emergency response across various studies. Several methodologies were employed, including machine learning and deep learning techniques, achieving high accuracy rates in identifying individuals, particularly in scenarios like disaster rescue and masked-face recognition during the COVID-19 pandemic. Studies also evaluated FRT's effectiveness in disaster victim identification, safety systems integration, and medical applications, showcasing its potential across different contexts. However, limitations such as challenges in real-world deployment, concerns regarding privacy and bias, and the need for further validation and standardization were highlighted across the studies, indicating areas for future research and development to enhance the technology's efficacy and ethical use. The review emphasizes the importance of addressing technical, ethical, and governance challenges to deploy FRT effectively and responsibly in emergency response, serving as a valuable resource for stakeholders and researchers seeking to understand and advance the field.

Keywords: human factors, emergency response, facial recognition, integrative review

DOI: 10.54941/ahfe1005317