ABSTRACT
Electronic Construction (e-Construction) is being increasingly used to minimize the amount of paperwork and simplify the daily operations inherent in the construction of highway infrastructures. Electronic ticketing (e-Ticketing) is a part of e-Construction that aids in the transfer of material tickets in a digital manner, accounting for more than half of construction costs;however, the technology has been pilot tested by several states since the beginning of 2013 and has been disbanded for various reasons. The purpose of this research is to pinpoint the challenges in the deployment of an e-Ticketing platform, as well as to determine the adoption rate of state departments of transportations (DOT) and to assess the benefits. The research method includes a combination of literature review and semistructured interviews to achieve the study's objectives. An inductive thematic analysis approach was used to analyze the interview transcripts. The study's findings are related to the reasons for delays and misconceptions about the implementation of the e-Ticketing platform. Internet connectivity at construction sites and high investment costs were found to be the major challenges that have delayed the implementation of the e-Ticketing platform. The study's results will aid decision makers in DOTs and engineers build a standard e-Ticketing platform, implement rules and guidelines, reduce investment costs, execute pilot testing, improve inspector safety, and complete projects in a timely and efficient manner. © 2023 American Society of Civil Engineers.
ABSTRACT
Ho Chi Minh City, particularly Vietnamese cities in general, is so busy and crowded since tremendous numbers of motorbikes move on roads. Ho Chi Minh City leaders have encountered several challenges in fully understanding and effectively dealing with problems of urban traffic for the past few decades. Software-based solutions are proper and dramatically necessary, currently. This paper presents the deployment of an AI-based application at the Ho Chi Minh City Department of Transportation. The paper mainly concentrates on traffic counting problems during the outbreak of the Covid-19 pandemic from June 2021. The performance of the AI-based application was compared with medical declaration data and achieved an accuracy of 93.80%. © 2022 IEEE.
ABSTRACT
The ongoing novel coronavirus (COVID-19) pandemic has highlighted the need for individuals to have easy access to healthcare facilities for treatment as well as vaccinations. The surge in COVID-19 hospitalizations during 2020 also underscored the fact that accessibility to nearby hospitals for testing, treatment and vaccination sites is crucial for patients with fever or respiratory symptoms. Although necessary, quantifying healthcare access is challenging as it depends on a complex interaction between underlying socioeconomic and physical factors. In this case study, we deployed a Multi Criteria Decision Analysis (MCDA) approach to uncover the barriers and their effect on healthcare access. Using a least cost path (LCP) analysis we quantified the costs associated with healthcare access from each census block group in the Los Angeles metropolitan area (LA Metro) to the nearest hospital. Social vulnerability reported by the Centers for Disease Control and Prevention (CDC), the daily number of COVID-19 cases from the Los Angeles open data portal and built environment characteristics (slope of the street, car ownership, population density distribution, walkability, traffic collision density, and speed limit) were used to quantify overall accessibility index for the entire study area. Our results showed that the census block groups with a social vulnerability index above 0.75 (high vulnerability) had low accessibility owing to the higher cost of access to nearby hospitals. These areas were also coincident with the hotspots for COVID-19 cases and deaths which highlighted the inequitable exposure of socially disadvantaged populations to COVID-19 infections and how the pandemic impacts were exacerbated by the synergistic effect of socioeconomic status and built environment characteristics of the locations where the disadvantaged populations resided. The framework proposed herein could be adapted to geo-target testing/vaccination sites and improve accessibility to healthcare facilities in general and more specifically among the socially vulnerable populations residing in urban areas to reduce their overall health risks during future pandemic outbreaks.