HCI International 2021 - Late Breaking Papers: HCI Applications in Health, Transport, and Industry

This study proposes a conceptual model that establishes a relationship between engagement with gamified applications, and its impact on a user’s quality of life (QoL). Since gamification is rapidly gaining popularity therefore the use of such applications has become a norm. Subjective quality of life is a mental state or an individual’s awareness of factors that impact major aspects of life, such as health, learning, creativity, socialization etc. Literature is sparse when it comes to investigating the impact of engagement with gamified applications, and its effect on quality of life. To address this research gap, we explore how consumer engagement with gamification cultivates an individual’s perception with regards to their quality of life. We posit that consumer engagement is a higher-order formative construct, comprising cognitive, affective and behavioural dimensions, is influenced by gamified applications, leading towards an increase in subjective QoL. QoL is also a higher-order formative construct involving first-order reflective constructs such as leisure time, view of life, creativity, learning, friendship and individualistic perspective of satisfaction. This study provides an important insight to avenues of academia and practitioners by developing a conceptual model where consumer engagement in serious games acts as a predictor of users’ QoL. We conclude by discussing important implications that arise from this exploration, along with its limitations and avenues for further research.

The application of human factors and ergonomics in transportation is an example of human-automation interaction. Since the year 2020, the covid-19 pandemic has become an emerging factor that interacts with transportation from epidemiological and ergonomic perspectives. This study aims at capturing the emerging trends of covid-19 related human factors in transportation through conclusions from a systematic literature review of relevant publications. Analyses of content and bibliometrics were accomplished by using tools such as VOS Viewer, Citespace, Harzing, and MaxQDA to establish the findings of emerging trends in this field. Key findings from these analyses are: (1) Since the start of the covid 19, countries over the world have administered a variety of travel-related controls in an attempt to contain or slow down the spread of the virus both domestically and internationally. (2) The enforced travel restrictions not only impacted the spread of the pandemic but also transformed people’s activity and travel patterns into a new form. (3) The altered activity and travel patterns further brought changes in transportation policy design, air quality control, and industry disruptions. (4) The pandemic has motivated people to adopt new HCI technologies, and some previously HCI technologies are being challenged because of the pandemic mitigation policies.

The constant growth in the number of patients needing physical therapy has affected service quality and treatment effectiveness. The aim of this study was to address patient demands and service provider limitations through the perspective of lean and explore the possibility of improving the quality of physical therapy service. This study was divided into two stages. First, orthopedics referral patients in the physical therapy department were selected to conduct a customer satisfaction survey (n = 112), and service quality gaps were identified with quantitative and qualitative questions in the survey. The second stage was to develop a semi-structured interview outline based on the aforementioned results, and then to interview seven service providers in the physical therapy department about the limitations and challenges of improving the quality of service. The results showed that, quantitatively, patients’ overall satisfaction was high, but, qualitatively, there were five critical service-quality demands to be improved. Five strategies were proposed for improving service quality based on the service provider’s suggestions and the lean perspectives: 1) Set wayfinding lines from the department of orthopedics to the physical therapy center; 2) Reduce unnecessary motion in the environment and implement 5S; 3) Install a standing chair for patients with fractured foot; 4) Visualize the patient treatment information of the appointment system; 5) Visualize the appointment and attendance status for further improvements in reducing manpower idleness. This study proved that the lean perspective can improve the quality of physical therapy from the patients’ point of view, and at the same time take into account service provider limitations.

With the national strategy of “Healthy China 2030”, China attempts to move from “disease-centered” care to “big health”, aiming to promote people’s health in an all-round way. National layout and local responses are key elements of realising the “big health” concept. This paper presents an exploration of the spatial-temporal distribution and cross-impact of policies, news reports and patents associated with “big health” at both national and local levels. A bibliometric analysis was carried out with data divided into three themes: disease prevention, disease cure, and health preservation. These data were retrieved from China National Knowledge Infrastructure (CNKI) and People’s Database. The results show that local governments respond to national policies on “big health” rapidly and positively, and the local news reports on “big health” promptly following the central news. The change speed and range of patent output are different in the three themes of “big health”. In the early and all-round development periods of “big health”, national policies affect future trends and current changes of patents respectively, while local policies all affect patent output.

The topic areas around sustainable urban planning and environmental health have grown in emphasis and research over the past few decades as part of the growing larger topic area of transportation and manufacturing in human-automation interactions. This increase has correlated with the increased attention to overall environmental health as a greater point of local and global work. With the growth and emergence of these subjects, it is pertinent to explore a possible link and connection between the two topics and their respective importance. In this study, a literature review and analysis were conducted using data from Google Scholar and Web of Science and analyzed using Vosviewer, MAXQDA, and Harzing Publish or Perish. Dual searches with the key terms “sustainable urban planning” and “environmental health” were conducted in Google scholar and web of science databases and analyzed for emergence and relevance using site trending analysis tools. Following these two topic area searches, Vosviewer, Harzing Publish or Perish, MAXQDA and Mendeley facilitated a co-citation analysis and content analysis to direct efforts to perform a larger literature review from scholarly articles over a broad range of publishing realms, home countries and authors. The results of the literature review presented results showing a possible connection between trends in both keyword topic areas and the need to analyze these emerging areas further due to their relatively new age. It is believed that future work can best push the fields of sustainable urban planning and benefit environmental health the most through definition of sustainable indicators and metrics, incorporating new technologies, and gathering and leveraging best practices. Human-computer interaction will play a pivotal role in promoting the emerging field of sustainable urban planning to a larger world audience by facilitating the creation and spread of the above future work areas.

Computerized Tomography Scanners (CT-SCAN) provide detailed cross-sectional images of the human body which are employed for the easier detection and further analysis of abnormalities concerning the functionality and structure of the skeleton, tissues, and organs. However, the appropriate CT-SCAN selection is an arduous task considering the complexity and high cost of these medical devices. This decision is even more sharpener in hospitals from Low-and-Middle-Income-Countries (LMIC) where the available budget is usually restricted and correct resource allocation should be therefore ensured while granting the greatest impact on the timeliness and efficacy of healthcare services. In this framework, multiple criteria from diverse fields need to be taken into account to satisfy the intricate requirements of users. In this regard, it is necessary to fully elicit the expectations of stakeholders as well as identify their importance in an overall decision-making context. To address these gaps, this study proposes a novel integration between the Fuzzy Analytic Hierarchy Process (FAHP) and VIKOR methods for the CT-SCAN selection problem. Initially, a Multi-Criteria Decision-Making (MCDM) model will be designed for selecting the most suitable CT-SCAN option for a particular LMIC hospital. Then IF-AHP will be applied to calculate the relative priorities of criteria and sub-criteria under uncertainty. Ultimately, VIKOR will be implemented for obtaining an overall decision-making context. To address these gaps, this study proposes a novel integration between the Fuzzy Analytic Hierarchy Process (FAHP) and VIKOR methods for the CT-SCAN selection problem. Initially, a Multi-Criteria Decision-Making (MCDM) model will be designed for selecting the most suitable CT-SCAN option for a particular LMIC hospital. Then IF-AHP will be applied to calculate the relative priorities of criteria and sub-criteria under uncertainty. Ultimately, VIKOR will be implemented for obtaining an overall appropriateness index per CT-SCAN candidate and thereby identifying the most pertinent one (s) for a specific LMIC medical institution.

Emergency Care Networks (ECNs) are integrated healthcare systems comprised of emergency departments (EDs). ECNs are called to be the primary response of healthcare authorities to deal with the expected uptick in the future demands for emergency care during the current Covid-19 pandemic. Lean Six Sigma (LSS) has been proposed to address this challenge since it allows managers to detect factors contributing to the extended waiting times (WT) throughout the patient journey. The suggested framework follows the DMAIC cycle that was initiated with the project charter definition; in the meantime, a SIPOC diagram was drawn to analyze the emergency care process and pinpoint critical process variables. Following this, a nested Gage R&R study was undertaken to study the measurement system performance; subsequently, a normal-based capability analysis was carried out to determine how well the ECN process satisfies the specifications. The next step was to identify the potential causes separating the ECN nodes from the desired target. Afterwards, improvement strategies were devised to lessen the average WT. After suitable data collection, a before-and-after analysis was performed to verify the effectiveness of the implemented strategies. Ultimately, a control plan containing an I-MR control chart was designed to maintain the improvements achieved with the LSS implementation. The results revealed that the average WT of the showcased node passed from 190.02 min to 103.1 min whereas the long-term sigma level increased from −0.06 to 0.11. The proposed framework was validated through a case study including the involvement of a medium-sized hospital from the public sector.

Eating healthier at work can substantially promote health and well-being among knowledge workers. However, little has been investigated on designing digital tools and interventions specialized in improving workday eating routines. This paper presents a user-centered contextual inquiry based on mixed-methods with an online questionnaire and a semi-structured interview. This study aimed to understand knowledge workers’ eating experiences and identify design opportunities and application strategies of digital tools to improve current practices. The questionnaire feedback from 54 Dutch knowledge workers revealed that their concerns over productivity, health and nutrition, energy support, and well-being could be decisive in shaping their eating routines at work. Furthermore, the results of 12 interview sessions suggested a set of expected digital features to encourage healthy eating at work, including health knowledge access, goal setting and self-tracking, technology-assisted health programs, and social support. Additionally, our findings also indicated that these digital features should be integrated into the office setting to offer personalized feedback and contextualized health interventions. Based on these findings, we derive design opportunities for workplace digital tools to promote healthy eating and discuss their potential contributions and future work to improved office vitality.

Systematic reviews are an essential tool to help healthcare providers and medical practitioners stay up to date on the latest evidence and practices within their field. In recent years, developments have arisen in automating these systematic reviews. While automated systematic reviews are not currently in widespread use in the medical field, they present a way to increase the output of systematic reviews. This study is a literature review of how the automating of systematic reviews is currently being integrated into the healthcare system. This literature review will be relying on tools such as Web of Science, Harzing’s Publish or Perish, VOSviewer, CiteSpace, and MAXQDA to collect and analyze article data sets based on keywords “automating systematic reviews” and “healthcare systematic reviews”. Co-citation and content analyses were performed on data sets to determine which articles were most relevant. These analyses showed that automating systematic reviews is developing more within fields outside of the medical field. However, researchers are beginning to take an interest in the applications of an automated systematic review to use in the medical field. The healthcare sector has been more hesitant to adopt automation and often continues to rely on traditional methods. Automation technology is quickly advancing but currently lacks the ability to apply critical thinking of how literature is relevant to current practice, more easily understood by clinician experience, attitudes, and values.

This article explores Canadians’ response to their federal government’s release of the COVID-19 Tracing app for smartphones in 2020 during the pandemic. Researchers and industry have proposed cellphone-based contact tracing to help contain the spread of SARS-COV-2 virus in people during the COVID-19 pandemic. However, the efficacy of contact tracing requires a certain threshold of participants and for people to enable specific access to communication ports on their mobile devices. Privacy and confidentiality concerns over users’ data on their personal devices have existed for years. Rightfully, industry watchdogs have raised concerns about the long-term consequences of contact tracing. As well questioning the potential confidentiality risks, privacy experts have also raised questions about whether contact tracing can curb the spread of the SARS-COV-2 virus. The uncertainty of this technology and pre-existing privacy concern could affect the adoption by the public. It is unknown how people perceive their security regarding contact tracing during the COVID-19 pandemic. This article presents early theoretical work and survey data taken from an ongoing study on participants’ perceptions of security and privacy perceptions of the COVID Alert contact-tracing app released in several Canadian provinces and territories during the 2020–2021 pandemic.

In the current Covid-19 situation, people all over the world must begin to adhere to social distancing guidelines. However, ensuring that people follow these social distancing guidelines has proven to be a difficult challenge for the government. To combat this issue, authorities have implemented IoT solutions such as remote health monitoring and contact tracing techniques to effectively manage the spread of coronavirus. To address this issue in depth, the current paper provides a comprehensive review of how IoT applications have aided the healthcare, education, home, entertainment, transportation, hospitality, and retail sectors of an economy. Additionally, the risk and challenges posed by the widespread adoption of IoT solutions are also addressed. Finally, the paper suggests ways to mitigate existing challenges associated with the implementation of IoT solutions.

Due to the schoolwork and long-time electronic devices use, teenagers have longer time in sedentary behavior and their good postures are continuously attracting attentions. Wearable technology based on IMUs or computer vision technology based on cameras have been widely explored. Smart textile sensing technology which has great potential in body postures monitoring is one of the fields that has developed rapidly in recent years. This article focuses on teenagers’ sitting posture, following the approach of research through design, we identified the problems and challenges, tested multiple textile samples, performed the locations analysis, and finally proposed a smart shirt integrated with six stretchable textile strain sensors. The resistance of each textile sensor will change linearly through the length change. Together with the classification model in MatLab, the smart shirt can distinguish inappropriate postures with an accuracy rate of 99.1%. We also proposed a feedback design and performed a wizard-of-oz field study to see how the smart shirt may help the teenagers to maintain good postures and how do the participants value the usability. The results demonstrated the system can help the participants facilitate maintaining good postures heir posture in sedentary work.

The purpose of this study is to effectively obtain the emotional needs of children and their families during the infusion process, explore the design strategies of children's mobile infusion equipment from the emotional perspective, and improve the emotional experience of children and their families during the children's infusion process. Firstly, this study conducts research on the children and their families through user interviews and questionnaires, and maps out the flow chart of infusion for children by combining the results of the research and field observations. Through the analysis of the pain points and opportunity points in the process, the needs of the children and their families are extracted respectively, and then they are preliminarily analyzed, integrated and classified according to the three levels of emotional thinking. Secondly, in order to analyze and filter the requirements more deeply, this study introduces the Kano model, classifies the classified emotional design requirements into Kano attributes, and then uses the Better-Worse coefficient formula to calculate the user satisfaction index of each design requirement. And on this basis, we conduct a four-quadrant analysis of the requirements to obtain the importance ranking of the emotional requirements of the children and their families. Finally, based on the results of the above needs analysis, this study explores the design principles and strategies of children's mobile infusion equipment at the visceral, behavioral and reflective levels, and discusses the innovative ideas of children's infusion equipment in emotional expression. This study bridges the gap of emotional care for children and their families in the field of pediatric infusion, provides a reference for the design of children's mobile infusion equipment, and also provides a reference for the design optimization of future pediatric medical products.

Narratives can have a powerful impact on our health-related beliefs, attitudes, and behaviors. The human papillomavirus (HPV) vaccine can protect against human papillomavirus that leads to different types of cancers. However, HPV vaccination rates are low. This study explored the effectiveness of a narrative-based interactive game about the HPV vaccines as a method to communicate knowledge and perhaps create behavioral outcomes. We developed a serious storytelling game called Vaccination Vacation inspired by personal narratives of individuals who were impacted by the HPV. We tested the game using a randomized control study of 99 adult participants and compared the HPV knowledge and vaccine beliefs of the Gamer Group (who played the game, n = 44) and the Reader group (who read a vaccine information sheet, n = 55). We also evaluated the usability of the game. In addition to high usability, the interactive game slightly impacted the beliefs about the HPV vaccine over standard delivery of vaccine information, especially among those who never received the HPV vaccine. We also observed some gender-based differences in perception towards usability and the likelihood of frequently playing the game. A narrative-based game could bring positive changes to players’ HPV-related health beliefs. The combination of more comprehensive HPV vaccine information with the narratives may produce a larger impact. Narrative-based games can be effectively used in other vaccine education interventions and warrant future research.

Transportation accident is one of the most common forms of accidents. Transportation accidents can be caused by a distracted driver, speeding, pedestrians’ influence, and alcohol influence. Accidents can lead to injuries, and transportation injuries accounted for around 38% of work-related injuries. Therefore, finding a way to prevent injury caused by transportation accidents can help in reducing fatalities and increase safety. This paper demonstrates a bibliometric analysis of scientific papers on injury prevention and transportation safety. Keywords used to help analyze the relationship between articles such as “Injury,” “Transportation,” and “Safety.” The analyses were conducted using VOSViewer, MAXQDA, Harzing's Publish or Perish 7, BibExcel, CiteSpace, Vicinitas, and Mendeley. By approaching these keywords in this article, promising transportation safety techniques and illustrating the connectivity between articles can improve the gap between transportation safety and the status quo. The articles themselves were collected from multiple databases such as Web of Science, SpringerLink, Scopus, and Google Scholar. Key findings from this paper are that to reduce accidents that caused injuries, protecting both drivers and pedestrians, such as creating pedestrian refuge islands and installing single-lane roundabouts and proper education about transportation safety, is necessary.

Causal models allow us to reconstruct traffic accidents, predict the likelihood of future accidents and implement counter measures to prevent them. For drivers with impairments like visual field loss, naturalistic data on crash causes is however scarce due to their current prohibition to drive. This paper presents an approach to deriving a causal model for the prediction of crash risks for current non-drivers. The applied use case focuses on a collision with an overlooked crossing vehicle in an intersection. Based on the combination of crash analyses for normal sighted drivers and models of information processing and human errors, a general structural causal model for crash risks in this use case was developed. The application of this model to drivers with visual field loss on the side of the approaching vehicle revealed four causal factors with an increased risk of occurring: faulty anticipation of location and timing of hazards; inadequate guidance of gaze movements; adverse scanning patterns; and cognitive overload. These elevated crash risks can guide the development of assistive technologies for drivers with visual impairments in the future.

Multiple infotainment sources can significantly overload the driver’s cognitive load and increase the collision probabilities. Current solutions provided have attempted to alleviate this issue with the centralization of infotainment devices to single touchscreen devices in the dashboard area. Yet this solution still requires the driver to take the eyes from the road and concentrate on operating the secondary tasks unrelated to the driving process. The paper presents a prototype Augmented Reality Head-Up Display (AR HUD) system that superimposes a selected number of infotainment data on the vehicle’s windshield only when this is safe for the driver. The selection of infotainment data and projection timing is calculated by a prototype Artificial Intelligence (AI) Co-Driver that aims to reduce the driver’s cognitive load. The proposed system was evaluated by 50 users against a typical touchscreen dashboard system. This work presents and discusses the subjective feedback related to the cognitive load that the users perceived during the trials. The paper concludes with a future plan for improving both the AI and AR HUD elements to perform in an urban environment.

With the development of e-commerce models in the domestic market, the demand for package delivery service has increased. It’s imminent to design an package delivery system to solve the problems of large demand, numerous classifications, and low user satisfaction in package delivery service. Due to the low user cost, remote controllability and other features, autopilot technology is suitable for package delivery system and has become a hot spot for theoretical research and commercial applications. This paper presents a new model of autonomous vehicle delivery service as a solution to the optimization program, which will be suitable for small area of the cities. The user relationship in the system has been resigned, the service process has been updated, and the service blueprint has been analyzed, then the service model based on time requirements of the users has been proposed. The ant colony algorithm was used for route planning of the autonomous vehicle as to the technical support, and a simulation was performed. The prototype interfaces of main functional modules in the delivery model were produced. A survey has been done to analyze the usability of the delivery model based on a questionnaire. Furthermore, the paper presents the benefits and the limitations of this kind of system.

Accidents caused by vehicles of transportation domain are the leading cause of death worldwide. Nearly 75% of road deaths happen in developing countries. The road traffic accident rate caused by four-wheeled vehicles is the highest among the reported statistics on road traffic accidents. Standing motorized scooters’ popularity has been continuously increasing in major cities of the USA and surge of traumatic injuries is observed in many hospitals. This report will analyze bibliometric data using tools like Harzing's Publish or Perish, VOSviewer, MAXQDA, Mendeley, BibExcel, and CiteSpace to provide a systematic literature review of publications on the above-mentioned subject. Analysis is performed on articles considered from a variety of outlets, including Google Scholar, Web of Science, SpringerLink, ResearchGate, and a few chapters from Salvendy's Handbook of Human Factors and Ergonomics, Fourth Edition. A co-citation analysis was performed to identify the most significant publications in the literature. This article also discusses how potential studies like usage of autonomous vehicles, usage of virtual reality, reducing human intervention, and increasing human-computer interaction can avoid accidents in the transportation industry.

The objective of the study was to look at the trend and advancement of Artificial Intelligence, Transportation, and Safety research through bibliometric analysis. The review retrieved data in Web of Science using specific terms related to Artificial Intelligence, Transportation, and Safety. VOSViewer, CiteSpace, and MAXQDA were utilized to conduct the citation analysis and content analysis of the Web of Science data set and 8 selected documents including 6 research articles and 2 chapters from the textbook Occupational Safety and Health for Technologists, Engineers, and Managers. Articles from GoogleScholar using Harzing’s Publish or Perish software and Web of Science database were used. The citation analysis creating a co-occurrence map discovered several keywords within clusters that were suggested to be subtopics of the general topic. Performing content analysis using the 8 selected documents has shown the most occurring keywords to be similar to those discovered in the citation analysis. The articles utilized bibliometric analysis tools to have further insight on the contributing journals and keywords drawn from multiple sources and methods of Artificial Intelligence and Transportation research. Articles from the Citespace citation burst and VOSViewer co-citation analysis were used to further support the necessity of automation and safety in artificial intelligence and transportation.

The automotive HMI system has become a flourishing topic in the field of human-machine interaction and user experience. In driving scene, it’s important to reduce the burden of drivers when doing interactive tasks due to the driving distraction, which belongs to the research category of cognitive psychology (CP). This study deduced four HMI design and evaluation dimensions from CP: 1. perceivability of elements, 2. comprehensibility of elements, 3. memorability of elements, 4. rationality and fluency of system feedback. In these dimensions, twelve HMI key guidelines for touch screen were defined based on CP theory and international guidelines and standards, which are about the size and contrast of icons and texts, the pattern and color of icons, the quantity and arrangement of information in the interface, and appropriate feedbacks. The results are strong references for automotive HMI design and evaluation.

Recent studies show that emotional changes can influence driving behavior. For example, positive valence could enable better takeover performance in regaining vehicle control. On the other hand, a state of anger has been shown to degrade driver situational awareness and performance compared to a neutral state. These emotional states may result from different factors like a vehicle’s internal or external environment. The roadside environment is one of the external factors which might influence driver behavior and performance. Hence, it is necessary to understand how emotional conditions affect driving actions to design safer road environments. However, research involving the use of emotions can be challenging due to methodological issues associated with measuring emotions. Different methods can be used to measure emotion both subjectively and objectively. These could include the use of reliable sources for assessing evoked emotions, since subjective emotional experiences are the essence of a feeling. An objective manifestation of emotion can be captured as a representation of our inner experience. Also, the objective manifestation of emotion is the representation of our inner experience. In this study, we conducted an eye-integrated human-in- the- loop (HTIL) simulation experiment to analyze the driver’s emotional state by comparing both subjective and objective data to find the relation between drivers’ physiologic feelings (i.e., Kansei Engineering method) and biosensor data (i.e., facial expression and eye movement).

There is not yet sufficient knowledge on how people want to be driven in a highly automated vehicle. Currently, trajectory behaviour as one part of the driving style is mostly implemented as a lane-centric position of the vehicle in the lane, but drivers show quite different preferences, especially with oncoming traffic and in curves. A driving simulator study was conducted to investigate seemingly natural reactive driving trajectories in curves on rural roads in an oncoming traffic scenario to better understand people’s preferences regarding driving styles. 46 subjects experienced different lateral offsets in curves in three different oncoming traffic scenarios either on a 3.00 m or on a 3.50 m lane width. The test track consisted of 12 right and 18 left curves with an oncoming truck, car or none oncoming vehicle in balanced order. Results show that reactive trajectory behaviour and wider lane widths lead to significantly higher perceived safety. Even though drivers tend to shift their lateral position in curves in manual driving situations, they do not want the automated vehicle to cut curves and hit the apex. On the other hand, they also do not wish to get close to the road side, as seen in manual driving, too. We recommend an adaptive driving trajectory, which modifies trajectory behaviour on different lane widths and adjusts its behaviour on type and position of oncoming vehicles. The results of the study help to design an accepted, preferred and trustfully trajectory behaviour for highly automated vehicles.

The increase in speed of development in the autonomous vehicle domain has led to the conceptualization of ideas such as utilizing these autonomous vehicles for services like taxis. A key component of designing such services is the Human Computer Interaction (HCI), understanding how humans interact with the autonomous system and this taxi service can be designed keeping this in mind. This report is intended on providing a systematic literature review of recent publications by performing analysis of bibliometric data using tools such as Harzing, CiteSpace, VOS Viewer, Mendeley, BibExcel and, MAXQDA. Articles for review were chosen from several sources including Google Scholar, Web of Science, SpringerLink, ResearchGate, and even a couple of chapters from Handbook of Human Factors and Ergonomics, Fourth Edition by Salvendy. This report also provides a summarized understanding of the trending topics in this emerging area and a brief discussion on how these services are currently constructed. It also provides a step-by-step procedure explaining how this analysis was carried out.

Nowadays the number of vehicles on road is increasing incrementally in emerging countries, and there is a need for proactive road health inspection methods that allow non-laborious and frequent road inspection with reasonable cost. Because of the nature of cheap and non-intrusive, vision-based road analysis has become a very popular topic in vision-based civil engineering researches around the world. In this paper, we discuss recent vision-based road distress detection methods, including our previous work and our presented work, for road distress visual inspection. This paper is divided into two parts. In the first part, we present non-deep learning based methods that aim to solve this problem of automatic road distress inspection. In the second part, we analyze recent deep learning based methods for road distress visual inspection and other related inspection of structure health monitoring. Finally, we propose our deep learning model called Modified U-Net whose goal is to solve the very difficult task of vision-based road’s crack detection. Along this paper, we also discuss about human factors in developing vision-based solutions for automatic road distress detection.

Within the study of human-automation or human-machine interaction, a phenomenon known as automation surprises confounds the design of semi-automated systems in the automotive setting. As automation systems grow in popularity and complexity, the nature of cooperation, shared control, and trust must be clearly defined such that both parties can dynamically transition between states of control and respond appropriately to the driving environment. To explore the emergence of automation surprises in transportation in the academic literature, this study utilizes bibliometric analysis and data mining tools to generate insights on prominent authors and sub-topics, identifying longstanding core articles in the topic. Results are shown in the form of descriptive figures created in software tools useful for bibliometric analysis. Insights from these figures and relevant articles related to automation surprises reveal an opportunity for review and reappraisal of automation surprises in transportation. A review of recent and well-established literature shows that automation surprises represent an important topic to address in the design of automotive automation systems.

Multiple resource theory is currently commonly applied in human–machine interactions in vehicle design. Haptic interaction is a crucial resource for driver perceptions. This paper reviews haptic research related to haptic driving from 2008 to 2020. A total of 248 journal papers and conference proceeding papers were reviewed and analyzed in CiteSpace, and 11 key elements were clustered. This paper presents them in two domains: vibration patterns and vibration scenarios. With vibration patterns, we mainly focus on patterns and locations; within this framework, we discuss applied scenarios, such as navigation, collision warning, and eco-driving. We also discuss the main challenges and future directions for transferring the results to real driving scenes and offer a roadmap for haptic research in this area.

With the rapid development of science and technology, some new terms, such as cloud computing, big data, and artificial intelligence, have become part of public life. Artificial intelligence is another technological revolution after human beings entered the information era, attracting more and more attention. As an extension and application of artificial intelligence technology in the automotive industry and transportation field, autonomous driving has received close attention from industry, academic, and even the national level in recent years worldwide. The self-driving car relies on artificial intelligence, visual computing, radar, monitoring devices, and global positioning systems to work in concert, which allows computers to operate motor vehicles automatically and safely without any human initiative. Autonomous driving technology will become mainstream for future cars in transportation. The review for autonomous driving in the artificial intelligent aspect was conducted using Cite Space, Harzing’s Publish, VOS viewer, Mendeley, Scopus, and Web of Science. By using the data from these database websites, co-citation analysis and the leading table analysis are organized together.

Maintenance procedures of technical installations are crucial to keep systems in a healthy state. Unfortunately, sometimes rare technical installations require certain types of maintenance that are not known to all technicians. We are investigating an idea that enables those technicians to still perform maintenance by using an assistance system (AS). An important part of such an AS, which we concentrate on in this work, is a task recognition engine. It keeps track of the tasks performed within a maintenance procedure, so that the AS can provide the technician with adequate information and help. We show how to build two types of task recognition models for this task recognition engine. The first was developed by Honecker & Schulte and is based on the Dempster-Shafer theory (DST). These models can be well estimated by experts, but may not represent the sequence of tasks in maintenance procedures because they are designed for parallel tasks. But still, they may be useful if there is not enough training data available. The second is based on Hidden Markov models (HMM). They are harder to estimate, but they may perform better for the sequential tasks in maintenance procedures if they are trained from a sufficient data set. Depending on the training data set’s size, we investigate which kind of model performs better by evaluating them on an example maintenance procedure.

The Internet of Things has led to the development of new operational frameworks and models within the manufacturing industry. The emergence of advanced technologies now gives managers better quality resources and knowledge to make more improved decisions on the problems they encounter. A systematic literature review was conducted in this report over articles containing the keywords “internet of things”, “manufacturing”, and “management” to receive a better understanding on the relationship between them. These keywords were searched through the databases Web of Science, Scopus, and Google Scholar via Harzing to receive articles and metadata. This metadata was then analyzed through the softwares VOSviewer and CiteSpace. These softwares were able to provide co-citation analysis, co-occurrence analysis, cluster analysis, and word clouds. The co-citation analysis and searching throughout the database Web of Science is how the 9 main references used in this report were found. The co-occurrence analysis, cluster analysis, and word cloud were used to gain insight on what subtopics should receive the most attention when analyzing the references. A subtopic found to have a lot of relevance to the keywords is a term called “Industry 4.0”. There are numerous new management systems and frameworks being developed from the integration of Internet of Things into manufacturing which are covered within this report.

The process of buying items in bulk in a supermarket, such as those in the fruit and vegetable sector, offers some opportunities for improvement, especially when older or very young people have to use this service. In this context, we use the Design Thinking methodology to find a comfortable, agile, and safe journey for people who use this type of service. Integrating Artificial Intelligence (AI) technology, User Experience/User Interface (UX/UI) approaches focused on people’s needs, visits to supermarkets, interviews with users, among other activities, we were able to design and implement a sustainable and inclusive solution to this problem.

The COVID 19 pandemic has affected the daily routine of all people, both in their family and work environments, globally. As a result, many companies in practically all the productive sectors of the countries have required to rethink several critical aspects of the business itself so as not to be absorbed by the crisis, avoid as much as possible losses in financial, human, technological resources, etc., and even disappear. In these challenging times that we live in, the corporate technology platform must provide remote connection facilities to employees. Thus, Teleworking is facilitated in a safe, flexible way, which does not delay the processes and business goals. To define this technological roadmap, it is essential to review the current specialized components, the network infrastructure, and recommendations to improve and optimize existing processes. Concerning the application of integrated methodologies for evaluating Teleworker’s technological conditions during the COVID-19, some studies have been found related to health and safety conditions, growth in the implementation of this modality, and future trends in teleworking. However, the approach to technological requirements in teleworking during the COVID-19 pandemic is still limited and not sufficiently studied. To address this challenge, this paper presents an integrated framework based on the application of Fuzzy AHP, TOPSIS, and multivariate methods for the evaluation of technological conditions of teleworkers during the COVID-19 in the construction sector. The methodology’s design is based on the international guidelines and pertinent scientific literature in Telework. The results obtained evidence that the criteria “Infrastructure,” “Digital Connectivity Services,” “Applications,” and “Users” are relevant in the evaluation of technological conditions for Telework due to the few differences in their relative weights.

The manufacturing workspace has evolved rapidly alongside the advancement of information technology. This has led to significant improvements in not only manufacturing output, but also safety and quality standards tracking. The integration of Internet of Things (IoT) technologies into the manufacturing workspace has been a major component in this evolution and contributes to Industry 4.0. This article looks to conduct a bibliometric analysis of IoT technologies and their increasing relevance as it relates to Safety Monitoring and Industry 4.0. This is accomplished through the use of readily available software tools such as MAXQDA, Harzing, CiteSpace and VOSviewer. Through use of these tools, key topics like Internet of Things, Safety Monitoring, Industry 4.0 can be readily analyzed and compiled into easy to interpret figures and data collectives. This report includes examples of the outputs of these tools as they relate to IoT, safety monitoring, and Industry 4.0. Through this analysis, it can be concluded that IOT integration into manufacturing is growing in popularity and will have a major effect on monitoring in the manufacturing workspace for the foreseeable future.

With the sudden shift from in-person to remote settings in the workplace and various other institutions as triggered by the lockdowns during the COVID-19 pandemic, this paper sought to examine the prevalence of research on the link between remote work and motivation. Two time periods were observed using VOSviewer and Harzing to determine whether a shift in focus on these topics took place as a result of the pandemic and what the overall insights were. In addition, a co-citation analysis was done in two parts. One part gave consideration of the references from a search using terms “motivation” and “remote work”. The other considered the same search terms with constraints on the dates of articles for the analysis to emphasize prior research that was more recently emphasized. Upon further analysis, it was found that a shift did take place with earlier research focusing on combating low motivation of healthcare workers in remote regions and the latest research focusing on potential solutions for reduced motivation levels of individuals who had to work from home. In both instances, it was seen that work in remote regions and work done remotely, that is from home, were associated with low motivation levels. While the area of remote work and motivation are highly relevant to job design, it also implicates human-computer interaction as an increase in the number of remote jobs may imply more time spent with computers which in turn may have potential connections with human motivation.

With the development of remote collaboration platforms, the word ‘workplace’ is no longer limited to offices. With the impact of COVID-19, more and more people bring their workplaces out of the corporate office. With that said, moving workplaces to different places has offered researchers opportunities to study the impact on productivity and ergonomics on traditional office workers in various environments. This study is a systematic literature review of the topic of workplace ergonomics and productivity. The review was conducted using platforms such as Scopus, VOSviewer, MAXQDA, Vicinitas, and Web of Science. Bibliometric and co-citation analyses were performed using these tools to show the relationship between diseases caused by bad posture and habits, such as Musculoskeletal Disorders and Computer Vision Syndrome, and productivity. Additionally, environmental and cognitive ergonomics, such as room humidity, room temperature, brightness, also play important roles in worker productivity. It is crucial to understand these issues so that employers can offer better support for their employees in all sorts of working environments without sacrificing much productivity.

The plastic industry is considered one of the most dynamic industries with the highest competitive projection in the country [1]. Thanks to the advances of this industry, new products have been developed with various applications at industrial, commercial, service levels, and society’s daily lives. Plastics are highly demanded their chemical and physical properties, versatility, and low cost. However, many challenges are arising from the growth in consumption and the dynamics of the plastics industry, such as the prices of raw materials, substitute products of plastic, the demands of consumers, government, and other interested parties with the impact of plastics on the environment during the different stages of their life cycle. Concerning the life cycle of the plastic products is especially determinant the post-consumption, where plastic waste presents a low percentage of recycling and a prolonged period of degradation, being a product questioned for its negative environmental implications. In this sense, companies in the sector must implement different strategies and tools to evaluate their environmental performance, considering the product life cycle. In the world, there are various government regulations for the responsible use of plastics. International methodologies focused on sustainable environmental management in the products, processes, and organizational level have also been developed, such as the product life cycle approach, reverse logistics, and the ISO 45001 standard. However, it is necessary to create objective and analytical methodologies for evaluating environmental management and reverse logistics that provide solutions for the plastic industry, helping companies comply with applicable legal requirements and standards, and supporting decision-making processes. Concerning the decision-making is a complex process given the complexity of the sector and the multiple criteria taken into account when evaluating and establishing improvement strategies. In the literature review, we found several studies with the application of a multicriteria combined approach focused on selecting plastic recycling methods, location of plastic processing centers, eco-design of plastic products, and selection of suppliers. Despite these considerations, the research-oriented on applying integrated methodologies for evaluating performance in the environmental management and reverse logistics in the plastic industry, under multiple criteria and uncertainty, are mostly limited and with the exciting potential of development. Therefore, this document presents a hybrid methodology for evaluating the performance in the environmental management and reverse logistics in the plastic industry by applying two techniques of Multi-criteria Decision Methods (MCDM) uses in environments under uncertainly. First, the fuzzy Analytic Hierarchy Process (FAHP) is applied to estimate the initial relative weights of criteria and sub-criteria. The fuzzy set theory is incorporated to represent the uncertainty in the judgments of decision-makers. Then, the Decision-making Trial and Evaluation Laboratory (DEMATEL) was used for evaluating the interdependences between criteria and sub-criteria. FAHP and DEMATEL are later combined for calculating the final criteria and sub-criteria weights under vagueness and interdependence. Subsequently, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to rank the companies of the plastic industry. Finally, we detect improvement opportunities for the companies of the plastic sector.

Simulators are widely used in training aircrew and seafarers as they provide a safer and more affordable alternative to training in an operational environment. In this study, a systematic literature review is conducted to review their usage in air, sea, rail, and road transportation, though the information available on rail simulation is extremely limited, despite it being a vital means to transport passengers and cargo globally. With tools such as VOSviewer and CiteSpace, it is possible to identify articles with the most impact and highest relevance to simulation training. Studies show that training effectiveness is affected by both the equipment and instruction quality. Fidelity – a simulator’s ability to replicate the real world – of the equipment determines what levels of training can be achieved, and its ability to enable the suspension of disbelief directly contribute to the students’ success. Instructors must also facilitate positive training transfer by attaining the best performance possible from the student and provide them with scenarios representative of actual conditions. Effective crew training and proper human-computer interface design are critical for accident mitigation, as the increased system complexity can take away the crew’s attention and overload training needs. Despite their popularity in air and sea transportation, simulator training for land transportation is extremely underutilized. Cost and fidelity are the primary hurdles it must overcome to achieve popularity for rail and road transportation, and further studies are required to determine its effectiveness in reducing the accident rate of novice drivers.

“Industry 4.0” has become the most significant subject of the emerging fields in manufacturing and industrial practices over the decade. It leverages the new smart technologies, including Artificial Intelligence, the Internet of Things, Autonomous Vehicles, Advanced Robots, etc. for the high involvement of automation. Such highly automated processes may raise different concerns from the traditional industry. They should have impacts on the safety management with adaption to the current development. Here we narrow down to the role of Industry 4.0 in the aspects of transformation and logistics and conducted a systematic literature review of the associated topics. We used various tools, such as CiteSpace and VOSviewer to analyze the metadata as well as several collected articles from the databases for trend, co-citation, and content analyses. We found that there is still an apparent lack of studies to incorporate the safety issues in Industry 4.0. And we suggest that safety management for Industry 4.0 on transportation and logistics should consider system design, data communication (as cybersecurity), and integration of intelligent technologies. Subjects of health and sustainability should be also included as challenges related to safety. Though many challenges are needed to be handled, emerging technologies can play significant roles to improve the safety of the work environment in the era of Industry 4.0.

Due to the Terminal demand fluctuation in the open market environment, the structure stability of digital supply chain will be affected, resulting in the instability of service quality. Based on the T-JIT theory, a conceptual model should be constructed from the change of market demand, the flow of service information on the nodes of digital supply chain, the quality of service information of nodes in the chain and the digital capability of enterprises. Then, the model hypothesizes are to be verified by the survey data of digital supply chain for Chinese manufacturing. The results show that: under certain market demand disturbance, the stronger the enterprise's digital technology capability, the higher the service information flow and service information quality of digital supply chain, and the stronger the enterprise's digital technology capability, the more significant the positive regulation effect.

Digital intrapreneurs (DIs) act and behave in a similar way to typical digital entrepreneurs without the risk of the venture. Digital Intrapreneurship, however, is under the influence of different organizational factors. This study is meant to focus on the relationship between digital intrapreneurship behavior and the workplace climate—specifically, how the workplace climate can influence DIs’ ability to innovate and exploit digital technologies. Our study revealed that three key workplace climate dimensions play into the formation of digital intrapreneurship behavior: individual, situational and organizational factors. The individual factors are represented by motivations, digital literacy, goals, needs, and the DI’s mindset. The individual factors are affected by the different situational factors that consist of collaborative norms, workplace culture, and group dynamics. The situational factors are in close relationship with organizational factors: mission, core values, and the reward system. The study also concludes that technological factors like digital infrastructure play a key role in the relation of the DI work climate and DI activity enabled said factors.

Legumes such as common beans (Phaseolus vulgaris L.) continue playing a critical role in making developed and developing economies food sustainable as alternative sources to animal proteins. The crops bring together different stakeholders in their value chain such as farmers, service providers, researchers and policymakers. Web-based portals are emerging as important tools that these different stakeholders can use to perform various tasks, access, and share vital information pertaining to common beans. However, designing portals that are specific to common beans has not been given adequate consideration in the literature. In this study, we administered a survey to profile challenges and design requirements for web-based portals that are specific to common beans. We present the survey findings in this paper. The findings provide useful insights to researchers and industry in developing future agricultural web-based portals, and can be applied to portals on other crops or different domains.

The global competitiveness creates an enormous pressure on companies as they need to reduce production costs in order to increase productivity. In this sense, the SMED and 5S tools appear as competent tools to reduce the waste associated with these processes. This work aims to study and assess some processes in a company in the textile sector. Improvement proposals supported in the SMED and 5S methodology are presented in different areas of the company. Advantages, investments and respective return times are presented. Regarding to SMED, reductions in setup time in the order of 30–40% were obtained with investment return times between 6 and 7 months. The implementation of the 5S allowed to reduce the time and distance traveled for a given task. The reorganization of the area, it was possible to obtain a space gain of about 58 m2. For this purpose, a multi-criteria decision model was designed to diagnose the critical areas for the implementation of Lean tools. Then, a questionnaire was also applied to the workers, with the goal to assess the impact of the implementation of lean philosophy in the field of occupational safety.

Ergonomics training is an essential element for maintaining occupational health and safety. With the world rapidly digitizing, it is important to adopt new methods to accommodate computer-supported learning while keeping the same level of efficiency and collaboration as in-person training sessions. Emerging collaborative technologies can be a potential means to conduct training over a virtual platform. In this systematic literature review, publications for ergonomics training and collaborative technologies were analyzed using tools such as Harzing’s Publish or Perish, VOS Viewer, MAXQDA, Mendeley, CiteSpace and BibExcel. Through content and co-citation analyses, emerging trends were identified. Various databases such as Google Scholar, Web of Science, SpringerLink, and ResearchGate served as the primary sources for references. From this study, it was assessed that there was significant research on the topic of interest, however, there is immense potential for growth particularly in the context of collaborative robots and virtual reality. Performing a literature review will help bring awareness to the importance of being able to conduct ergonomics training through a virtual collaborative technology.

With the rapid development of wireless sensor technology, wireless sensors have the potential to be applied in various fields. The introduction of wireless sensors in safety application is one of the feasible applications. The wireless sensors can be used to monitor human and environment to avoid potential safety issues. In this study, a systematic literature review was conducted by software like VOSviewer, CiteSpace, Harzing’s Publish or Perish, MAXQDA and Mendeley. A trend analysis was conducted. It was found that the wireless sensors in the safety application are becoming increasingly popular. However, compared with a large number of wireless sensor papers, there is still a lot of research space in the safety application. The engagement measurement by Vicintas showed there is a lot of room for popularization of wireless sensors for safety in daily life. A co-citation analysis demonstrated the three clusters of wireless sensors in the safety application: wireless sensor network, location privacy and communication protocol. The citation burst analysis showed the trend has shifted from sensor network design to location privacy, Internet of Things (IoT) and applications. The Content Analysis listed the most frequent words from 15 selected key articles (such as data, node, network, monitoring). It can be concluded that safety applications of wireless sensors are increasing, and there is still a lot of work to be done.