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With the upgrading and innovation of the logistics industry, the requirements for the level of transportation smart technologies continue to increase. The outbreak of the COVID-19 has further promoted the development of unmanned transportation machines. Aimed at the requirements of intelligent following and automatic obstacle avoidance of mobile robots in dynamic and complex environments, this paper uses machine vision to realize the visual perception function, and studies the real-time path planning of robots in complicated environment. And this paper proposes the Dijkstra-ant colony optimization (ACO) fusion algorithm, the environment model is established by the link viewable method, the Dijkstra algorithm plans the initial path. The introduction of immune operators improves the ant colony algorithm to optimize the initial path. Finally, the simulation experiment proves that the fusion algorithm has good reliability in a dynamic environment. © 2022 IEEE.
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Concerns about the effects of global warming and predicted rising sea levels are radically changing government policies to lower carbon emissions using sustainable green technologies. The United Kingdom aims to reduce its carbon emissions by 78% by 2035 and achieve net zero by 2050. This is a major driver for energy management and is influencing development of buildings which use autonomous smart technologies to assist in lowering carbon footprints. These Smart Buildings use digital technologies by connecting sensor data with intelligent systems which can be monitored remotely to provide more efficient facilities management. The data harvested and transmitted from the IoT sensors provides a key component for Big Data Analytics using techniques such as Association rule mining for intelligent interpretation which can assist facilities management becoming more agile regarding office space utilization. The shift toward hybrid working particularly instigated by the COVID-19 pandemic and recent energy supply concerns caused by the Ukraine crisis presents facilities management with opportunities to optimize their space, reduce energy consumption, and allow them to identify commercial opportunities for the unused space throughout the building. This chapter discusses the use of association rules for data mining derived from a simulated dataset for an investigative analysis of office workflow patterns for facilities management operations, resource conservation, and sustainability. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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IoT seems to be the trending solution in all sectors notably because of the yield in productivity, efficiency, effective strategies, and results that are associated with adapting to this technology. These positive results are enormously experienced in one of the crucial sectors which determine and ensure the prolonged healthy life expectancy of mankind. It is well noted that a lot of work has been done on this topic in Academia and Corporate field all over the world but this paper will present a selective review that has been done so far by the Academic world as a scholarly article and a resource for the Health Sector in Fiji to earnestly integrate smart technologies in its architecture. © 2022 IEEE.
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Using bibliometric analysis, this research provides a comprehensive, systematic, and visual overview of 441 studies related to smart tourism, which were published between 2010 and 2021, thus considering the state of research and trends in this research field from the beginning of smart tourism research to the entry of the fifth-generation mobile communication technology era and the explosion of COVID-19. It also offers insights into its future research agenda and advancing the development of smart tourism. This paper can provide intuitive and valuable information to promote theoretical and practical research on smart tourism. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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The global pandemic has significantly accelerated the need for remote monitoring and diagnostics of airline operations and assets. As passenger and cargo flights are impacted from all directions, maintenance can be the steady, reliable part of the puzzle that helps get things back on track. This chapter explores the aircraft safety challenges that can be addressed with better maintenance technology and human factor modeling. Aircraft safety relies heavily on maintenance. During the COVID-19 recovery phase, airline operators need to focus on the application of a robust management of change process to implement better maintenance technology, identify new aircraft safety risks, determine effective mitigation measures, and implement strategies for deploying changes accordingly. For years aircraft maintenance routines have been carried out in the same manner without change, now with international travel restrictions, social distancing, reduced staff, and limited maintenance funding, the need for smarter ways of doing maintenance is obvious. In this regard smart technology has an important role to play. For instance, IoT data generates the capacity for predictive aircraft maintenance, AI introduces the capacity for smart, deep-learning machines to make predictive maintenance more accurate, actionable, and automatic. AI-enabled predictive maintenance leverages IoT data to predict and prevent aircraft failures. While smart technology enhances aircraft safety through better maintenance performance on the one hand, there are technical and human factor problems induced by COVID-19 on the other. The Safe Aircraft System (SAS) model, based on the Dirty Dozen and SHELL human factor models, is an initiative proposed to minimize such COVID-19 problems. This work shows through a case illustration that SAS modeling is a useful tool in identifying potential hazards/consequences associated with any major or minor changes in flight operations. Hence the synergistic effect of smart maintenance and the SAS model in enhancing aircraft system safety are demonstrated. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Organizations experiment with how smart technology can be used to manage employees since before COVID-19 and the possibilities seem almost limitless. However, the question of how this can be achieved without impairing the so-needed trust inside organizations is yet to answer. Hence, in this study, we employ a crisp-set QCA to investigate what trust-enabling datafication control configurations look like. Drawing on unique survey data from Switzerland, we show that datafication control can go hand in hand with trust if organizations make efforts for employee-centricity. Further, we can reveal four distinct ways of how organizations can implement employee-centricity to mitigate possible trust-impairing signals that stem from augmented data-gathering and analysis capabilities. Our results contribute to the still heated debate on the duality of control and trust. They also help leaders to navigate through the unmanageable multitude of possible and even trust-toxic combinations. © 2022 IEEE Computer Society. All rights reserved.
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There is no international consensus on a comprehensive criterion to classify human settlements into urban and rural settlements. Different national criteria are used for delineating the borders between the two types of settlements. The main components of the criteria are population size, population density, population economic activity, administrative and legal and services and facilities. Whether all these criteria have been used or some of them, an outright socio-cultural and economic distinction between the two categories of settlements have developed over years around the world. The widely used virtual space during the pandemic provided people with access to facilities and services and enabled them to work for places that usually require their physical presence. The literature has not yet covered this point. Therefore, this paper aims at revisiting the classification of urban and rural areas in the COVID-19 aftermath. Through desk work and employing qualitative and quantitative research approaches, secondary data was collected from published relevant journals, reports, books, and websites. Content and comparative analysis for analysing qualitative data and content and quantitative comparative analysis and tabulation were used to carry out the research. This paper suggested that the world is in a transitional period towards full urban status. During this period, accessibility to virtual space can be used as a comprehensive criterion for calcifying human settlements into urban and rural. © 2022 by MIP.
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Service Robots, Artificial Intelligence (AI), and Service Automation have shown to be increasingly advantageous to hotel businesses. Especially, during the COVID-19 pandemic, hotels are starting to adopt artificial intelligence (AI) and robotics to increase the quality of their service. The are several studies have examined the costs and benefits of implementing these smart technologies, only a few of them have investigated the impact on hotel employees job performance. The purpose of this study is to investigate whether hotel employees' self-efficacy, their attitude on technology adoption, and their relationship quality with supervisor can affect their job performance. A convenience sample method was used to select respondents. The survey was distributed to employees of five- and four-star hotels in Jakarta who worked with technology equipment daily. There were 171 research participants involved in this study. Primary data was gathered using a questionnaire survey and analyzed quantitatively using SmartPLS to test for causal relationships in the data. The outcome of this research found that there is a positive significance relationship between employees' self-efficacy and their job performance, employees' relationship quality and their job performance, and also with their attitude on smart technology adoption and their job performance. These findings contribute to the impact of smart technology adoption literature, particularly in smart technology adoption in hospitality industry. © 2022 IEEE.
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Smart tech offers much promise for tourism recovery from the COVID-19 crisis and the broader issue of decarbonising tourism. This paper investigates how accommodation managers engaged with smart tech during the crisis, and the journey of learning how to use numerical data output to drive sustainability actions. Interviews with nine accommodation managers/owners at six sites uncovers a ‘tech journey' that extends prior to, and beyond, the acquisition and installation of the smart technology itself. The journey is explained by a new framework that recognises the need for users (here, the accommodation managers) of smart tech to ‘make it their own', integrating it into their decisions, workflows and finally, identity. This can only happen through a capacity to understand what the data (i.e. numerical outputs) mean, and a process of transforming data into actions. Understanding these processes of ‘data domestication' and ‘data clotting' addresses key gaps in how to achieve potentially radical changes in resource use. Only one case study site had reached this final stage of the journey. The theoretical framework uses the findings from each case to propose early diagnostic questions/tools that can help identify where smart system may need assistance to move from data to action.
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This chapter discusses an important topic in factory management, that of improving the understandability of AI applications for group multi-criteria decision making in manufacturing systems. Due to its long-term and cross-functional impact, decision making may be more critical to the competitiveness and sustainability of manufacturing systems than production planning and control. This chapter uses the example of choosing the right smart and automation technologies for factories during the COVID-19 pandemic. This topic is of particular importance as many factories are forced to close or operate on a smaller scale (using a smaller workforce), thus pursuing further automation. Artificial intelligence and Industry 4.0 technologies have many applications in this area, most of which can also be applied for other decision-making purposes in manufacturing systems. First, a systematic procedure was established to guide the group multi-criteria decision-making process. Applications of AI and XAI to identify targets are first reviewed. Subsequently, the application of AI and XAI to selection factors and development of criteria is presented. Artificial intelligence techniques are widely used to derive criteria priorities. Therefore, it is particularly important to explain XAI techniques and tools for such AI applications. Aggregating the judgments of multiple decision makers is the next focus, followed by the introduction of AI and XAI applications to evaluate the overall performance of each alternative. Taking fuzzy ranking preference based on similarity to ideal solution (FTOPSIS) as an example, the application of XAI techniques and tools in explaining comparison results using FTOPSIS is illustrated. Another AI technology used for the same purpose is fuzzy VIKOR. XAI techniques and tools for interpreting fuzzy VIKOR are also presented. Finally, several metrics are proposed to evaluate the effectiveness of XAI techniques or tools for decision making in the manufacturing domain. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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One of the main impacts of technologies in the tourism sector is traveler empowerment. Technology has allowed travelers to be a lot more informed and to take a proactive role in organizing their own trip. Now, tourists are much more demanding, have several options to choose, and have more bargaining power. Tourist has also become not just a mere visitor, but a content generator sharing their experience with other travelers. This research intends to identify the adoption of technologies in the hotel and restaurant sector and secondly to identify smart technologies that can help to eradicate the virus and normalize the hospitality business. The research question is: How COVID-19 could be a trigger for the adoption of new technologies in the hospitality sector? The objectives are: (i) to identify new technologies already adopted in the hotel and restaurant areas, (ii) to pinpoint how new technologies could help in health and cleanness protocols, and (iii) to categorize changes in operational areas after the consecutive lockdowns. To achieve these goals, several case studies were collected to show and explain best practices for the future. The results are expected to help identify outcomes to build a survey to apply to hospitality professionals. Also, those outcomes will be useful in improving professionals' tools, resources, and procedures to help to eradicate the COVID-19 virus. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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One of the main impacts of technologies in the tourism sector is traveler empowerment. Technology has allowed travelers to be a lot more informed and to take a proactive role in organizing their own trip. Now, tourists are much more demanding, have several options to choose, and have more bargaining power. Tourist has also become not just a mere visitor, but a content generator sharing their experience with other travelers. This research intends to identify the adoption of technologies in the hotel and restaurant sector and secondly to identify smart technologies that can help to eradicate the virus and normalize the hospitality business. The research question is: How COVID-19 could be a trigger for the adoption of new technologies in the hospitality sector? The objectives are: (i) to identify new technologies already adopted in the hotel and restaurant areas, (ii) to pinpoint how new technologies could help in health and cleanness protocols, and (iii) to categorize changes in operational areas after the consecutive lockdowns. To achieve these goals, several case studies were collected to show and explain best practices for the future. The results are expected to help identify outcomes to build a survey to apply to hospitality professionals. Also, those outcomes will be useful in improving professionals' tools, resources, and procedures to help to eradicate the COVID-19 virus. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Introduction: The exponential increase of the older segment of the population (1) is coinciding with the growing challenges of a digital society in different socio-cultural contexts (2). Objective(s): This exploratory study aims to analyze older adult perspectives of how smart technology influenced their meaning in life during the Covid-19 Public Health Emergency period, using qualitative research at a cross-national level. Method(s): Three hundred and fifty one community-dwelling older participants aged 65-87 years were included in the study. Participants were Italian, Mexican, Portuguese and Spanish. All the narratives went through a process of content analysis. Result(s): Findings of content analysis produced six themes: Meaningful relations, rewarding activities, spirituality, health and safetyrelated support, self-growth, and physical activity. Smart technology was important in promoting significant relations for Mexican older adults (71.3%), rewarding activities for Portuguese older adults (57.1%), spirituality for Spanish older participants (71.6%), and physical activity for Italian older adults (29.5%). Conclusion(s): This study indicated that smart technology during the Health Emergency period was important for the meaning in life of older populations, mostly by facilitating meaningful relations, rewarding activities and spirituality. Future interventions with older adults during pandemic periods should consider the diversity of themes associated with increasing older adult well-being, from a cross-cultural perspective. 1. von Humboldt S & Leal I. The old and the oldest old: Do they have different perspectives on adjustment to aging?. Int J Gerontol;9:156-160. 2. von Humboldt S et al. Does spirituality really matter? - Astudy on the potential of spirituality to older adult's adjustment to aging. Jpn Psychol Res, 56;114-125.
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During the COVID-19 pandemic, some smart technology applications were more effective than had been expected, whereas some others did not achieve satisfactory performance. Consequently, whether smart technology applications in healthcare are sustainable is a question that warrants investigation. To address this question, a hybridising subjective and objective fuzzy group decision-making approach with explainable artificial intelligence was proposed in this study and then used to evaluate the sustainability of smart technology applications in healthcare. The contribution of this research is its subjective evaluation of the sustainability of smart technology applications followed by correction of the evaluation outcome on the basis of the applications' objective performance during the COVID-19 pandemic. To this end, a fuzzy nonlinear programming model was formulated and optimised. In addition, the impact of several major global events that occurred during the pandemic on the sustainability of smart technology applications was considered. The proposed methodology was applied to evaluate the sustainability levels of eight smart technology applications in healthcare. According to the experimental results, three applications-namely healthcare apps, smartwatches, and remote temperature scanners-are expected to be highly sustainable in healthcare, whereas one application, namely smart clothing, is not.
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BACKGROUND: Temperature-taking behaviors vary with levels of circulating infectious illness; however, little is known about how these behaviors differ by demographic characteristics. Populations with higher perceived risks of illness are more likely to adopt protective health behaviors. OBJECTIVE: We investigated differences in temperature-taking frequency and the proportion of readings that were feverish among demographic groups (age, gender, urban/rural status) over influenza offseason; influenza season; and waves 1, 2, and 3 of the COVID-19 pandemic. METHODS: Using data from smart thermometers collected from May 1, 2019, to February 28, 2021, across the United States, we calculated the frequency of temperature-taking and the proportion of temperature readings that were feverish. Mixed-effects negative binomial and mixed-effects logistic regression analyses were performed to identify demographic characteristics associated with temperature-taking frequency and the proportion of feverish readings, respectively. Separate models were fit over five study periods: influenza offseason (n=122,480), influenza season (n=174,191), wave 1 of COVID-19 (n=350,385), wave 2 (n=366,489), and wave 3 (n=391,578). RESULTS: Both temperature-taking frequency and the proportion of feverish readings differed by study period (ANOVA P<.001) and were the highest during influenza season. During all periods, children aged 2-5 years and 6-11 years had significantly higher frequencies of temperature-taking than users aged 19-30 years, and children had the highest proportion of feverish readings of all age groups, after adjusting for covariates. During wave 1 of COVID-19, users over the age of 60 years had 1.79 times (95% CI 1.76-1.83) the rate of temperature-taking as users aged 19-30 years and 74% lower odds (95% CI 72%-75%) of a reading being feverish. Across all periods, men had significantly lower temperature-taking frequency and significantly higher odds of having a feverish reading compared to women. Users living in urban areas had significantly higher frequencies of temperature-taking than rural users during all periods, except wave 2 of COVID-19, and urban users had higher odds of a reading being feverish in all study periods except wave 1 of COVID-19. CONCLUSIONS: Temperature-taking behavior and the proportion of readings that were feverish are associated with both population disease levels and individual demographic characteristics. Differences in the health behavior of temperature-taking may reflect changes in both perceived and actual illness risk. Specifically, older adults may have experienced an increase in perceived risk during the first three waves of COVID-19, leading to increased rates of temperature monitoring, even when their odds of fever were lower than those of younger adults. Men's perceived risk of circulating infectious illnesses such as influenza and COVID-19 may be lower than that of women, since men took their temperature less frequently and each temperature had a higher odds of being feverish across all study periods. Infectious disease surveillance should recognize and incorporate how behavior impacts illness monitoring and testing.
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Cyber security is the implementation of smart technologies to safeguard computer systems, mobile devices, communication networks or most importantly the sensitive and confidential data saved in those systems or devices from various types of cyber-attacks, unauthorized access, hackers or intruders. Cyber security can also be considered as a subset of information security because information security is a general term. It aims to protect a wider domain which includes all kinds of information assets either hard copy or soft copy. The recent accelerating rise in digitalization due to Covid-19 has brought in many new challenges. The amount of personal data present on the web due to the same has raised concerns among users. However, it's not only the personal data that is a matter of concern but also the dataset which is given as input to numerous machine learning and deep learning models. Local networks are prone to attacks and intrusion activities now more than ever. As a result, cyber security experts have been working on the development of more complex monitoring systems and algorithms for the detection and prevention of such activities. Various technologies like machine learning and deep learning might play a significant role in improving cyber security. It can help in analyzing patterns and improving the models for recognizing similar attacks in future. This research work aims to study intrusion detection systems in detail and differentiate between intrusion detection systems, intrusion prevention systems and firewalls as IDS and IPS are commonly regarded as the same thing. It also highlights the previous works related to this subject along with their suggested methods. © 2022 IEEE.
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The Internet of Things (IoT) is an innovative technology with billions of sensors in various IoT applications. Important elements used in the IoT are sensors that collect data for desired analyses. The IoT and sensors are very important in smart cities, smart agriculture, smart education, healthcare systems, and other applications. The healthcare system uses the IoT to meet global health challenges, and the newest example is COVID-19. Demand has increased during COVID-19 for healthcare to reach patients remotely and digitally at their homes. The IoT properly monitors patients using an interconnected network to overcome the issues of healthcare services. The aim of this paper is to discuss different applications, technologies, and challenges related to the healthcare system. Different databases were searched using keywords in Google Scholar, Elsevier, PubMed, ACM, ResearchGate, Scopus, Springer, etc. This paper discusses, highlights, and identifies the applications of IoT healthcare systems to provide research directions to healthcare, academia, and researchers to overcome healthcare system challenges. Hence, the IoT can be beneficial by providing better treatments using the healthcare system efficiently. In this paper, the integration of the IoT with smart technologies not only improves computation, but will also allow the IoT to be pervasive, profitable, and available anytime and anywhere. Finally, some future directions and challenges are discussed, along with useful suggestions that can assist the IoT healthcare system during COVID-19 and in a severe pandemic.
Subject(s)
COVID-19 , Internet of Things , COVID-19/diagnosis , COVID-19/epidemiology , Delivery of Health Care , Humans , Internet , Monitoring, Physiologic , PandemicsABSTRACT
Background: Although smart speaker technology is poised to help improve the health and well-being of older adults by offering services such as music, medication reminders, and connection to others, more research is needed to determine how older adults from lower socioeconomic position (SEP) accept and use this technology. Objective: This study aimed to investigate the feasibility of using smart speakers to improve the health and well-being of low-SEP older adults. Methods: A total of 39 adults aged between 65 and 85 years who lived in a subsidized housing community were recruited to participate in a 3-month study. The participants had a smart speaker at their home and were given a brief orientation on its use. Over the course of the study, participants were given weekly check-in calls to help assist with any problems and newsletters with tips on how to use the speaker. Participants received a pretest and posttest to gauge comfort with technology, well-being, and perceptions and use of the speaker. The study staff also maintained detailed process notes of interactions with the participants over the course of the study, including a log of all issues reported. Results: At the end of the study period, 38% (15/39) of the participants indicated using the speaker daily, and 38% (15/39) of the participants reported using it several times per week. In addition, 72% (28/39) of the participants indicated that they wanted to continue using the speaker after the end of the study. Most participants (24/39, 62%) indicated that the speaker was useful, and approximately half of the participants felt that the speaker gave them another voice to talk to (19/39, 49%) and connected them with the outside world (18/39, 46%). Although common uses were using the speaker for weather, music, and news, fewer participants reported using it for health-related questions. Despite the initial challenges participants experienced with framing questions to the speaker, additional explanations by the study staff addressed these issues in the early weeks of the study. Conclusions: The results of this study indicate that there is promise for smart speaker technology for low-SEP older adults, particularly to connect them to music, news, and reminders. Future studies will need to provide more upfront training on query formation as well as develop and promote more specific options for older adults, particularly in the area of health and well-being.
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Food, is very essential in our Life. because without food humans can't survive. During the time of COVID-19 pandemic, it is extremely crucial to take precautions about the food we consume. During this pandemic, people around the world have become more and more cautious about food security. Keeping this in mind food safety and quality is one of the vital matters we observe throughout our lives. Internet of Things (IOT) is a domain that we can use anywhere to improve the quality by using different sensors used for tracking and tracing things. IOT with food supply chain (FSC) would elevate food standards. This paper explores more about IOT devices working to secure packet food and frozen food. This paper also discusses future scope about the same model. By this research, technology and information might be valuable for all the consumers to increase awareness in addition to knowledge. © 2022 IEEE.
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This paper presents a definition of what Autonomous Vehicle and their functions are, how they operate, gather data and what threats they have to encounter-with throughout their operations. As explained later in the article, we can observe that there are a handful of ways by which a self-driving vehicle can gather information about it's surrounding environment beside the sensors it is equipped with. These methods of gathering data are thoroughly explained in the article alongside their advantages and disadvantages. This article also tries to have a look at the methods an AV can overcome the computing challenges it is facing while guiding and controlling the vehicle, as well as staying in communication with other vehicles or any object that can provide useful information to the vehicle. © 2021 ACM.