A Detection System for Comfortable Locations Based on Facial Expression Analysis While Riding Bicycles

In recent years, the use of bicycle as a healthy and economical means of transportation has been promoted worldwide. In addition, with the increase in bicycle commuting due to the COVID-19, the use of bicycles are attracting attention as a last-mile means of transportation in Mobility as a Service(MaaS). To help ensure a safe and comfortable ride using a smartphone mounted on a bicycle, this study focuses on analyzing facial expressions while riding to determine potential comfort along the route with the surrounding environment and to provide a map that users can explicitly feedback(FB) after riding. Combining the emotions of facial expressions while riding and FB, we annotate comfort to different locations. Afterwards, we verify the relationship between locations with high level of comfort based on the acquired data and the surrounding environment of those locations using Google Street View(GSV). © 2023 Owner/Author.

The smart city and COVID-19

Smart cities are concepts much loved by politicians and technologists but are very difficult to bring about in practice. There are many isolated applications in cities such as operating streetlamps, but very few, if any, examples of integrated applications sharing data and managing the city as a holistic entity rather than a set of disparate and unconnected applications. This is despite hundreds of trials and indicates how difficult bringing about a smart city will be. The key challenge is the wide range of interested parties in a city including the elected city authority, subcontractors and suppliers to the authority, emergency services, transport providers, businesses, residents, workers, tourists, and other visitors. Some of these entities will be primarily driven by finance, such as businesses and transport providers. Some will be driven by political considerations. Some will be concerned with the quality of life as well as financial costs. In some cases, there will be conflicting interests-the city may want as much information as possible on people in the city, whereas individuals may want privacy and the minimum data stored concerning their movements and attributes. COVID-19 does not change any of these issues, but it does increase the importance of some applications such as smart health, logistics, people surveillance, data security, and crisis management, while reducing the importance of others such as traffic management. It may result in more willingness for monitoring and data sharing if this can be shown to result in better control of the virus. © 2023 the authors.

Does COVID-19 change consumers' involvement in e-commerce last-mile delivery? An investigation on behavioural change, maintenance and habit formation

The COVID-19 pandemic accelerates e-commerce adoption, which naturally induces an expedited acceptance of innovative last-mile deliveries. Focusing on self-collection via parcel lockers technology, this study investigates consumers' behavioural change, maintenance and habit formation related to e-commerce deliveries in response to the pandemic. We use a survey instrument for data collection (n = 500) and structural equation modelling for data analysis. Anchored on the risk–attitude–norm–ability–self-regulation (RANAS) framework, this study found that risk, attitude, norm, ability and self-regulation factors related to using the contactless shopping-delivery channel lead to the formation of self-collection habits, and that the formation process is fully mediated by consumers' maintenance motivation to use the channel. Furthermore, consumers' online shopping habit partially mediates the relationship between the maintenance motivation and self-collection habit formation. Consumers who were already frequent online shoppers before the pandemic are less likely to pick up self-collection as a habit during the pandemic. Additionally, model comparisons are conducted which reveal the differentiated habit formation processes. The findings contribute to a theoretical understanding of the formation of delivery habit as driven by the pandemic. Practical implications are also created which guide logistics and e-commerce operators' interactions with consumers in the post-pandemic period.

Collaborative mapping of the noise level in Guayaquil during COVID-19

The SARS-CoV-2 virus triggered a never-before-seen scenario worldwide. Ecuador declared a state of emergency to contain coronavirus transmission by applying social isolation policies and mobility limitations. During this period, noise pollution decreased in Guayaquil city. This study proposes the use of smartphones to collect noise data and generate soundscape maps of Guayaquil during different time slots. The results revealed traffic as the predominant type of noise, followed by vehicles, buses, and people´s voices. This article demonstrates the feasibility of crowdsourcing for the collection of environmental variables. © 2022 National Institute for Space Research, INPE. All rights reserved.

Pandemics and the built environment: A human– building interaction typology

Surveys of urban history from ancient times to the present reveal a continuum of collective responses to pandemics ranging from quarantine facilities and monitoring the spread of disease to building new wastewater networks. The contemporary COVID-19 pandemic includes new digital tools and techniques that supplement (and sometimes replace) the existing analogue responses, while raising new ethical issues with respect to privacy. A typology of pandemic responses in cities is created, based on human–building interaction (HBI) principles. This typology can be used to compare and contrast analogue and digital responses relating to distancing, monitoring and sanitising. It provides a summary of a wide range of individual and collective implications of pandemics and demonstrates the indelible connections between pandemics and the built environment. In addition, the typology provides a tool to interpret some of the opportunities and drawbacks of digitalising cities. PRACTICE RELEVANCE The COVID-19 pandemic has demonstrated the enduring co-evolution of cities and disease through history. This study aims to inform future pandemic preparedness by providing a framework for designers, managers and users of public spaces to evaluate the multiple implications of emerging technologies that are integrated within the urban fabric. While the rapid rise of digitalisation to advance urban health agendas continues to raise new questions relating to individual and civic freedoms, HBI qualitatively provides a lens through which to examine the overlapping spatial, ethical, and temporal consequences for humans and the built environment. Urban planning researchers and designers can use HBI principles to humanise the sustainable smart city. © 2023 The Author(s).

Managing Safety and Security in the Smart City: Covid-19, Emergencies and Smart Surveillance

The chapter examines the role and potential inherent in surveillance systems in smart cities today. The Covid-19 pandemic and the resultant restrictions to mobility, on the one hand, and the need for strengthened enforcement measures highlighted the already existing weaknesses and contingencies besetting surveillance in smart cities. The chapter makes a case that the adoption of smart city surveillance and infrastructure management systems may contribute to the improvement of safety and security in the smart city as well as to an overall enhancement of the smart city's resilience. The discussion in this chapter focuses on the complex processes of data acquisition, data sharing, and data utilization to explain in which ways they all add to smart surveillance systems that-while aware of individual freedoms and privacy issues-contribute to the process of making a smart city resilient. To showcase the applicability of these findings, a wireless mesh network (WMN) surveillance system is presented. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Applying Machine Learning and Model-Driven Approach for the Identification and Diagnosis of Covid-19

Ubiquitous environments are not fixed in time. Entities are constantly evolving;they are dynamic. Ubiquitous applications therefore have a strong need to adapt during their execution and react to the context changes, and developing ubiquitous applications is still complex. The use of the separation of needs and model-driven engineering present the promising solutions adopted in this approach to resolve this complexity. The authors thought that the best way to improve efficiency was to make these models intelligent. That's why they decided to propose an architecture combining machine learning with the domain of modeling. In this article, a novel tool is proposed for the design of ubiquitous applications, associated with a graphical modeling editor with a drag-drop palette, which will allow to instantiate in a graphical way in order to obtain platform independent model, which will be transformed into platform specific model using Acceleo language. The validity of the proposed framework has been demonstrated via a case study of COVID-19. © 2023 IGI Global. All rights reserved.

Smart Tourism using Attractive and Safe Travel Recommendation Technology

The tourism sector was among the most affected sector during the COVID-19 pandemic and has lost up to USD 5.87 billion potential revenue. Since many countries closed the borders, including Indonesia, by applying travel restrictions and thus tourists postponed their visits. Whereas vaccine distribution has shown good progress as the vaccination percentage in Jakarta and Bali has shown promising results since the majority of its population has been vaccinated, and it helps many industries, including tourism, recover. However, the pandemic might change tourist behavior. In addition, information about tourist destinations is spread poorly in various sources, and it psychologically affects tourists' decision to visit. Many works have been published to address this issue with the recommendation system. However, it does not provide geopolitical variables such as PPKM in Indonesia to ensure safeness for the tourist. Therefore, this research aims to enhance innovations in the tourism industry by considering the geopolitics factor into the system using Multiple Linear Regression. The result of this research demonstrates the effectiveness of geopolitics added variable on three different cities Jakarta, Java, and Bali. It can be implemented in a wide area in Indonesia. For further research, the proposed model can be used in a wide area in Indonesia and developed for a more comprehensive recommendation system. © 2022 IEEE.

Path Planning of Follow-up Transport Robot Based on Machine Vision

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.

Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review

The use of machine learning and data-driven methods for predictive analysis of power systems offers the potential to accurately predict and manage the behavior of these systems by utilizing large volumes of data generated from various sources. These methods have gained significant attention in recent years due to their ability to handle large amounts of data and to make accurate predictions. The importance of these methods gained particular momentum with the recent transformation that the traditional power system underwent as they are morphing into the smart power grids of the future. The transition towards the smart grids that embed the high-renewables electricity systems is challenging, as the generation of electricity from renewable sources is intermittent and fluctuates with weather conditions. This transition is facilitated by the Internet of Energy (IoE) that refers to the integration of advanced digital technologies such as the Internet of Things (IoT), blockchain, and artificial intelligence (AI) into the electricity systems. It has been further enhanced by the digitalization caused by the COVID-19 pandemic that also affected the energy and power sector. Our review paper explores the prospects and challenges of using machine learning and data-driven methods in power systems and provides an overview of the ways in which the predictive analysis for constructing these systems can be applied in order to make them more efficient. The paper begins with the description of the power system and the role of the predictive analysis in power system operations. Next, the paper discusses the use of machine learning and data-driven methods for predictive analysis in power systems, including their benefits and limitations. In addition, the paper reviews the existing literature on this topic and highlights the various methods that have been used for predictive analysis of power systems. Furthermore, it identifies the challenges and opportunities associated with using these methods in power systems. The challenges of using these methods, such as data quality and availability, are also discussed. Finally, the review concludes with a discussion of recommendations for further research on the application of machine learning and data-driven methods for the predictive analysis in the future smart grid-driven power systems powered by the IoE.

Programmable polymer materials empowered by DNA nanotechnology

Over the past century, synthetic polymers have had a transformative impact on human life, replacing nature-derived materials in many areas. Yet, despite their many advantages, the structure and function of synthetic polymers still appear rudimentary compared to biological matter: cells use dynamic self-assembly to construct complex materials and operate sophisticated macromolecular devices. The field of DNA nanotechnology has demonstrated that synthetic DNA molecules can be programmed to undergo predictable self-assembly, offering unparalleled control over the formation and dynamic properties of artificial nanostructures. Intriguingly, the principles of DNA nanotechnology can be applied to the engineering of soft programmable materials, bringing the abilities of synthetic polymers closer to their biological counterparts. In this perspective, we discuss the unique features of DNA-functionalized polymer materials. We describe design principles that allow researchers to build complex supramolecular architectures with predictable and dynamically adjustable material properties. Finally, we highlight two key application areas where this biologically inspired material class offers particularly promising opportunities: (1) as dynamic matrices for 3D cell and organoid culture and (2) as smart materials for nucleic acid sequencing and pathogen detection.

Impact of Biomedical Engineering on Human & social Dynamics: A Review on Recent Approaches Through Bioengineering from Recent Past to Post-Covid-19

INTRODUCTION: The paper aims to discuss the various issues/ problems that people face in day to day life. Using diverse scenarios ranging from mental health issues to common grafting procedures, the author here strives to link these issues to bioengineering and how they are being impacted by modern technology. Most methods and procedures discussed attempt to utilize day-to-day activities and ease of access. The paper has adopted rapid review method. For literature collection, Google scholar database has been used with a scope of specific keywords and time frame of 5 weeks to complete the study © COPYRIGHT RED FLOWER PUBLICATIONS PVT LTD

Molecular Diagnostics on Smartphone

During the COVID-19 pandemic, point-of-care genetic testing (POCT) devices were used for on-time and on-site detection of the virus, which helped to prevent and control the spread of the pandemic. Smartphones, which are widely used electronic devices with many functions, have the potential to be used as a molecular diagnostic platform for universal healthcare monitoring. Several integrated diagnostics platforms for the real-time and end-point detection of COVID-19 were developed using the functions of smartphones, such as the operating system, power, sound, camera, data storage, and display. These platforms use the 5V output power of smartphones, which can be amplified to power a micro-capillary electrophoresis system or a thin-film heater, and the CMOS camera of smartphones can capture the color change during a colorimetric loop-mediated isothermal amplification test and detect fluorescence signals. Smartphones can also be used with self-written web-based apps to enable automatic and remote pathogen analysis on POCT platforms. Our lab developed a handheld micro-capillary electrophoresis device for end-point detection of SARS-CoV-2, as well as an integrated smartphone-based genetic analyzer for the qualitative and quantitative colorimetric detection of foodborne pathogens with the help of a custom mobile app. © 2023 SPIE.

Technology Application in Tourism Festivals in Asia: Theoretical Discussions

Modern-day tourism festivals in Asia have greatly embraced technology to boost festival quality, attendee's experience and marketing potential. With this development, technology enhances tourism festival demand, innovation, and attendance. This in turn boosts the market value since it creates a modernized, industrialized, and commercialized industry that can compete favorably on the global tourism market. Although the application of advanced technology particularly in festivals has been anticipated to be associated with several technical challenges, financial and human resource constraints, it is important to note that if appropriate and acceptable models are identified and factors that influence technological applied, a long-lasting impression on the minds of the festival visitors can be created. This study was done to both offer a theoretical overview of the application of technologies in tourism festivals and to inform development of strategy in the Asian tourism festival industry. Effective integration of innovative digital technologies in tourism festivals in Asia is anticipated to create a unique leisure experience, particularly in a unique form of festivals known as ‘Smart Tourism Festivals'. Besides sustainability, these highly impact on the key experience outcomes such as satisfaction and memorability of the festival attendees. The COVID-19 pandemic has given momentum to the current technological application processes in various film, music, culture, sport, art and other related carnivals and festivals in the tourism industry especially amongst the leading Asian economies such as China, South Korea, Japan, Malaysia, India, Singapore, Bangladesh, Hong Kong and Thailand among others. This paper uses existing studies to provide a theoretical discussion of tourism festivals in the Asian context, areas of impact of digital technologies on festivals, emergence of smart tourism festivals, the underlying challenges and opportunities. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Key supply chain strategies for post-COVID-19 recovery: evidence from an Indian smart furniture industry

PurposeSmart furniture is an essential part of research that has been designed to best complement easy and safe human interaction. The purpose of smart furniture is to save the space of the house and make the products unique, awesome and safe, functional, strong and also make it works better so the people can live better with it. This research aims to explore the key supply chain strategies implemented by the Indian smart furniture industry to reduce the impact of a post-COVID-19 pandemic.Design/methodology/approachThis work utilized a case study and conducted semi-structured interviews with the top leadership of the smart furniture manufacturing industry to explore key supply chain strategies to reduce the influence of the post-COVID-19 pandemic. Additionally, key supply chain strategies have been analyzed using a multi-criteria decision-making technique known as grey relational analysis (GRA) to determine their ranking significance in the smart furniture industry.FindingsThe results of this study discovered that "Inventory-Categorization” is essential in ensuring business continuity during the COVID-19 pandemic and helps reduce the amount of stock they have on hand. It enhanced the opportunity for employees to properly focus on their work and an opportunity for better work-life balance. The results of the study can also help supply chain stakeholders in their establishment of critical strategies.Research limitations/implicationsThe implications of this research work help the Indian furniture industry to make supply chain investment decisions that benefit the organization to sustain itself.Originality/valueThis is the first study to explore key supply chain strategies for the post-COVID-19 era. This work will assist managers and practitioners in helping the organization decide which supply chain strategies are more critical to the betterment of the organization.

Smart-thing design by children at a distance: How to engage them and make them learn

In recent years, research in Child-Computer Interaction has shifted the focus from design with children, giving them a voice in the design process, to design by children to bring child participants different benefits, such as engagement and learning. However, design workshops, encompassing different stages, are challenging in terms of engagement and learning, e.g., they require prolonged commitment and concentration. They are potentially more challenging when held at a distance, as in recent years due to the COVID-19 pandemic. This paper explores at-a-distance smart-thing design by children, how it can engage different children and support their learning in programming. The paper reports a series of design workshops with 20 children, aged from 8 to 16 years old, all held at a distance. They were all organised with the DigiSNaP design framework and toolkit. The first workshop enabled children to explore what smart things are, to start ideating their own smart things and to scaffold their programming. The other workshops enabled children to evolve their own smart-thing ideas and programs. Data were gathered in relation to children's engagement and learning from different sources. Results are promising for future editions of smart-thing design at a distance or in a hybrid modality. They are discussed along with guidelines for smart-thing design by children at a distance. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Nanomaterial-based smart coatings for antibacterial, antifungal, and antiviral activities

Infectious diseases caused by different pathogens (parasites, protozoa, bacteria, viruses, and fungi) have affected the world at various times in the form of epidemics and pandemics. The coronavirus has also directly affected the world's economy and public health. Various drugs such as antibiotics, antimicrobials, antifungals, and antivirals have been investigated to combat these diseases. However, these fatal infections are still a major concern because of their transmission through contaminated surfaces, human-to-human contact, airborne diffusion, and microbial resistance. Therefore, considerable efforts are required to suppress the transmission of these pathogens. Smart coatings are able to sense their environment and adapt their properties according to the stimulus. Furthermore, various parameters of coating technology can be controlled on a molecular level to influence the morphology. Nanomaterial (NM)-based smart coatings are 99.99% effective against bacteria, viruses, and fungi because of the unique properties of NMs involved. Moreover, NM-based smart coatings are 1000-fold more efficient than traditional coating technologies. Besides their antifungal, antiviral, and antibacterial application, they are anticorrosive and self-cleaning. This chapter summarizes various NM-based smart coatings (organic, inorganic, and carbon) implemented in antibacterial, antifungal, and antiviral applications. Furthermore, the application of these coatings in various fields and their associated challenges will be discussed. © 2023 Elsevier Inc. All rights reserved.

Mobile Intellectual Property Marketplace Model for Commercialization of Intellectual Property Rights

This study discusses the development of the intellectual property (IP) marketplace model based on mobile location-aware computing. Referring to statistics released by the Directorate General of Intellectual Property, there has been a growth in the number of intellectual property rights (IPR) applications in recent years, even during the Covid-19 pandemic. On the other hand, after IPR protection, the commercialization of IPR is one of the pillars of the IP system. Nevertheless, research institutions such as LIPI/BRIN indicate that the potential for commercializing IPR is still low. Furthermore, the opportunity is that cellular networks have covered almost all parts of Indonesia, and there has been significant growth in smartphone users. The method utilized in this research is prototyping. This research results from an IP marketplace model based on mobile location-aware computing in Indonesia. Using the smartphone user's location, contextual IPR information from the user's location related to IPR will enter their smartphone. The experimental results indicate that the application can display a list of IPR information according to the smartphone user's location. Furthermore, the search feature can forage IPR listing information based on user queries. © 2022 IEEE.

Nanoparticles as an exotic antibacterial, antifungal, and antiviral agents

Globally, concerns regarding the COVID-19 pandemic its prevention have become important. Because of COVID-19 and other microbial diseases, enhance research work has emerged revealing new antimicrobial and antiviral materials and techniques. Tremendous growth in nanotechnology has opened up the door to fabricating numerous nanomaterials. These nanomaterials are employed as antimicrobial and antiviral agents for various applications with 99.99% effectiveness compared with conventional techniques. Nanoparticles possess unique physicochemical characteristics for multiple applications. This chapter details the use of nanoparticles for antifungal, antimicrobial, and antiviral applications. It describes various kinds of nanoparticles, such as nanometals, metal oxides, polymeric nanomaterials, and carbon-based nanomaterials. © 2023 Elsevier Inc. All rights reserved.

The Detection of Abnormal Behavior in Healthcare IoT Using IDS, CNN, and SVM

Health care is always a top priority, and that has not changed no matter how far we have come in terms of technology. Since the coronavirus epidemic broke out, almost every country has made health care a top priority. Therefore, the best way to deal with the coronavirus pandemic and other urgent health problems is through the use of IoHT. The tremendous growth of IoT devices and networks especially in the healthcare domain generates massive amounts of data, necessitating careful authentication and security. Other domains include agriculture, smart homes, industry, etc. These massive data streams can be evaluated to determine undesirable patterns. It has the potential to reduce functional risks, avoid problems that are not visible, and eliminate system downtime. Past systematic and comprehensive reviews have significantly aided the field of cybersecurity. However, this research focuses on IoT issues relating to the medical or healthcare domain, using the systematic literature review method. The current literature in health care is not enough to analyze the anomaly of IoHT. This research has revealed that fact. In our subsequent work, we will discuss the architecture of IoHT and use AI techniques such as CNN and SVM to detect intrusions in IoHT. In the interest of advancing scientific knowledge, this study identifies and suggests potential new lines of inquiry that may be pursued in this area of study. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.