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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.
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The development of the COVID-19 epidemic has increased the home learning time of children. More researchers began to pay attention to children's learning in home. This survey reviewed the frontier and classic cases in the field of interactive design of children's home learning in the past five years, analyzed tangible user interface, augmented reality, and multimodal interaction in human-computer interaction of children's home learning. This paper reviewed the application of interactive system in children's learning and points out its positive side in development of ability, process of learning, habits of learning, and environment of learning of children. Through analysis, we advise that it is necessary to create home learning applications, link smart home systems, and build an interactive learning environment for smart home learning environment design. Finally, we point out the technical and ethical problems existing in the current research, proposes that intelligent perception, emotion recognition, and expression technologies should be introduced in the future, and looks forward to the development of this field. © 2023 Institute of Computing Technology. All rights reserved.
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As more homes become digitally connected the use of assistive technologies to support the operation in the home environment especially when one thinks of the elderly and the sick, our research shows that there is a gap in the literature with respect to the measure of the effectiveness of the use of these assistive technologies to support the home as a smart home. We conduct quantitative usability experiments supported by a conceptual human interaction framework to assess this effectiveness. We conduct as proof of concept these experiments with the use of a Google mini automated assistant and an internet ready light bulb sensor , to determine the responsiveness to the human voice, at different location proximities around the home, and the correctness to these responses to qualify the effectiveness argument. In this study the authors use their primary residence amidst the COVID19 pandemic to demonstrate the type of concerns. Our explicit contributions in this study are (i) A systematic review of the literature in this area (ii) the design of the smart home network environment with the google mini assistant and light ulb sensor that supports the human voice interactions (iii) Identify a suitable conceptual human interaction framework to support the use of the smart devices connected within the home users environment to support our experiments (iv) Provide critical case evaluation of the measure of effectiveness of the usability experiments supported by this conceptual framework. © 2023 IEEE.
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A smart home is a component of the Internet of Things (IoT) technology implementations that help people with their daily activities. To link devices to the Internet of Things, a variety of communication methods can be used. Impairments restrict the activities that disabled people can participate in. This paper proposes an automation system that enables disabled people to control televisions (TVs), lights, and fans, any other electrical devices at home, using just voice commands without moving. The Google Assistant feature for mobile phones is used to achieve voice recognition on electronic components. This system also contains the concept of human temperature measurement where the temperature sensor, fixed to the door, checks the temperature of the person and opens when it is normal. This prevents the user from getting infected by the illness, keeping in mind the present situation of covid19. © 2023 IEEE.
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Over the past two years, the world has witnessed one of the worst pandemics due to the outbreak of coronavirus (covid19), which has infected hundreds of millions and claimed the lives of millions across the globe. If we have learned anything from this pandemic, it is that the actual healthcare systems are unreliable under situations of enormous pressure. Accordingly, the present investigation tackles smart healthcare paradigm as a solution to transform the classical healthcare model into a sustainable one. Therefore, this paper reviews the most advances on remote healthcare monitoring technologies and introduces a novel smart home architecture combined with cloud computing and machine learning to create a sustainable solution for healthcare. Furthermore, a case study of a patient with heart disease is suggested to highlight the importance of using machine learning to automate medical monitoring at home. Additionally, an investigation of human behavior using neural network transformers is suggested as a perspective of the research in hand to examine patients' activities at home using surveillance camera thus constructing a resilient remote healthcare model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Many researchers have studied non-expert users' perspectives of cyber security and privacy aspects of computing devices at home, but their studies are mostly small-scale empirical studies based on online surveys and interviews and limited to one or a few specific types of devices, such as smart speakers. This paper reports our work on an online social media analysis of a large-scale Twitter dataset, covering cyber security and privacy aspects of many different types of computing devices discussed by non-expert users in the real world. We developed two new machine learning based classifiers to automatically create the Twitter dataset with 435,207 tweets posted by 337,604 non-expert users in January and February of 2019, 2020 and 2021. We analyzed the dataset using both quantitative (topic modeling and sentiment analysis) and qualitative analysis methods, leading to various previously unknown findings. For instance, we observed a sharp (more than doubled) increase of non-expert users' tweets on cyber security and privacy during the pandemic in 2021, compare to in the pre-COVID years (2019 and 2020). Our analysis revealed a diverse range of topics discussed by non-expert users, including VPNs, Wi-Fi, smartphones, laptops, smart home devices, financial security, help-seeking, and roles of different stakeholders. Overall negative sentiment was observed across almost all topics in all the three years. Our results indicate the multi-faceted nature of non-expert users' perspectives on cyber security and privacy and call for more holistic, comprehensive and nuanced research on their perspectives. © 2022
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Purpose: The coronavirus disease 2019 (COVID-19) pandemic has had a big impact on organisations globally, leaving organisations with no choice but to adapt to the new reality of remote work to ensure business continuity. Such an unexpected reality created the conditions for testing new applications of smart home technology whilst working from home. Given the potential implications of such applications to improve the working environment, and a lack of research on that front, this paper pursued two objectives. First, the paper explored the impact of smart home applications by examining the factors that could contribute to perceived productivity and well-being whilst working from home. Second, the study investigated the role of productivity and well-being in motivating the intention of remote workers to use smart home technologies in a home-work environment in the future. Design/methodology/approach: The study adopted a cross-sectional research design. For data collection, 528 smart home users working from home during the pandemic were recruited. Collected data were analysed using a structural equation modelling approach. Findings: The results of the research confirmed that perceived productivity is dependent on service relevance, perceived usefulness, innovativeness, hedonic beliefs and control over environmental conditions. Perceived well-being correlates with task-technology fit, service relevance, perceived usefulness, perceived ease of use, attitude to smart homes, innovativeness, hedonic beliefs and control over environmental conditions. Intention to work from a smart home-office in the future is dependent on perceived well-being. Originality/value: The findings of the research contribute to the organisational and smart home literature, by providing missing evidence about the implications of the application of smart home technologies for employees' perceived productivity and well-being. The paper considers the conditions that facilitate better outcomes during remote work and could potentially be used to improve the work environment in offices after the pandemic. Also, the findings inform smart home developers about the features of technology which could improve the developers' application in contexts beyond home settings. © 2023, Emerald Publishing Limited.
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In IoT (Internet of Things), the concept of a Smart City integrates technologies and physical devices in various fields of deployment. One such instance is logistics. With the increasing popularity and need for online shopping, the e-commerce sector is growing-which goes hand in hand with the logistics industry. The logistics industry keeps growing and is gaining more and more importance-and so do the delivery solutions in the last-mile part of the logistics chain. The last-mile delivery offers a lot of possibilities for new and complexly integrated smart solutions. We propose a new solution for smart delivery services on the last mile. We call it a Smart Post Box. This concept combines various elements and creates a multi-purpose smart city solution that can be easily integrated into different systems. It introduces new ways to receive and send packages, integrates as a part of a smart household, sends notifications, and can be used to collect valuable data. During the current coronavirus outbreak, this solution would prove to be useful in reducing interpersonal contact and thus help eliminate the transfer of the disease. Our calculations show great potential for such innovation. © 2022 IEEE.
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As the advancement in technology continues to increase, systems also need to be upgraded to meet new trends and solve developing problems. Existing systems of home automation generally focus on energy management, security, and comfort. These smart homes would be more efficient if they can also perform health diagnoses. In this paper, a cost-effective IoT-based home automation system that performs the function of energy conservation, smart security, and disease detection is designed. The system uses the NodeMCU ESP8266 IoT board with its in-built Wi-Fi shield, eliminating the need to acquire a separate Wi-Fi module. The NodeMCU is interfaced with the user's android device where the connected loads on the relay modules are controlled thus enabling the system to control home appliances via an android application. The ESP8266 is also connected to a PIR sensor that checks for motion and triggers an alarm when motion is detected and connected to a contactless temperature sensor that measures the body temperature of anyone and sends the readings to the display while also triggering an alarm if the temperature is above normal indicating the sign of illness or diseases such as coronavirus, high fever, influenza. This paper presents a design of a simple system that not only assists the user to control his home appliances, conserve energy, and improve home security but also helps to protect the user from allowing covid-19-infected persons into their home. © 2022 IEEE.
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This paper presents a cost-effective and flexible electronic textile sensor with high sensitivity and fast response and demonstrates its versatile applications, including real-time measurements of finger kinematics, phonation, cough patterns, as well as subtle muscle movements (i.e., eye reflex). The sensor can discriminate between speech and cough patterns, thereby expanding its applications to COVID-19 detection, speech rehabilitation training, and human/machine interactions. A combination of different sensor data is essential to acquire clinically significant information. Therefore, a sensor array is interfaced with the LoRa communication protocol to establish an Internet of Things (IoT)-based electronic textile framework. The IoT integration allows remote monitoring of body kinematics and physiological parameters. Therefore, the proposed IoT-based framework holds the potential to provide real-time and continuous health monitoring to allow immediate intervention during this pandemic. © 2022 IEEE.
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Remote health care is currently one of the most promising solutions to ensure a high level of treatment outcome, cost-efficiency and sustainability of the healthcare systems worldwide. Even though research on remote health care can be traced back to the early days of the Internet, the recent COVID-19 has necessitated further improvement in existing health care systems with invigorated research on remote health care technologies. In this article we delve into the state-of-the-art research in latest technologies and technological paradigms that play a vital role in enabling the next generation remote health care and assisted living. First the need of using the latest technological developments in the domain of remote health care is briefly discussed. Then the most important technologies and technological paradigms that are crucial in enabling remote health care and assisted living are emphasised. Henceforth, a detailed survey of existing technologies, potential challenges in those technologies, and possible solutions is conducted. Finally, missing research gaps and important future research directions in each enabling technology are brought forth to motivate further research in remote health care.
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The demand for energy sources such as electricity is increasing as the population is increasing, which results in high billing costs and more energy consumption. More factors are resulting from these issues. For example, the decreased awareness from residents about how to save energy, especially kids and elderly people who forget about turning off home appliances and lights when they are not needed to be on. HARMS provide a smart solution through the concept of machine learning (ML) and recommendations, it will monitor power consumption, show recommendations and control home appliances based on the resident's behaviors, when they are willing to turn on the room light or any other home appliance and when to turn them off in order to enhance energy saving. HARMS will also track the inhabitant's usual and unusual behavior to take an action. We must note that due to this exceptional situation (Covid-19 Pandemic), HARMS may be done either using actual hardware, simulation, or both. The hardware parts will consist of microcomputer, motion, light, and current transformer sensors. The software parts will consist of a control system that collects data from sensors and monitors the power consumption, a database to store the collected data, appropriate algorithms for the recommender system, and an android application to interact with the residents. Regarding the simulation will consist of a web-based application to represent the home environment and the appliances, including the control and the recommender systems. This project will experiment at the College of Computer Sciences and Information Technology (CCSIT) at King Faisal University (KFU). © 2022 IEEE.
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The Internet of Things (IoT) paradigm is widely seen as revolutionary in manufacturing, large-scale industries and many other aspects of our every-day life, e.g. Smart Homes and Smart Cities. In this paper we describe our learning project focused on IoT. We propose principles and contents for specifically addressing IoT in the computer science education since the beginning of technical studies, allowing students to learn computer science and engineering pillars IoT is built upon. We believe that this kind of approach could motivate students to enthusiastically embrace Information Technology and Computer Science. We implemented our learning project at the high school level, coping with the COVID-19 pandemic period. The technologies used for remote learning in that period are also described, with an emphasis on our virtual lab approach. © 2022, Springer Nature Switzerland AG.
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The COVID-19 pandemic has significantly affected people's behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre- and post-COVID-19 pandemic times. The weekend usage patterns look similar pre- and post-COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.
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With the advancement of the Internet of Things in our smart environment, smart devices are working without human intervention. So home can be converted to intelligent home automation systems to perform its computation automatically. In a pandemic situation, the majority of people have spent their maximum time at home. So indoor air quality, insider's and outsider's health monitoring has become an important issue. As respiratory diseases are the main concern for pandemics, we have to develop an intelligent home system model to monitor healthy environmental conditions for the users. This paper proposes an energy-efficient smart system model to monitor the health and environmental condition by measuring the carbon monoxide threat level that indirectly affects other atmospheric parameters. Our system alerts when the carbon monoxide level exceeds the safe level. Remote monitoring of the home and health parameters is done in real-time with the help of the system model. For this purpose, we are adopting Dempster-Shafer evidence theory as a mathematical model to aggregate the data coming from different sensors. The sensor nodes track the home and health parameters such as room temperature, humidity, carbon monoxide level, SpO2 level, body temperature, and pulse rate. The smartphone app updates the user's real-time sensor data through the display and indirectly helps to maintain the physical distance. The proposed intelligent home-health system model is compact, cost-effective, energy-efficient for the user, and is especially useful for the quarantined covid affected people in a pandemic situation. © 2022 ACM.
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Traditional home automation is inconvenient for aging people. Biometric based personalized smart phone secures smart home automation. Internet of Things (IoT) is envisioned as a promising solution in the thrusting arenas of healthcare, industries, home automation and other domains due to its significant contribution towards connectivity, security, sleek design, low power, low cost and low workforce. This has come a long way industrially and is making an impact in the domestic market after Covid-19 pandemic. Social distancing and contact less solution is the need of the hour. Life style of people has changed from home to workplace such as remote monitoring, collaborative online work-place and online classes. This has increased the economic status of the home automation products manufacturing industry. User Authenticated Smart Home Automation with Healthcare Architecture considers security along with healthcare. This takes into account IoT reusable design concept that uses in-built user specific biometrics in smart phone for secured authentication. IoT based electronics and electrical devices are remotely monitored. The user activity is monitored and archived for future retrieval. An ambient temperature is maintained to make sure that the devices are operated in near ideal circumstances to avoid thermal throttling and this extends the lifetime of the devices. Thermal throttling causes serious threats to the devices and to the human being. In the proposed User Authenticated Smart Home Automation System with Healthcare, smart home is secured using user specific biometric authentication;sanitizer is provided and temperature is measured on entry;thermal throttling due to devices is prevented by maintaining the room temperature thereby providing healthcare. © 2021 Institute of Physics Publishing. All rights reserved.
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The rapid proliferation of embedded devices has led to the growth of the Internet of Things (IoT) with applications in numerous domains such as home automation, healthcare, education and agriculture. However, many of the connected devices particularly in smart homes are the target of attacks that try to exploit security vulnerabilities such as hard-coded passwords and insecure data transfer. Recent studies show that there is a considerable surge in the number of phishing attacks targeting smart homes during the COVID-19 pandemic. Moreover, many of the existing user authentication protocols in the literature incur additional computational overhead and need to be made more resilient to smart home targeted attacks. In this paper, we propose a novel lightweight and privacy-preserving remote user authentication protocol for securing smart home applications. Our approach is based on Photo Response Non-Uniformity (PRNU) to make our protocol resilient to smart home attacks such as smartphone capture attacks and phishing attacks. In addition, the lightweight nature of our solution is suitable for deployment on heterogeneous and resource constrained IoT devices. Besides, we leverage geometric secret sharing for establishing mutual authentication among the participating entities. We validate the security of the proposed protocol using the AVISPA formal verification tool and prototype it on a Raspberry Pi to analyze the power consumption. Finally, a comparison with existing schemes reveals that our scheme incurs a 20% reduction in communication overhead on smart devices. Furthermore, our proposed scheme is usable as it absolves users from memorizing passwords and carrying smart cards. Author
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Every day there are more devices or objects that connect to the internet, these devices are found in different areas in the home, health, industry and others, this project is implemented in the internet of things for homes, it is a module called “nutrition”, the which allows you to have a record of diets provided by a nutritionist, this allows reducing costs and food waste because with the mobile application called: Mobile application for smart appliances (EInt), you can obtain the products directly from a preferred provider. Given the situation current due to the COVID-19 pandemic, exits to non-essential situations have been reduced, this prototype pretends to be a support for users when making errand purchases and avoid going out as little as possible. The analysis and design of the device contains several agents, this article describes the nutrition agent, the food ontology, its semantic network. © 2021, Springer Nature Switzerland AG.
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COVID-19 has caused disruptions in the sharing economy for both platforms and owners, who are typically micro-businesses. Lower demand and ample supply means that users have a great deal of choice. Finding ways for properties to differentiate themselves has been a pressing need. Against this background, this paper pursued two objectives: firstly to explore the perceived functional and emotional value of smart accommodation and the factors contributing to this by adopting the Theory of Consumption Values, and secondly to examine the role of perceived value in driving intention to stay in smart accommodation in the future. 430 responses were collected to analyse the relationships among antecedents, value and intention. The results showed that the functional value of smart accommodation is associated with the perception that such accommodation represents good value for the price, smart devices are useful, they can enhance control of stay experiences, and there are resources and opportunities facilitating the use of technology. Emotional value is determined by the perception that staying in smart accommodation represents sustainable behaviour, the integration of smart home technologies offers control over the stay experience, improves the entertainment experience, aesthetics and playfulness of using technology. Emotional values are inhibited by the perception of surveillance in smart accommodation. Also, the study offers evidence of the correlation of intention with functional and emotional value. The evidence contributes to the literature by explaining the potential implications of innovative technologies for business recovery in the post-pandemic reality, exploring the applications of smart technologies in delivering tourism services, and identifying the factors in the adoption of smart homes in the hospitality sector. The findings provide practical implications for facilitating the applications of innovative technology and its adoption in home and non-home environments.
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BACKGROUND: Ubiquitous, smart technology has the potential to assist humans in numerous ways, including with health and social care. COVID-19 has notably hastened the move to remotely delivering many health services. A variety of stakeholders are involved in the process of developing technology. Where stakeholders are research participants, this poses practical and ethical challenges, particularly if the research is conducted in people's homes. Researchers must observe prima facie ethical obligations linked to participants' interests in having their autonomy and privacy respected. OBJECTIVE: This study aims to explore the ethical considerations around consent, privacy, anonymization, and data sharing with participants involved in SPHERE (Sensor Platform for Healthcare in a Residential Environment), a project for developing smart technology for monitoring health behaviors at home. Participants' unique insights from being part of this unusual experiment offer valuable perspectives on how to properly approach informed consent for similar smart home research in the future. METHODS: Semistructured qualitative interviews were conducted with 7 households (16 individual participants) recruited from SPHERE. Purposive sampling was used to invite participants from a range of household types and ages. Interviews were conducted in participants' homes or on-site at the University of Bristol. Interviews were digitally recorded, transcribed verbatim, and analyzed using an inductive thematic approach. RESULTS: Four themes were identified-motivation for participating; transparency, understanding, and consent; privacy, anonymity, and data use; and trust in research. Motivations to participate in SPHERE stemmed from an altruistic desire to support research directed toward the public good. Participants were satisfied with the consent process despite reporting some difficulties-recalling and understanding the information received, the timing and amount of information provision, and sometimes finding the information to be abstract. Participants were satisfied that privacy was assured and judged that the goals of the research compensated for threats to privacy. Participants trusted SPHERE. The factors that were relevant to developing and maintaining this trust were the trustworthiness of the research team, the provision of necessary information, participants' control over their participation, and positive prior experiences of research involvement. CONCLUSIONS: This study offers valuable insights into the perspectives of participants in smart home research on important ethical considerations around consent and privacy. The findings may have practical implications for future research regarding the types of information researchers should convey, the extent to which anonymity can be assured, and the long-term duty of care owed to the participants who place trust in researchers not only on the basis of this information but also because of their institutional affiliation. This study highlights important ethical implications. Although autonomy matters, trust appears to matter the most. Therefore, researchers should be alert to the need to foster and maintain trust, particularly as failing to do so might have deleterious effects on future research.