Search Results (29)

The rapid growth of China’s aging population has made elderly care a pressing social issue. Due to an imperfect pension system, limited uptake of institutional care, and uneven regional economic development, most elderly people in China still rely on home-based care. Elderly people living at home are usually cared for by their family, partners, caregivers, or themselves. However, this often fails to meet their complex health, safety, and emotional needs. Artificial intelligence may provide promising solutions to improve home care experiences and address the multifaceted health and lifestyle challenges faced by homebound elderly people. This review explores the applications of artificial intelligence in home-based care from four main perspectives: home health care, home safety and security, smart life assistants, and psychological care and emotional support. We systematically searched PubMed, IEEE Xplore, CNKI, and Scopus databases, integrated the latest research published between 2015 and 2024, focused on peer-reviewed, practice-oriented research, and reviewed relevant technology development paths and the current status of the field. Unlike previous studies that focused on physiological monitoring, this study is the first to systematically and comprehensively evaluate the role of artificial intelligence in improving the convenience of daily life and mental health support for elderly people at home. By comprehensively reviewing and analyzing the basic principles and application background of artificial intelligence technology in this field, we summarize the current technical and ethical challenges and propose future research directions. This study aims to help readers gain a deeper understanding of the current status and emerging trends of artificial intelligence-enabled home-based elderly care, thereby providing valuable insights for continued innovation and application in this rapidly developing field. Full article

As populations age globally, governments face mounting challenges in reconfiguring healthcare and housing systems to support aging-in-place. This study offers a comparative analysis of South Korea and the United Kingdom, examining how each country integrates digital technologies, such as Artificial Intelligence (AI), telecare, and smart housing systems, into their aging strategies. South Korea employs a centralized, technology-driven approach that prioritizes the national rollout of AI-enabled smart homes and digital health infrastructure. In contrast, the UK advances a decentralized, community-based model emphasizing social housing, localized care delivery, and telecare integration. Despite these differing trajectories, both nations face shared limitations, including high implementation costs, digital literacy barriers, and concerns about data privacy. Critically, the study finds that the success of aging-in-place efforts is shaped not only by technological capacity but also by governance dynamics, political continuity, and institutional coordination. In response, the paper proposes policy recommendations alongside an ethical framework grounded in transparency, autonomy, informed consent, and equity. Sustainable aging-in-place strategies require not only innovative technologies, but also inclusive governance and ethically robust design to ensure accessibility, trust, and long-term impact. Full article

Intelligent safety and security is significant for preventing risks, ensuring information security and promoting sustainable social development, making it an indispensable part of modern society. Current research primarily focuses on the knowledge base and research hotspots in the field of intelligent safety and security. However, a comprehensive mapping of its overall knowledge structure remains lacking. A total of 1400 publications from the Web of Science Core Collection (2013–2023) are analyzed using VOSviewer and CiteSpace, through which co-occurrence analysis, keyword burst detection, and co-citation analysis are conducted. Through this approach, this analysis systematically uncovers the core themes, evolutionary trajectories, and emerging trends in intelligent safety and security research. Unlike previous bibliometric studies, this study is the first to integrate multiple visualization techniques to construct a holistic framework of the intelligent safety and security knowledge system. Additionally, it offers an in-depth analysis of key topics such as IoT security, intelligent transportation systems, smart cities, and smart grids, providing quantitative insights to guide future research directions. The results show that the most significant number of publications are from China; the top position on the list of papers published by related institutions is occupied by King Saud University from Saudi Arabia. Renewable and Sustainable Energy Reviews, Sustainable Cities and Society, and IEEE Transactions on Intelligent Transportation Systems are identified as the leading publications in this field. The decentralization of blockchain technology, the security and challenges of the Internet of Things (IoT), and research on intelligent cities and smart homes have formed the knowledge base for innovative security research. The four key directions of intelligent safety and security research mainly comprise IoT security, intelligent transportation systems, traffic safety and its far-reaching impact, and the utilization of smart grids and renewable energy. Research on IoT technology, security, and limitations is at the forefront of interest in this area. Full article

Even while living circumstances and construction techniques have generally improved, occupants of these spaces frequently feel unsatisfied with the sense of security they provide, which leads to looking for and eventually enacting ever-more-effective safety precautions. The continuous uncertainty that contemporary individuals experience, particularly with regard to their protection in places like cities, prompted the field of computing to design smart devices that attempt to reduce threats and ultimately strengthen people’s sense of protection. Intelligent apps were developed to provide protection and make a residence a smart and safe home. The proliferation of technology for smart homes necessitates the implementation of rigorous safety precautions to protect users’ personal information and avoid illegal access. The importance of establishing cyber security has been recognized by academic and business institutions all around the globe. Providing reliable computation for the Internet of Things (IoT) is also crucial. A new method for enhancing safety in smart home environments’ sustainability using IoT devices is presented in this paper, combining the Whale Optimization Algorithm (WOA) with Deep Convolutional Neural Networks (DCNNs). WOA-DCNN hybridization seeks to enhance safety measures by efficiently identifying and averting possible attacks in real time. We show how effective the proposed approach is in defending smart home systems from a range of safety risks via in-depth testing and analysis. By providing a potential path for protecting smart home surroundings in a world that is growing more linked, this research advances the state of the art in IoT security. Full article

Background: With an aging population and the continuous advancement of smart technology, the Chinese government is exploring smart elderly care models to address the challenges posed by aging. Although smart home systems are viewed as a promising solution, their adoption rate among older people remains low. Objectives: This study aimed to investigate the factors influencing the behavioral intention to use smart home systems among older people in Linyi City, Shandong Province, China. Methods: A literature review revealed a lack of quantitative research on older people’s behavioral intention toward smart home systems based on the Innovation Diffusion Theory. This study developed an extended model based on the Innovation Diffusion Theory, Technology Acceptance Model, and external variables, incorporating eight variables: intergenerational technical support, perceived cost, self-reported health conditions, compatibility, observability, trialability, perceived usefulness, perceived ease of use, and behavioral intention. Results: Analysis of 387 valid questionnaires showed that compatibility and trialability significantly and positively affect perceived ease of use, while self-reported health conditions, perceived ease of use, and perceived usefulness have significant effects on behavioral intention. In addition, perceived cost had a negative influence on behavioral intention. Contributions/Significance: These findings highlight the importance of considering these factors in the design of smart home systems to improve user experience and provide valuable practical guidance to smart home system developers, R&D institutions, and policymakers. Full article

Seniors face many challenges as they age, such as dementia, cognitive and memory disorders, vision and hearing impairment, among others. Although most of them would like to stay in their own homes, as they feel comfortable and safe, in some cases, older people are taken to special institutions, such as nursing homes. In order to provide serious and quality care to elderly people at home, continuous remote monitoring is perceived as a solution to keep them connected to healthcare service providers. The new trend in medical health services, in general, is to move from ’hospital-centric’ services to ’home-centric’ services with the aim of reducing the costs of medical treatments and improving the recovery experience of patients, among other benefits for both patients and medical centers. Smart energy data captured from electrical home appliance sensors open a new opportunity for remote healthcare monitoring, linking the patient’s health-state/health-condition with routine behaviors and activities over time. It is known that deviation from the normal routine can indicate abnormal conditions such as sleep disturbance, confusion, or memory problems. This work proposes the development and deployment of a smart energy data with activity recognition (SEDAR) system that uses machine learning (ML) techniques to identify appliance usage and behavior patterns oriented to older people living alone. The proposed system opens the door to a range of applications that go beyond healthcare, such as energy management strategies, load balancing techniques, and appliance-specific optimizations. This solution impacts on the massive adoption of telehealth in third-world economies where access to smart meters is still limited. Full article

China’s rapidly aging population and shortage of care resources have made it difficult for its traditional model to meet the home care needs of the elderly. On this premise, China is implementing home digital health interventions based on smart technology. During implementation, instead of the expected explosion in long-term adoption, there has been a large amount of abandonment. But so far, the relationship between service experience and these behaviors has been ignored. This study aims to explore the reasons for the long-term adoption or abandonment behaviors of technology by elders in the home care environment. A qualitative study was conducted based on Golant’s framework of smart technology adoption behaviors among elders. Semi-structured interviews were conducted with 26 elders who are long-term or former users of smart technology in a home care environment, and data from the interviews were analyzed using directed content analysis. This study identified three themes that influence elders’ adoption behaviors of smart technology in the home care environment, including immediate effectiveness, long-term usability, and possible collateral damage. The findings indicated that the experience of the elders is the key point that affects long-term adoption behavior. For more elders to use smart technology in the home care environment, it is necessary for the government, technology developers, and nursing institutions to further reform the existing system. Full article

A fall is one of the most devastating events that aging people can experience. Fall-related physical injuries, hospital admission, or even mortality among the elderly are all critical health issues. As the population continues to age worldwide, there is an imperative need to develop fall detection systems. We propose a system for the recognition and verification of falls based on a chest-worn wearable device, which can be used for elderly health institutions or home care. The wearable device utilizes a built-in three-axis accelerometer and gyroscope in the nine-axis inertial sensor to determine the user’s postures, such as standing, sitting, and lying down. The resultant force was obtained by calculation with three-axis acceleration. Integration of three-axis acceleration and a three-axis gyroscope can obtain a pitch angle through the gradient descent algorithm. The height value was converted from a barometer. Integration of the pitch angle with the height value can determine the behavior state including sitting down, standing up, walking, lying down, and falling. In our study, we can clearly determine the direction of the fall. Acceleration changes during the fall can determine the force of the impact. Furthermore, with the IoT (Internet of Things) and smart speakers, we can verify whether the user has fallen by asking from smart speakers. In this study, posture determination is operated directly on the wearable device through the state machine. The ability to recognize and report a fall event in real-time can help to lessen the response time of a caregiver. The family members or care provider monitor, in real-time, the user’s current posture via a mobile device app or internet webpage. All collected data supports subsequent medical evaluation and further intervention. Full article

Innovative technological solutions are required to improve patients’ quality of life and deliver suitable treatment. Healthcare workers may be able to watch patients from a distance using the Internet of Things (IoT) by using big data algorithms to analyze instrument outputs. Therefore, it is essential to gather information on use and health problems in order to improve the remedies. To ensure seamless incorporation for use in healthcare institutions, senior communities, or private homes, these technological tools must first and foremost be easy to use and implement. We provide a network cluster-based system known as smart patient room usage in order to achieve this. As a result, nursing staff or caretakers can use it efficiently and swiftly. This work focuses on the exterior unit that makes up a network cluster, a cloud storage mechanism for data processing and storage, as well as a wireless or unique radio frequency send module for data transfer. In this article, a spatio-temporal cluster mapping system is presented and described. This system creates time series data using sense data collected from various clusters. The suggested method is the ideal tool to use in a variety of circumstances to improve medical and healthcare services. The suggested model’s ability to anticipate moving behavior with high precision is its most important feature. The time series graphic displays a regular light movement that continued almost the entire night. The last 12 h’ lowest and highest moving duration numbers were roughly 40% and 50%, respectively. When there is little movement, the model assumes a normal posture. Particularly, the moving duration ranges from 7% to 14%, with an average of 7.0%. Full article

The world’s population is getting older these days. Frailty, a gerontologic health condition associated with ageing, has serious consequences. One crucial remedy for the elderly population is the development of ageing-in-place infrastructures. To better understand the market requirements for ageing housing units, the causes of downsizing and the governmental measures to ameliorate the situation, face-to-face in-depth individual and focus group interviews were conducted in this study. Elderly residents of two significant ageing-in-place institutions in Hong Kong, along with their caregivers, were interviewed. The method of methodological triangulation was used to combine interviews, records, and communication tools to increase the reliability and trustworthiness of the findings. The provision of facilities for the elderly has successfully established a pathway for creating and making housing spaces available to families who need larger homes, while the elderly typically downsize from larger homes and relieve their financial needs. It is also found that a digital divide exists; some respondents suggested that they do not know about computers and do not use smart facilities in their homes. Full article

The growing share of the population over the age of 65 is putting pressure on the social health insurance system, especially on institutions that provide long-term care services for the elderly or to people who suffer from chronic diseases or mental disabilities. This pressure can be reduced through the assisted living of the patients, based on an intelligent system for monitoring vital signs and home automation. In this regard, since 2008, the European Commission has financed the development of medical products and services through the ambient assisted living (AAL) program—Ageing Well in the Digital World. The SmartCare Project, which integrates the proposed Computer Vision solution, follows the European strategy on AAL. This paper presents an indoor human activity recognition (HAR) system based on scene understanding. The system consists of a ZED 2 stereo camera and a NVIDIA Jetson AGX processing unit. The recognition of human activity is carried out in two stages: all humans and objects in the frame are detected using a neural network, then the results are fed to a second network for the detection of interactions between humans and objects. The activity score is determined based on the human–object interaction (HOI) detections. Full article

According to the “World Population Prospects 2022” released by the United Nations in August 2022, the world will officially enter an “aging society”. In order to provide the elderly with an improved quality of daily life, “health promotion” and “prevention of disease” will be important. With respect to care of the elderly, the concepts of “therapeutic environment” and “green care” have been explored and developed. Therefore, in this study, we combine the currently popular Internet of Things (IoT) into an aquaponics system and proposes a smart green care system (SGCS). The proposed system uses face recognition technology to record the labor and rehabilitation history of the elderly, in combination with environmental data analysis, to enable automatic control decisions for equipment in conjunction with a voice control system to reduce the obstacles faced by the elderly in operating the information system. It also uses image recognition technology to monitor and notify about plant diseases and insect pests to achieve automatic management and enhance the interaction between the elderly and the SGCS through human–computer interaction. The SGCS allows the elderly to guide it to participate in appropriate activities through direct contact with the natural environment, thereby enhancing the quality of green healing life. In this study, taking long-term care institutions as an example, we verified proof of concept (PoC), proof of service (PoS), and proof of business (PoB), confirming the feasibility of the SGCS. The SGCS proposed in this study can be successfully used in long-term care institutions and various other environments, such as medical units and home care contexts. It can take full advantage of the functions associated with the concept of “healing environment” and “green care” widely recognized by users. Therefore, it can be widely used in the field of long-term care in the future. Full article

Mild cognitive impairment (MCI) may occur with old age and is associated with increased cognitive deterioration compared to what is normal. This may affect the person’s quality of life, health, and independence. In this ageing worldwide context, early diagnosis and personalized assistance for MCI therefore become crucial. This paper makes two important contributions: (1) a system (RO-SmartAgeing) to address MCI, which was developed for Romania; and (2) a set of criteria for evaluating its impact on remote health monitoring. The system aims to provide customized non-invasive remote monitoring, health assessment, and assistance for the elderly within a smart environment set up in their homes. Moreover, it includes multivariate AI-based predictive models that can detect the onset of MCI and its development towards dementia. It was built iteratively, following literature reviews and consultations with health specialists, and it is currently being tested in a simulated home environment. While its main strength is the potential to detect MCI early and follow its evolution, RO-SmartAgeing also supports elderly people in living independently, and it is safe, comfortable, low cost, and privacy protected. Moreover, it can be used by healthcare institutions to continuously monitor a patient’s vital signs, position, and activities, and to deliver reminders and alarms. Full article

The distance between home and school is crucial for children’s mobility and education equity. Compared with choice-based enrollment systems, much less attention has been given to the commuting distance to school in proximity-based systems, as if the institutional arrangement of assigning children to nearby schools can avoid the problem of long commuting distances. Using student-type smart card data, this study explored the spatial characteristics of the commuting distance to primary schools by public transport and the residence-school spatial pattern under the proximity-based system in Beijing. The relationships between long school commutes and house price/age were investigated under the context of school gentrification. For the identified primary student users, fewer than 35% of the students travelled fewer than 3 km to school, while more than 80% of students travelled long distances greater than 5 km, which indicated that the policy of “attending nearby school” did not guarantee a shorter commuting distance to school. Long distances to school greater than 5 km correlate negatively with a lower average house price/building age and fewer students. This finding verified the assumptions from China’s school gentrification that people might buy older school-district houses but live far from the school district for a new house. These findings provide a complementary view of previous survey studies and reveal the actual commuting distance by public transport for a group of primary students in a proximity-based enrollment system. Full article

Virtual assistants, deployed on smartphone and smart speaker devices, enable hands-free financial transactions by voice commands. Even though these voice transactions are frictionless for end users, they are susceptible to typical attacks to authentication protocols (e.g., replay). Using traditional knowledge-based or possession-based authentication with additional invasive interactions raises users concerns regarding security and usefulness. State-of-the-art schemes for trusted devices with physical unclonable functions (PUF) have complex enrollment processes. We propose a scheme based on a challenge response protocol with a trusted Internet of Things (IoT) autonomous device for hands-free scenarios (i.e., with no additional user interaction), integrated with smart home behavior for continuous authentication. The protocol was validated with automatic formal security analysis. A proof of concept with websockets presented an average response time of 383 ms for mutual authentication using a 6-message protocol with a simple enrollment process. We performed hands-free activity recognition of a specific user, based on smart home testbed data from a 2-month period, obtaining an accuracy of 97% and a recall of 81%. Given the data minimization privacy principle, we could reduce the total number of smart home events time series from 7 to 5. When compared with existing invasive solutions, our non-invasive mechanism contributes to the efforts to enhance the usability of financial institutions’ virtual assistants, while maintaining security and privacy. Full article