Search Results (1,064)

The increasing elderly population presents major challenges to traditional healthcare due to the need for continuous care, a shortage of skilled professionals, and increasing medical costs. To address this, smart elderly care homes where multiple residents live with the support of caregivers and IoT-based assistive technologies have emerged as a promising solution. For their effective operation, a reliable high speed network like 5G is essential, along with intelligent resource allocation to ensure efficient service delivery. This study proposes a deep reinforcement learning (DRL)-based resource management framework for smart elderly homes, formulated as a Markov decision process. The framework dynamically allocates computing and network resources in response to real-time application demands and system constraints. We implement and compare two DRL algorithms, emphasizing their strengths in optimizing edge utilization and throughput. System performance is evaluated across balanced, high-demand, and resource-constrained scenarios. The results demonstrate that the proposed DRL approach effectively learns adaptive resource management policies, making it a promising solution for next-generation intelligent elderly care environments. Full article

Integration of IoT and predictive modeling is critical for optimizing microclimate management in urban-agglomeration vertical farming. In this study, we present a hybrid digital twin approach that combines a physical microclimate model with a distributed IoT monitoring system to simulate and control the phytotron environment. A set of heat- and mass-balance equations governing the dynamics of temperature, humidity, and transpiration was implemented and parameterized using a genetic algorithm (GA)—an evolutionary optimization method—with real-time data collected over three intervals (72 h, 90 h, and 110 h) from LoRaWAN sensors (temperature, humidity, CO₂) and Wi-Fi-connected power meters managed by Home Assistant. The optimized model achieved mean temperature deviations ≤ 0.1 °C, relative humidity errors ≤ 2%, and overall energy consumption accuracy of 99.5% compared to measured values. The digital twin reliably tracked daily climate fluctuations and system energy use, confirming the accuracy of the hybrid approach. These results demonstrate that the proposed framework effectively integrates theoretical models with IoT-derived data to deliver precise environmental control and energy-use optimization in vertical farming, while also laying the groundwork for scalable digital twins in controlled-environment agriculture. Full article

Background and Objectives: Osteoarthritis (OA) is a chronic, degenerative joint disease. The main symptoms include pain that can cause loss of function and stiffness, as well as swelling, reduced range of motion, crepitus, joint deformity, and muscle weakness. It leads to irreversible structural changes, that in advanced stages can require surgical interventions. The aim of this review was to summarize the current literature about the role of virtual reality (VR), exergames and digital technologies in patients with knee osteoarthritis before or after total knee arthroplasty, to understand if it is possible to prevent and reduce the symptoms and if these new technologies are more effective than conventional rehabilitation therapies. Materials and Methods: We conducted a systematic search of PubMed, Cochrane Library, Scopus, and PEDro from inception to November 2024. The review adhered to the PRISMA 2020 guidelines, and the protocol was prospectively registered in PROSPERO (registration number: CRD42024541890). We included randomized controlled trials (RCTs) enrolling participants aged 60 years or older, in which VR or telerehabilitation programs were compared with conventional rehabilitation approaches. Eligible studies had to report at least one of the following outcomes: pain, functionality, stability, or adherence. Two independent reviewers screened titles and abstracts, assessed full-text eligibility, extracted data, and evaluated the risk of bias using the Cochrane Risk of Bias 2 (RoB 2) tool. Results: Fourteen randomized controlled trails (RCTs) (1123 participants; mean age 68.2 years) were included. VR and telerehabilitation generally outperformed conventional rehabilitation for pain (8/13 studies, −0.9 to −2.3 VAS points) and functionality (7/13 studies, WOMAC improvement 8–15%, TUG −1.2 to −2.8 s). Compliance was higher in most technology-assisted programs (6/7 studies, 70–100% adherence). Stability outcomes were less consistent, with only 1/4 studies showing clear benefit. One study favored conventional rehabilitation for functionality. Overall risk of bias was low-to-moderate, with heterogeneity mainly driven by intervention duration, platform type, and supervision level. Conclusions: Structured telerehabilitation, non-immersive VR, and interactive online exercise programs, especially those offering real-time feedback, show comparable or superior benefits to conventional rehabilitation in older adults with knee OA or after TKA, particularly for pain reduction, functional gains, and adherence. These approaches enhance accessibility and home-based care, supporting their integration into clinical practice when in-person therapy is limited. Full article

Physical rehabilitation is crucial for injury recovery, offering pain relief and faster healing. However, traditional methods rely heavily on in-person professional feedback, which can be time-consuming, expensive, and prone to human error, limiting accessibility and effectiveness. As a result, patients are often encouraged to perform exercises at home; however, due to the lack of professional guidance, motivation dwindles and adherence becomes a challenge. To address this, this paper proposes a smartphone-based solution that enables patients to receive exercise feedback independently. This paper reviews current Computer Vision systems for assessing rehabilitation exercises and introduces an intelligent system designed to assist patients in their recovery. Our proposed system uses motion tracking based on Computer Vision, analyzing videos recorded with a smartphone. With accessibility as a priority, the system is evaluated against the advanced Qualysis Motion Capture System using a dataset labeled by expert physicians. The framework focuses on human pose detection and movement quality assessment, aiming to reduce recovery times, minimize human error, and make rehabilitation more accessible. This proof-of-concept study was conducted as a pilot evaluation involving 15 participants, consistent with earlier work in the field, and serves to assess feasibility before scaling to larger datasets. This innovative approach has the potential to transform rehabilitation, providing accurate feedback and support to patients without the need for in-person supervision or specialized equipment. Full article

In light of mounting concerns regarding community safety, this study undertakes a comprehensive examination of the role of convenience stores in Taiwan as pivotal conduits for social safety. Through a meticulous analysis of the extant literature and informal conversational interview conducted in both urban and rural settings, this study elucidates the manner in which these commercial establishments have assumed a pivotal role in enhancing the social safety net within local communities. The findings of this study demonstrate that convenience stores have been instrumental in providing frontline assistance during emergencies and natural disasters, thereby fostering a sense of community cohesion through their provision of essential day-to-day services. Moreover, this study underscores the manner in which the inherent characteristics of convenience stores contribute to the sustainability of communities. For instance, the promotion of environmental practices and the reduction of travel-related carbon emissions enhance not only the resilience of communities but also of local spaces. Moreover, the employment strategy of having convenience stores in local areas has a beneficial effect on the local economy and local employment levels. Convenience stores provide employment opportunities close to home, which in turn enhances residents’ safety and economic stability. These findings suggest that convenience stores have untapped potential for community safety and development. The contribution of this study is to highlight the multiple roles of convenience stores through empirical research and to provide a reference for policymakers to better integrate the positive characteristics of retail networks into the social security system. Full article

Patterns of family caregiving of older adults have been identified based on aspects such as care-related tasks and intensity and are associated with caregiver well-being. A gap remains, however, in understanding how individual-, relational-, and cultural-level factors concurrently inform caregiving groups within multicultural families. In this study, we identified caregiving patterns among Mexican American individuals aiding older adults by drawing from a variety of care recipient and caregiver characteristics. We also assessed relationships between established subgroups and perceived caregiver stress. Using data from the 2016 Hispanic Established Populations for the Epidemiological Study of the Elderly (Caregiver supplement, Wave 9, N = 460), we performed latent class analysis to determine caregiving subgroups from 8 indicator variables representing patient needs, family characteristics, and caregiver health and support. Findings identified four caregiving subgroups that varied based on older adults’ care needs and caregivers’ family status, nativity, and health. Results from multivariable linear regression indicated that caregivers from the Moderate Burden/Non-cohabitating group perceived significantly less stress than those in the Elevated Burden & Health Risk group. In conclusion, we demonstrated how multi-level factors shape caregiving patterns, which can inform support efforts for multicultural families. Full article

The aging population in Europe and other developed regions is accelerating the demand for adaptable domestic environments that support independent living and care at home. In this context, ontologies offer a promising approach to represent and manage knowledge about built environments, smart technologies, and user needs—especially within Ambient Assisted Living (AAL) systems. This paper presents a systematic literature review examining the role of ontologies in the reconfiguration of domestic living spaces, with a focus on their application in design processes and decision support systems. Following the PRISMA methodology, 14 relevant works published between 2000 and 2025 were identified and analyzed. The review explores key aspects such as ontology conceptualization, reuse, engineering methodologies, integration with CAD systems, and validation practices. The results show that research on this topic is fragmented yet growing, with the first contribution dated 2005 and peaks in 2016, 2018, and 2024. Most works (11) were conference papers, with Europe leading the contributions, particularly Italy. Half of the reviewed ontologies were developed “from scratch”, while the rest relied on conceptualizations such as BIM. Ontology reuse was inconsistent: only 50% of works reused existing models (e.g., SAREF, SOSA, BOT, ifcOWL), and few adopted Ontology Design Patterns. While 11 works followed ontology engineering methodologies—mostly custom or established methods such as Methontology or NeOn—stakeholder collaboration was reported in less than 36% of cases. Validation practices were weak: only six studies presented use cases or demonstrators. Integration with CAD systems remains at a prototypical stage, primarily through semantic enrichment and SWRL-based reasoning layers. Remaining gaps include poor ontology accessibility (few provide URLs or W3IDs), limited FAIR compliance, and scarce modeling of end-user needs, despite their relevance for AAL solutions. The review highlights opportunities for collaborative, human-centered ontology development aligned with architectural and medical standards to enable scalable, interoperable, and user-driven reconfiguration of domestic environments. Full article

Background/Objective: The global acceleration of population aging presents profound challenges to the physical, psychological, and social well-being of older adults. As traditional exercise programs face limitations in accessibility, personalization, and sustained social support, there is a critical need for innovative, inclusive, and community-integrated digital movement solutions. This study aimed to develop and evaluate Movement Poomasi, a hybrid digital healthcare application designed to promote physical activity, improve digital accessibility, and strengthen social connectedness among older adults. Methods: From March 2023 to November 2023, Movement Poomasi was developed through an iterative user-centered design process involving domain experts in physical therapy and sports psychology. In this study, the term UI/UX—short for user interface and user experience—refers to the overall design and interaction framework of the application, encompassing visual layout, navigation flow, accessibility features, and user engagement optimization tailored to older adults’ sensory, cognitive, and motor characteristics. The application integrates adaptive exercise modules, senior-optimized UI/UX, voice-assisted navigation, and peer-interaction features to enable both home-based and in-person movement engagement. A two-phase usability validation was conducted. A 4-week pilot test with 15 older adults assessed the prototype, followed by a formal 6-week study with 50 participants (≥65 years), stratified by digital literacy and activity background. Quantitative metrics—movement completion rates, session duration, and engagement with social features—were analyzed alongside semi-structured interviews. Statistical analysis included ANOVA and regression to examine usability and engagement outcomes. The application has continued iterative testing and refinement until May 2025, and it is scheduled for re-launch under the name Wello! in August 2025. Results: Post-implementation UI refinements significantly increased navigation success rates (from 68% to 87%, p = 0.042). ANOVA revealed that movement selection and peer-interaction tasks posed greater cognitive load (p < 0.01). A strong positive correlation was found between digital literacy and task performance (r = 0.68, p < 0.05). Weekly participation increased by 38%, with 81% of participants reporting enhanced social connectedness through group challenges and hybrid peer-led meetups. Despite high satisfaction scores (mean 4.6 ± 0.4), usability challenges remained among low-literacy users, indicating the need for further interface simplification. Conclusions: The findings underscore the potential of hybrid digital platforms tailored to older adults’ physical, cognitive, and social needs. Movement Poomasi demonstrates scalable feasibility and contributes to reducing the digital divide while fostering active aging. Future directions include AI-assisted onboarding, adaptive tutorials, and expanded integration with community care ecosystems to enhance long-term engagement and inclusivity. Full article

Industry Revolution Five (Industry 5.0) will shift the focus away from technology and rely more on to the collaboration between humans and AI-powered robots. This approach emphasizes a more human-centric perspective, enhanced resilience, optimized workplace processes, and a stronger commitment to sustainability. The humanoid robot market has experienced substantial growth, fueled by technological advancements and the increasing need for automation in industries such as service, customer support, and education. However, challenges like high costs, complex maintenance, and societal concerns about job displacement remain. Despite these issues, the market is expected to continue expanding, supported by innovations that enhance both accessibility and performance. Therefore, this article proposes the design and implementation of low-cost, remotely controlled humanoid robots via a mobile application for home-assistant applications. The humanoid robot boasts an advanced mechanical structure, high-performance actuators, and an array of sensors that empower it to execute a wide range of tasks with human-like dexterity and mobility. Incorporating sophisticated control algorithms and a user-friendly Graphical User Interface (GUI) provides precise and stable robot operation and control. Through an in-house developed code, our research contributes to the growing field of humanoid robotics and underscores the significance of advanced control systems in fully harnessing the capabilities of these human-like machines. The implications of our findings extend to the future development and deployment of humanoid robots across various industries and societal contexts, making this an ideal area for students and researchers to explore innovative solutions. Full article

The absence of parental presence has a direct impact on the emotional stability and social routines of children, especially during extended periods of separation from their family environment, as in the case of daycare centers, hospitals, or when they remain alone at home. At the same time, the technology currently available to provide emotional support in these contexts remains limited. In response to the growing need for emotional support and companionship in child care, this project proposes the development of a multi-platform software architecture based on artificial intelligence (AI), designed to be integrated into humanoid robots that assist children between the ages of 6 and 14. The system enables daily verbal and non-verbal interactions intended to foster a sense of presence and personalized connection through conversations, games, and empathetic gestures. Built on the Robot Operating System (ROS), the software incorporates modular components for voice command processing, real-time facial expression generation, and joint movement control. These modules allow the robot to hold natural conversations, display dynamic facial expressions on its LCD (Liquid Crystal Display) screen, and synchronize gestures with spoken responses. Additionally, a graphical interface enhances the coherence between dialogue and movement, thereby improving the quality of human–robot interaction. Initial evaluations conducted in controlled environments assessed the system’s fluency, responsiveness, and expressive behavior. Subsequently, it was implemented in a pediatric hospital in Guayaquil, Ecuador, where it accompanied children during their recovery. It was observed that this type of artificial intelligence-based software, can significantly enhance the experience of children, opening promising opportunities for its application in clinical, educational, recreational, and other child-centered settings. Full article

Background: Assistance dogs can support children with autism by improving emotional regulation and social functioning, but access is limited. The Family Dog Service was developed to help families of autistic children gain similar benefits through companion dogs. It offers tailored support for selecting, training, and integrating a dog into the home. This study explored parent perspectives on the service and perceived impacts of companion dogs. Methods: A cross-sectional online survey was conducted among UK residents who attended Family Dog Service workshops. The survey included demographic data, mental health and wellbeing measures, and questions about human–animal interactions. Quantitative data were analysed descriptively; qualitative responses underwent thematic analysis. Results: Of 118 participants, 101 (85.6%) owned a dog, while 17 (14.4%) were considering acquisition. Most owners reported improvements in their child’s mood (75.2%; n = 76) and reduced anxiety-related behaviours (70.3%, n = 71) following dog acquisition. Nearly half (49.5%, n = 50) rated the child–dog relationship as ‘very’ or ‘extremely’ positive within the first month, increasing to 86.1% (n = 87) by the time of data collection. Families also reported enhanced dynamics and reduced caregiver stress. Despite some challenges, the service was valued for its autism-specific guidance and ongoing support. Conclusions: The Family Dog Service may offer a practical, accessible alternative to assistance dogs, supporting autistic children’s wellbeing and strengthening family relationships through positive interactions between children and their dogs. Full article

The Internet of Things (IoT) has emerged as a transformative technology in managing Alzheimer’s Disease (AD), offering novel solutions for early diagnosis, continuous patient monitoring, and assistive care. This review presents a comprehensive analysis of IoT-enabled systems tailored to AD care, focusing on wearable biosensors, cognitive monitoring tools, smart home automation, and Artificial Intelligence (AI)-driven analytics. A systematic literature survey was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify, screen, and synthesize 236 relevant studies primarily published between 2020 and 2025 across IEEE Xplore, PubMed, Scopus and Web of Science. The inclusion criteria targeted peer-reviewed articles that proposed or evaluated IoT-based solutions for AD detection, progression monitoring, or patient assistance. Key findings highlight the effectiveness of the IoT in detecting behavioral and cognitive changes, enhancing safety through real-time alerts, and improving patient autonomy. The review also explores integration challenges such as data privacy, system interoperability, and clinical adoption. The study reveals critical gaps in real-world deployment, clinical validation, and ethical integration of IoT-based systems for Alzheimer’s care. This study aims to serve as a definitive reference for researchers, clinicians, and developers working at the intersection of the IoT and neurodegenerative healthcare. Full article

Background/Objectives: Post-stroke cognitive impairment significantly impacts long-term functional outcomes, particularly in instrumental activities of daily living (IADLs). Working memory training (WMT) has emerged as a potential cognitive rehabilitation strategy; however, its transfer to real-world functionality remains unclear. This study evaluated whether adaptive computerized WMT enhances IADLs performance compared to a non-adaptive control condition in chronic stroke survivors. Methods: A single-blind, randomized controlled trial was conducted with 50 adults aged 50–79 years, ≥12 months post-ischemic stroke, and diagnosed with a mild neurocognitive disorder. Participants were randomized to adaptive WMT or non-adaptive cognitive training, each completing 25 home-based sessions over 12 weeks via a standardized online platform. Primary outcomes included the Lawton and Brody IADL Scale and the Working Memory Questionnaire (WMQ); secondary outcomes included the Working Memory Index (WMI) from the WAIS-IV. Analyses included frequentist and Bayesian methods. Results: Both groups showed significant pre–post improvements in IADL independence and WMI (p < 0.05; BF₁₀ > 10), with no significant between-group differences on overall IADL outcomes. The adaptive WMT group demonstrated specific gains in WMQ—Storing (p = 0.033; BF₁₀ = 3.83), while the control group improved in WMQ—Attention and IADL—Assistance Required (p = 0.004–0.035; BF₁₀ > 6). Bayesian ANOVA indicated that these effects were primarily driven by the interventions, with minimal influence from depressive symptoms or global cognition. Conclusions: Adaptive WMT yielded domain-specific cognitive benefits but did not enhance IADL performance beyond non-adaptive training. These findings highlight the limited far transfer of WMT and the importance of designing ecologically valid, multimodal rehabilitation strategies post-stroke. Full article

This study offers a detailed environmental, energy, and economic evaluation of thermal modernisation options for an existing single-family home in southern Poland. A total of 24 variants, combining different heat sources (solid fuel, biomass, natural gas, and heat pumps) with various levels of building insulation, were analysed using energy performance certification methods. Results show that, from an energy perspective, the most advantageous scenarios are those utilising brine-to-water or air-to-water heat pumps supported by photovoltaic systems, reaching final energy demands as low as 43.5 kWh/m²year and primary energy demands of 41.1 kWh/m²year. Biomass boilers coupled with solar collectors delivered the highest renewable energy share (up to 99.2%); however, they resulted in less notable reductions in primary energy. Environmentally, all heat pump options removed local particulate emissions, with CO₂ reductions of up to 87.5% compared to the baseline; biomass systems attained 100% CO₂ reduction owing to renewable fuels. Economically, biomass boilers had the lowest unit energy production costs, while PV-assisted heat pumps faced the highest overall costs despite their superior environmental benefits. The findings highlight the trade-offs between ecological advantages, energy efficiency, and investment costs, offering a decision-making framework for the modernisation of sustainable residential heating systems. Full article

Background/Objectives: Maintaining proper oral hygiene is particularly challenging for individuals with autism spectrum disorder (ASD) due to sensory sensitivities, communication difficulties, and anxiety. Traditional oral hygiene education methods may be ineffective for this population, thereby necessitating innovative solutions. This study evaluates the effectiveness of a virtual reality (VR)-based educational program in improving home oral hygiene practices among children and adolescents with ASD. Methods: Sixty-four children with ASD (Level 1) were recruited and divided into two groups. Group 1 received traditional oral hygiene education, while Group 2 used a VR-based intervention featuring a virtual domestic bathroom with an avatar demonstrating proper brushing and flossing techniques. The intervention lasted eight weeks, with two one-hour sessions per week. The oral health assessment tool (OHAT) was used to evaluate oral hygiene status before and after the intervention. An unpaired t-test compared outcomes between groups. Results: Both groups showed improvements in oral hygiene, but the VR intervention group exhibited a significantly greater reduction in OHAT scores compared to the traditional education group (p < 0.001) due to a greater improvement in oral health. The VR-based approach enhanced engagement and adherence to oral hygiene routines, particularly benefiting children with ASD who struggle with conventional methods. Conclusions: VR-based education appears to be a promising tool for improving oral hygiene habits in children with ASD by providing an interactive and immersive learning experience. Future research should explore long-term adherence and the broader application of VR in healthcare education. Full article