Smart Home Services Research Articles

Pelayanan Holistik Rumah Cerdas Di Desa Tamanrejo, Kecamatan Limbangan, Kabupaten Kendal

Evangelism through holistic smart home services is very effective. Because in the process children are blessed and parents are also blessed. The Smart House in Tamanrejo Village in December 2023-February 2024 involves more than 10 members from STT Christ Alfa Omega Semarang. Coordinated by one person to organize the teaching planning. Before the implementation began, one of the representatives met with the head of the local RT to coordinate with the residents regarding the implementation of the smart home. Then after it is agreed. The coordinator divides tasks for the teaching team in teaching. In teaching in a smart home, the place used is one of the homes of residents who are willing to use it. It was agreed that the study house would be held once a week on Fridays at 16.00-17.00 WIB. In implementing the learning house, the teaching team provides teaching in accordance with the curriculum that has been created. Then after carrying out these activities, the teaching team also visited the children's parents. In this case, pre-evangelism can be carried out through curriculum studies in the home learning about character building. Apart from that, through visits to the families of the children being taught.

Modelling eco-friendly smart home appliances’ adoption intention from the perspective of residents: a comparative analysis of PLS-SEM and fsQCA

PurposeThis research aims to explore the factors influencing the adoption intention of eco-friendly smart home appliances among residents in densely populated urban areas of a developing country.Design/methodology/approachA quantitative research approach was employed to gather data from 348 respondents through purposive sampling. A comparative analysis strategy was then utilized to investigate the adoption of eco-friendly smart home appliances, combining both linear (PLS-SEM) and non-linear (fsQCA) approaches.FindingsThe results obtained from PLS-SEM highlight that performance expectancy, facilitating conditions, hedonic motivation, price value, and environmental knowledge significantly influence the adoption intention of eco-friendly smart home appliances. However, the findings suggest that effort expectancy, social influence, and habit are not significantly associated with customers' intention to adopt eco-friendly smart home appliances. On the other hand, the fsQCA results identified eight configurations of antecedents, offering valuable insights into interpreting the complex combined causal relationships among these factors that can generate (each combination) the adoption intention of eco-friendly smart home appliances among densely populated city dwellers.Research limitations/implicationsThis study offers crucial marketing insights for various stakeholders, including homeowners, technology developers and manufacturers, smart home service providers, real estate developers, and government entities. The findings provide guidance on how these stakeholders can effectively encourage customers to adopt eco-friendly smart home appliances, aligning with future environmental sustainability demands. The research implications underscore the significance of exploring the antecedents that influence customers' adoption intention of eco-friendly technologies, contributing to the attainment of future sustainability goals.Originality/valueThe environmental sustainability of smart homes, particularly in densely populated city settings in developing countries, has received limited attention in previous studies. Therefore, this study aims to address the pressing issue of global warming and make a meaningful contribution to future sustainability goals related to smart housing technologies. Therefore, this study employs a comprehensive approach, combining both PLS-SEM (linear) and fsQCA (non-linear) techniques to provide a more thorough examination of the factors influencing the adoption of environmentally sustainable smart home appliances.

A living lab to develop smart home services for the residential welfare of older adults

Owing to the decline in the physical and social functions of older adults, the residential environment substantially impacts the psychological and emotional stability and life satisfaction for older adults. Recently, there has been a growing interest in providing residential welfare services related to the health and independent living of the older adults. The primary objective of this research was to identify the needs and perceptions of older adults regarding smart home services and associated sensors and evaluate the indoor environment conditions of older adults through a living lab. Survey results indicate that older adults felt the burden of electricity bills in summer and winter and had relatively high safety-related smart home service needs. Focus group interviews with the participants in the living lab confirmed that older adults positively perceived the benefits and privacy of the living-lab sensors. In addition, the analysis of indoor environment data over one year from a case study household showed that approximately 66.4 % during the winter season and 13.1 % during the summer season have fallen within the neutral thermal comfort range according to the proposed approach (i.e., predicted mean vote (PMV) calculated using heart rate). This study adopted the proposed PMV method (hereafter PMV-P) that takes into account personal factors (e.g., metabolic rate of older adults that can be calculated using heart rate) and environmental factors (e.g., temperature, humidity) by using the real-time data collected from IoT (Internet of Things)-based sensors. Furthermore, this study proposed a new home energy management system (EMS) algorithm on the basis of model predictive control for reducing heating energy consumption while satisfying the thermal comfort. The new EMS was demonstrated to achieve 5–12 % heating energy savings depending on the thermal comfort preferences of occupants. Overall, the results of multidisciplinary research not only provided the preliminary evidence regarding the needs and perceptions of older adults toward IoT-based sensors but also showcased the development of IoT-based smart home service system through the living lab.

Barriers to Older Adults Adapting Smart Homes: Perceived Risk Scale Development

The 21st century has marked the dawn of an aging population. China’s aging process ranks first worldwide. The country has recognized the gravity of this demographic shift and implemented strategies to address it at the national level. A vast majority of elderly Chinese individuals (approximately 90%) aspire to age in their own homes. Smart homes, endowed with cutting-edge digital technologies, such as AI, the Internet of Things, and big data, hold vast potential for enabling this vision. However, acceptance of smart home products and services among elderly individuals in China remains low. The main reason is that the related products and services fail to effectively alleviate the perceived risk of this population in the R&D process of related products and services, and there is a lack of effective measurement methods. To holistically assess the potential obstacles faced by elderly individuals using smart home products and services, this study targeted individuals aged 45–60 years in China. This study aimed to develop a comprehensive perceived risk scale specific to smart homes for this demographic. Initially, this study identified key risk dimensions and corresponding measurement items through a rigorous literature review, user interviews, and expert consultations. Subsequently, it ensured the reliability and validity of each dimension and its corresponding observation variables through preliminary research, exploratory factor analysis, and confirmatory factor analysis. This approach allowed for a comprehensive understanding of the challenges faced by future elderly individuals when utilizing smart home products and services, thus enabling the development of more effective solutions. The scale encompassed ten factors and seventy measurement items, including Privacy and Security Risk (seven items), Physical Risk (seven items), Technological Risk (nine items), Performance Risk (seven items), Service Risk (nine items), Financial Risk (five items), Psychological Risk (seven items), Industry and Market Risk (six items), Social Support Risk (six items), and Policy and Legal risk (seven items). The measurement scale developed in this study represents a groundbreaking first attempt to create a systematic scale for assessing the perceived risks associated with smart homes for the elderly in China. It not only enables professionals, businesses, and manufacturers to avoid or reduce barriers in the R&D process of related products and services, facilitating smart home industry growth and enhancing user adoption, but also serves as a universal reference for the potential obstacles that digital technology may encounter in addressing aging-related issues, which has significant theoretical value and practical importance.

A study on smart home use intention of elderly consumers based on technology acceptance models.

Smart home devices have great potential to improve the quality of life and independence of older people, positively impacting their health, safety, and comfort. However, Chinese research in this field is still in its early stages. Therefore, more comprehensive and in-depth studies are needed to comprehend the various aspects influencing the acceptance and use of smart homes by older users. This study adopted the Technology Acceptance Model (TAM) and included perceived usefulness, perceived ease of use, usage intention, intergenerational technology support, perceived value, and perceived risk as extension variables to delve deeper into the behavioral intentions of older users in smart home services. The study used a convenience sampling method to randomly distribute 236 questionnaires among older adults over the age of 60 in the school's community and neighboring urban communities who have experience in smart home use and who can complete human-computer interactions either independently or with the help of others, mainly focusing on the four sections: user characteristics, family situation, experience of use, and usage intention. The study used structural equation modeling (SEM) and factor analysis to analyze the completion of questionnaires. Finally, we conducted a validation analysis of the rationality and scientificity of the model and derived the six dimensions of the model of the influencing factors on the use of smart home products by the elderly and the weight sizes of their corresponding 13 influencing factors. The results show that perceived usefulness and perceived ease of use have a positive effect on users' intention to use smart homes. Perceived ease of use has a positive effect on the perceived usefulness of smart homes. In addition, intergenerational technology support, perceived value, and perceived risk impact users' perceived usefulness and perceived ease of use of the smart home. This research aims to describe the factors influencing older users' willingness to use smart homes. The findings are not only significant for the elderly in China but also of broad value to other regions and countries facing similar demographic challenges. The development of smart homes not only involves the elderly but is also closely related to all segments of society. The government should increase policy support and guide more social forces to participate in the development of the smart home industry. Service providers and designers should fully understand the demand situation and user experience of target users to develop easy-to-use smart home solutions. At the same time, smart homes, as intelligent products for the elderly, need to focus not only on the basic needs of the elderly such as material life and home safety, but also on the spiritual needs of elderly users. Children or caregivers should always pay attention to the psychological state of the elderly and actively guide them to use smart homes to help them realize their self-worth. We look forward to more research focusing on this area in the future and further exploring the specific issues and solutions involved.

Exploring services in a smart city through socio-technical design principles: Revealing five tensions in a smart living context

Smart cities have been studied for many years, but smart homes and the citizens' actual living in these smart homes are less researched. We argue that for digital government research, and for governments to be successful in smart city development in practice, it is necessary not only to understand living on a societal level, but also living aspects in the narrow context of homes. Citizens populate the smart city and are the ones who are supposed to use the services provided by the government. In this article we explore and analyze digital and analogue services in smart homes developed in a new city district. We have conducted observational studies in 53 apartments during an urban living expo which we analyze by applying a set of socio-technical design principles. The research question that guides the analysis is: “What tensions between values in digital and analogue services for a smart living can be revealed by a socio-technical perspective?”. We identify five tensions between: 1) being in control and being controlled, 2) intended and undesirable use of personal data, 3) digital and analogue smartness, 4) smart home visions and practices, and 5) environmental and social sustainability. By revealing these tensions, we contribute to an understanding of the complexity of smart living. We also contribute by highlighting the importance of applying a perspective that captures both technology and citizen and user issues (i.e., social aspects) when developing services in the smart home context.

Design and Implementation of a Smart Energy Meter System using the Internet of Things

Recent advances in the Internet of Things (IoT) and cloud computing have led to the development of various smart home applications and services. In addition, with the increase in the number of home appliances, the daily electricity consumption is also increasing, which increases the need for smart energy meters and monitoring systems. The proposed smart energy meter system measures current and voltage, calculates energy consumption and other information. The system is realized using ESP32s board (combination of microcontroller and Wi-Fi module), which connects to the internet and uploads data to the cloud. ThingSpeak is used as a cloud web server, which allows any user to remotely view individual consumption figures. This paper presents the design and implementation of a household smart energy meter that can collect and store energy consumption data of household appliances and major loads. The system measures three-phase currents and voltages, calculates power consumption, transmits the data to the cloud and displays it on an OLED screen.

IoT 기술의 사회복지적 활용을 위한 서비스 러닝 프로그램 개발 및 효과 검증

Objectives This study aims to explore the meaning of service learning teaching method to specialized high school students by applying a service learning program with the subject of a related major to specialized high school stu-dents and analyzing the effect.
 Methods In this study, the PPCD (Pre Post Control Design) model was used to determine the effect of each of the experimental group and control group by performing a pre-test and comparing the results with the post-test results of the research program treatment. Therefore, an experimental group of 12 students belonging to an IoT-related autonomous club and a control group of 11 general students taking IoT-related classes were selected. The program developed and applied a service learning program using the Design Thinking methodology, which is being actively discussed in engineering education, and the program lasted about a month from September 15, 2021 to October 14, 2021.
 Results Analysis of covariance (ANCOVA) was used to minimize the effect of students' existing creative person-ality level and class satisfaction on the program outcome. After adjusting the creative personality level to 3.178 and the pre-class satisfaction to 4.0, the posterior values were derived. As a result, the creative personality level was 3.874 in the experimental group and 3.192 in the control group, and the class satisfaction was 4.33 in the ex-perimental group and 3.913 in the control group. 이Based on the results of this study, the level of creativity and class satisfaction of the experimental group to which the smart home service learning program was applied in-creased significantly. and it can be evaluated that the smart home service learning program had a positive effect on the creative personality and class satisfaction of vocational high school students.
 Conclusions The conclusions of this study are as follows. First, the smart home service learning program in this study was effective because it provided an opportunity to directly apply smart home technology rather than theory and simple practice, and continued to provide the reward of being able to help someone. Second, for effective service learning, it is necessary to first secure a pool of active institutions, and at this time, it is necessary to pro-vide detailed manuals for effective learning and service based on the principle of reciprocity. Third, the effect may vary depending on the student's interest, so it is necessary to plan and operate the program from a long-term per-spective rather than a one-off.

소셜미디어 빅데이터 분석을 통한 스마트 가전의 소비가치 분석

The purpose of this study is to analyze the consumer discourse formed about smart home appliances and derive consumption values to provide useful basic data for establishing development strategies or marketing strategies for smart home appliances in the future. As a result of the discourse analysis, 9 topics such as the design and application of easy-to-use functions of smart home appliances and differentiated smart home services that realize smart life were derived, and as a result of the analysis of consumption value types, 10 types such as functional, artificial intelligence, experiential, and eco-friendly were analyzed. As a result of the discourse analysis, it can be said that consumer value is the field in which consumers are most interested in smart home appliances, and consumer-centered consumption value analysis is judged to be a valid work for exploring the development direction of smart home appliances. In addition, when comparing the consumption value type revealed in the previous study with the analysis type of this report, the same, similar, and different types appeared among each other, confirming the difference in the perception of consumption value between researchers and consumers.

Retracted: Design of Smart Home Service Robot Based on ROS

Retracted: Design of Smart Home Service Robot Based on ROS

Smart home service terminal design for elderly families integrating the KANO model and perceptual engineering

In recent years, smart homes have gradually come into our lives and have brought many positive impacts to our lives. However, in specifically targeted application design planning, the designer community is not always able to consider and analyze every factor. This paper proposes an integrated nonlinear design that incorporates the KANO model as well as a mathematical model of sensible engineering coupled with design science. The application of different design solutions in different types of households is evaluated after dividing the different types of living of elderly households into specific situations. The results show that for elderly households of type 1 versus 4, scenario 2 generally has more accurate application feasibility compared to scenario 1. The maximum increase in application accuracy for Scenario 2 compared to Scenario 1 was 6.28%. However, the frequency of use decreased by 3.09%. And for elderly households of type 2 and 3, which tend to live alone, the feasibility of application of scenario 2 is similar or even worse than that of scenario 1. The improved Scenario 3 both have higher application feasibility than Scenarios 1 and 2 and has a more user-friendly visual aid to understand the design, which helps the elderly group to better use the smart home service terminal system.

A study on community older people's willingness to use smart home-an extended technology acceptance model with intergenerational relationships.

Despite the potential of smart home technology to promote sustainable lifestyles, the adoption rate among older adults remains relatively low. This study aims to investigate the influence of intergenerational relationships on the acceptance of smart home services among seniors. A survey was conducted among 298 older adults in China, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Ten predictor variables were examined to assess their impact on the willingness to use smart home services. Intergenerational relationships significantly influenced the utilization of smart home services among older adults. Specifically, intergenerational instrumental support had a direct positive effect on the behavioral intention to use smart homes. Additionally, intergenerational emotional and financial support affected life satisfaction, which subsequently influenced the behavioral intention to use smart homes. The assistance and guidance provided by younger generations play a crucial role in shaping the willingness of older adults to adopt smart home technology. Intergenerational support can contribute positively to enabling aging individuals to age in place through the utilization of technology.

Data-Driven Futuristic Scenarios: Smart Home Service Experience Foresight Based on Social Media Data

Exploring future scenarios can consider future generations and society from a long-term perspective. A Futures Triangle is an approach used for mapping future scenarios. In general, the Futures Triangle collects weak signals using qualitative research methods. However, collecting weak signals qualitatively is limited by its small data size and manual data analysis errors. To overcome those limitations, this study proposes the data-driven futuristic scenario approach. This approach analyzes a large number of social perceptions existing in social networks as weak signals via semantic network analysis. Using our proposed data-driven approach, researchers can quantitatively collect weak signals for a Futures Triangle. To verify the applicability of the proposed method, we conducted a case study on the Chinese smart home service experience. The dataset consists of 2421 posts containing the keyword “smart home experience” on the Chinese social media platform Weibo. Three future scenarios were constructed using the proposed method. The results demonstrate the feasibility of the proposed methodology. The data-driven futuristic scenario approach has the advantage of quantitatively analyzing a large amount of stakeholder data to provide weak signals for the Futures Triangle. We suggest that the data-driven futuristic scenario approach serves as a supplementary method, combined with the traditional Futures Triangle approach, to comprehensively explore future scenarios.

SDN-based multi-level framework for smart home services

The smart home is a field that uses smart devices and gadgets to automate tasks and operations in the house, and it is expected that this study subject will become a focal point in future civilizations. The adoption of smart home services faces significant obstacles in terms of reliability and stability. The Software Defined Networking (SDN) paradigm offers up novel approaches and trends to embrace smart technologies to tackle the issues of smart homes. To avoid accidents, we developed a vertical SDN-based multi-level structure consisting of two controllers with a parent-child connection. It enables smart homes to make optimal use of current services while also providing new services to smart homes and buildings, opening the path for future smart services. In addition, we created an Application Programming Interface (API) for the smart home to make it easier to use current services and pave the path for future smart services. We designed numerous jobs depending on their categorization to give smart services, which is beneficial for smart homes. Local topologies, cloud topologies, and cloud-local topologies have all been compared in the evaluation section. The performance of POX, NOX, and Flood Light controllers is measured using three performance metrics: mean throughput, Round-Trip Time (RTT), and packet loss across all three topologies. Our findings revealed that the cloud-local topology had the lowest packet loss ratio of 1.4%, while the local and cloud topologies had 1.9% and 2.3%, respectively.

CROSS: A framework for cyber risk optimisation in smart homes

This work introduces a decision support framework, called Cyber Risk Optimiser for Smart homeS (CROSS), which advises both smart home users and smart home service providers on how to select an optimal portfolio of cyber security controls to counteract cyber attacks in a smart home including traditional cyber attacks and adversarial machine learning attacks. CROSS is based on a multi-objective bi-level two-stage optimisation. In stage-one optimisation, the problem is modelled as a multi-leader-follower game that considers both security and economic objectives, where the provider selects a security portfolio to protect both itself and its users, while rational attackers target the weakest path. Stage-two optimisation is a Stackelberg security game that focuses on additional user security controls under the remit of smart home users. While CROSS can potentially be applied to other similar use cases, in this paper, our aim is to address threats against artificial intelligence (AI) applications as the use of AI in smart Internet of Things (IoT) devices introduces new cyber threats to home environments. Specifically, we have implemented and assessed CROSS in a smart heating use case in a prototypical AI-enabled IoT environment that combines characteristics and vulnerabilities currently present on existing commercial off-the-shelf (COTS) devices, demonstrating the selection of optimal decisions.

AutoInfer: Self-Driving Management for Resource-Efficient, SLO-Aware Machine=Learning Inference in GPU Clusters

As Internet-of-Things (IoT) keeps growing, IoT-side intelligence services, such as intelligent personal assistant, healthcare surveillance, and smart home service, offload more and more complex machine learning (ML) inference workloads to cloud clusters. GPUs have been widely adopted to accelerate the execution of these ML inference workloads. However, current cluster management systems guarantee low tail latency for ML inferences using resource over-provisioning and small batch sizes, resulting in a serious waste of GPU resources and increasing the service costs greatly. To mitigate poor GPU utilization, we present AutoInfer, a self-driving cluster management system for ML inference serving in GPU clusters, where users express only the latency and accuracy requirements for their workloads without needing to specify the model variant, GPU provisioning strategy, and batching mechanism. AutoInfer extends the matrix factorization model to automatically recommend model variants for each new incoming ML inference workload with respect to latency and accuracy requirements, by identifying similarities to previously scheduled workloads. During runtime, AutoInfer leverages online telemetry data and deep reinforcement learning to adaptively adjust the GPU allocation and batch size to account for load variations while minimizing the effects on tail latency Service Level Objectives (SLOs). Testbed experiments show that AutoInfer is able to improve the average GPU utilization by up to 77% and keep the tail latency SLO violations under 5.5%.

Security Attacks and Countermeasures in Smart Homes

The Internet of Things (IoT) application is visible in all aspects of humans’ day-to-day affairs. The demand for IoT is growing at an unprecedented rate, from wearable wristwatches to autopilot cars. The smart home has also seen significant advancements to improve the quality of lifestyle. However, the security and privacy of IoT devices have become primary concerns as data is shared among intelligent devices and over the internet in a smart home network. There are several attacks - node capturing attack, sniffing attack, malware attack, boot phase attack, etc., which are conducted by adversaries to breach the security of smart homes. The security breach has a negative impact on the tenants' privacy and prevents the availability of smart home services. This article presents smart homes' most common security attacks and mitigation techniques.

Evaluating Smart Home Services and Items: A Living Lab User Experience Study

South Korea is expected to become a super-aged society by 2025, when more than 20% of its population will be aged 65 and over. One possible solution for minimizing the socioeconomic burden posed by this aging trend is smart home technology, which can be used to support older adults’ daily routines. In this study, the aim is to suggest the direction of development on smart home technology and products to enhance our understanding of service and item needs for the optimal commercialization of smart homes for users. A living lab was set up to research the experience of using smart home technology in real environments. To obtain intuitive and specific evaluations, visitors of varying ages tested each item and living space and responded to a five-point scale questionnaire on importance (recognition) and performance (satisfaction). The recognition and satisfaction for each smart home item or service were then evaluated using basic statistical analysis, importance–performance analysis, and factor analysis using SPSS. It was determined that the importance and performance evaluations of smart home services and items differed by age group. The scores for the two categories exhibited evident similarities in the older adult group. More similarities were found in the evaluation of performance than importance across age groups. The results show that different age groups agree that the development of services/items that can constantly and automatically check residents’ health status should be prioritized.

Enhanced Crow Search with Deep Learning-Based Cyberattack Detection in SDN-IoT Environment

The paradigm shift towards the Internet of Things (IoT) phenomenon and the rise of edge-computing models provide massive potential for several upcoming IoT applications like smart grid, smart energy, smart home, smart health and smart transportation services. However, it also provides a sequence of novel cyber-security issues. Although IoT networks provide several advantages, the heterogeneous nature of the network and the wide connectivity of the devices make the network easy for cyber-attackers. Cyberattacks result in financial loss and data breaches for organizations and individuals. So, it becomes crucial to secure the IoT environment from such cyberattacks. With this motivation, the current study introduces an effectual Enhanced Crow Search Algorithm with Deep Learning-Driven Cyberattack Detection (ECSADL-CAD) model for the Software-Defined Networking (SDN)-enabled IoT environment. The presented ECSADL-CAD approach aims to identify and classify the cyberattacks in the SDN-enabled IoT environment. To attain this, the ECSADL-CAD model initially pre-processes the data. In the presented ECSADL-CAD model, the Reinforced Deep Belief Network (RDBN) model is employed for attack detection. At last, the ECSA-based hyperparameter tuning process gets executed to boost the overall classification outcomes. A series of simulations were conducted to validate the improved outcomes of the proposed ECSADL-CAD model. The experimental outcomes confirmed the superiority of the proposed ECSADL-CAD model over other existing methodologies.

A Study on the Factors Influencing the Purchase Intention of Smart Home Service Robots in the Post-COVID-19 Era

포스트 코로나 시대에 가정은 생활 방식 변화의 가장 중요한 중심 중 하나가 될 것이며, 이는 스마트 홈솔루션에 대한 사람들의 지속적인 요구를 촉진할 뿐만 아니라 사람들이 가정에서 발생하는 새로운 변화에 더 잘 적응하도록 촉진할 것이다. 홈서비스 로봇의 가치를 점차 인식하게 됐지만 현재 소비자 관점에서 스마트 홈서비스 로봇을 연구 대상으로 하는 실증 연구는 적다. 본 연구는 포스트 코로나 시대의 스마트 홈서비스 로봇의 구매의도의 영향 요인을 검증하기 위해 일반 중국인을 조사 대상으로 선정하고 정량적 분석 방법을 이용하여 제품특징, 오프라인 경험은 제품태도 사이에는 상당한 긍정적인 영향 관계가 있는 것을 검증하였으며, 제품 태도는 제품 특성, 오프라인 경험과 소비자의 구매의도 사이에 매개효과를 확인하였으며, 동시에 제품 태도가 구매의도에 미치는 영향을 기반으로 사회적 상호작용을 통해 제품 태도가 구매의도에 미치는 영향을 조절효과를 확인하였다. 이를 통해 기업이 소비자의 구매 결정을 보다 명확하게 이해할 수 있도록 돕고, 스마트 홈서비스 로봇 관련 기업이 의사결정 및 마케팅 홍보에 참고할 수 있도록 한다.