‘User-Home relationship’ regarding user experience of smart home products

Sadikoglu-Asan, Hatice

doi:10.1080/17508975.2020.1726724

Cited by 6 publications

(4 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the virtual digital museum, the online digital museum APP, which uses intelligent mobile devices as interactive terminals, can be realized by displaying high-definition zoomable collection maps, three-dimensional displays of collections, voice explanations, and other means. The research on interaction design and user experience has started late and lags in knowledge and creativity [11]. Since not much attention has been paid to interaction design and user experience, there are few professional research institutions.…”

Section: Related Workmentioning

confidence: 99%

User Experience Perspectives on the Application of Interactivity Design Based on Sensor Networks in Digital Museum Product Display

Zhang

2022

Journal of Sensors

View full text Add to dashboard Cite

This paper designs a model of interactivity design in digital museum product display, constructs a sensor network model, and tests the sensor network-based interactivity design in digital museum product display under the perspective of user experience. This paper makes a museum user experience model based on sensory, behavioral, cognitive, and emotional experiences; establishes a user experience design framework; conducts specific theoretical analysis and research from four aspects; uncovers specific factors affecting museum user experience; analyzes the impact of each experience factor on user system design and possible design entry points; and proposes corresponding user system design strategies to guide subsequent design practice sessions. This paper also completes the hardware circuit and PCB board design of the wireless sensing node based on the CC2430 chip as the core. Tomcat WEB server and J2EE-based Spring MVC Web development framework are used as the leading implementation technology to complete the functions of real-time data query, network parameter setting, and historical data storage. The ideographic practice of visual representation of the digital museum is discussed around its optical system. Knowledge-based model dominates the digital museum representation, and examining the complex constitutive processes and characteristics of images involves not only the production of discursive order but also the production of presentation contexts as well as virtual spaces, which construct a new visual presentation of digital museums. However, the virtual representation practice of digital museums still has paradoxes, the absence of the sense of experience and the flatness of the virtual space, in which the audience cannot have a visual experience under this presentation.

show abstract

Section: Related Workmentioning

confidence: 99%

User Experience Perspectives on the Application of Interactivity Design Based on Sensor Networks in Digital Museum Product Display

Zhang

2022

Journal of Sensors

View full text Add to dashboard Cite

show abstract

“…Studies show that occupancy prediction has the potential to reduce more than 60% of unnecessary building energy consumption. With the rapid improvement of machine learning (ML) and the advancement of computer vision, research on building occupancy prediction via image/video is gaining momentum as reported in several studies [3,[5][6][7][8][9]. The research techniques mainly contain two aspects: cameras at the room entrance and installed indoor cameras.…”

Section: Introductionmentioning

confidence: 99%

Multimodal Framework for Smart Building Occupancy Detection

Abuhussain,

Alotaibi,

Dodo

et al. 2024

Sustainability

View full text Add to dashboard Cite

Over the years, building appliances have become the major energy consumers to improve indoor air quality and occupants’ lifestyles. The primary energy usage in building sectors, particularly lighting, Heating, Ventilation, and Air conditioning (HVAC) equipment, is expected to double in the upcoming years due to inappropriate control operation activities. Recently, several researchers have provided an automated solution to turn HVAC and lighting on when the space is being occupied and off when the space becomes vacant. Previous studies indicate a lack of publicly accessible datasets for environmental sensing and suggest developing holistic models that detect buildings’ occupancy. Additionally, the reliability of their solutions tends to decrease as the occupancy grows in a building. Therefore, this study proposed a machine learning-based framework for smart building occupancy detection that considered the lighting parameter in addition to the HVAC parameter used in the existing studies. We employed a parametric classifier to ensure a strong correlation between the predicting parameters and the occupancy prediction model. This study uses a machine learning model that combines direct and environmental sensing techniques to obtain high-quality training data. The analysis of the experimental results shows high accuracy, precision, recall, and F1-score of the applied RF model (0.86, 0.99, 1.0, and 0.88 respectively) for occupancy prediction and substantial energy saving.

show abstract

“…“Smartness” is infectious: it is extending above and beyond specific devices, as well as contexts—including the home (Taylor et al 2007 ; Wilson et al 2015 ). Smart homes have become technologically available and feasible (De Silva et al 2012 ; Sciuto and Nacci 2014 ; Sadikoglu-Asan 2020 ), and the interest in smart homes in research and industry is growing exponentially (Solaimani et al 2013b ; Wilson et al 2015 ), yet, their appeal to the general population is limited (Taylor et al 2007 ; Marikyan et al 2019 ): while the COVID-19 pandemic might accelerate technology adaption in the home (Maalsen and Dowling 2020 ), perceived and potential benefits continue to be incongruent and adoption and diffusion rates remain low (Marikyan et al 2019 ). The “socio-economic and technological constellation” (Friedewald et al 2005 , p. 236) necessary for their success has—still—not been met.…”

Section: Introductionmentioning

confidence: 99%

“…Investigating the relationship between user and home has only just begun (p. ex. Sadikoglu-Asan 2020 ).…”

Section: Introductionmentioning

confidence: 99%

User requirements for the design of smart homes: dimensions and goals

Reisinger

Prost

Schrammel

et al. 2022

J Ambient Intell Human Comput

View full text Add to dashboard Cite

The ‘Smart Home’ is a strongly technology-driven field. While user-centered requirements have been reported for specific features, a considerable gap persists for design based on an everyday home context and the social and emotional nature of the home. To address this, we present a user-centered design process to question and expand narrow framings of energy-efficiency and smart control and consider the richness and variety of the domestic context as design space for smart homes. Our three-step investigation employs cultural probing, participatory design fiction, and focus groups to progress from the home context “as-is” towards a blending of values with technological responses. Our findings highlight the home as a complex construct imbued with organically grown practices and individual and collective needs, values, and emotions. Based on empirical, real-user data we present features and system expectations that address this multifaceted overall picture. This paper advises the design process of future smart home solutions in three facets: first, we discuss the value of the design process applied in this study and future possibilities to expand. Second, we show design dimensions, namely time, space, relations, individual factors, and values that allow design for a heterogeneity of users and situations. Third, we derive specific design goals to highlight directions of smart home system design: design for control, low effort, integration, evolvability, identity, sociability, and benefits.

show abstract

‘User-Home relationship’ regarding user experience of smart home products

Cited by 6 publications

References 31 publications

User Experience Perspectives on the Application of Interactivity Design Based on Sensor Networks in Digital Museum Product Display

User Experience Perspectives on the Application of Interactivity Design Based on Sensor Networks in Digital Museum Product Display

Multimodal Framework for Smart Building Occupancy Detection

User requirements for the design of smart homes: dimensions and goals

Contact Info

Product

Resources

About