Model of an intelligent smart home system based on ambient intelligence and user profiling

This paper introduces a new approach to building an intelligent smart home. The main goal is to leverage a modern, flexible, smart home by employing concepts and technologies of IoT, ambient intelligence, user profiling, and multimedia. The model combines these elements to develop not only an effective platform but also a rich, personalized and unique experience for the smart home users. By using ambient intelligence to gather and analyze the environmental data and combine them with user profiles, the system finds the right multimedia content adapted to the user’s needs, based on their habits, time of the day and the weather. Besides, the system adapts the user’s environment, as to make them feel as comfortable as possible, by adjusting the amount of light, movement of the curtains and setting the room temperature. The evaluation has shown the presented model possesses great potential for gaining new knowledge in the area of smart environment and IoT, enhancing everyday life, as well as innovations in various contexts.

[1]  Matti Hämäläinen,et al.  A web-based two-layered integration framework for smart devices , 2012, EURASIP J. Wirel. Commun. Netw..

[2]  Katja de Vries,et al.  Identity, profiling algorithms and a world of ambient intelligence , 2010, Ethics and Information Technology.

[3]  Rajinder Sandhu,et al.  A stochastic game net‐based model for effective decision‐making in smart environments , 2017, Concurr. Comput. Pract. Exp..

[4]  P. Verbeek,et al.  Ambient Intelligence and Persuasive Technology: The Blurring Boundaries Between Human and Technology , 2009, Nanoethics.

[5]  Jiebo Luo,et al.  A picture tells a thousand words - About you! User interest profiling from user generated visual content , 2015, Signal Process..

[6]  Nadjib Badache,et al.  Event-Aware Framework for Dynamic Services Discovery and Selection in the Context of Ambient Intelligence and Internet of Things , 2016, IEEE Transactions on Automation Science and Engineering.

[7]  Karthik Ram,et al.  Git can facilitate greater reproducibility and increased transparency in science , 2013, Source Code for Biology and Medicine.

[8]  Lei Chen,et al.  User behavior and user experience analysis for social network services , 2020, Wirel. Networks.

[9]  Michael Friedewald,et al.  Perspectives of ambient intelligence in the home environment , 2005, Telematics Informatics.

[10]  Jordi Mongay Batalla,et al.  Deployment of smart home management system at the edge: mechanisms and protocols , 2018, Neural Computing and Applications.

[11]  Jaime Lloret,et al.  Multimedia sensors embedded in smartphones for ambient assisted living and e-health , 2015, Multimedia Tools and Applications.

[12]  Nadine Guhr,et al.  Privacy concerns in the smart home context , 2020, SN Applied Sciences.

[13]  Jordi Forné,et al.  Measuring the privacy of user profiles in personalized information systems , 2014, Future Gener. Comput. Syst..

[14]  Karim Djouani,et al.  A Knowledge Oriented Approach for Composing Ambient Intelligence Services , 2017, ANT/SEIT.

[15]  Aleksandra Labus,et al.  A SMART HOME SYSTEM BASED ON SENSOR TECHNOLOGY , 2016 .

[16]  Tho Le-Ngoc,et al.  Capacity-maximization threshold design for wideband sensing with guaranteed minimum primary user rate , 2012, EURASIP J. Wirel. Commun. Netw..

[17]  Yousra Bendaly Hlaoui,et al.  Model driven approach for adapting user interfaces to the context of accessibility: case of visually impaired users , 2018, Journal on Multimodal User Interfaces.

[18]  Marco Brambilla,et al.  Model-driven development of user interfaces for IoT systems via domain-specific components and patterns , 2017, Journal of Internet Services and Applications.

[19]  Phillippa Carnemolla,et al.  Ageing in place and the internet of things – how smart home technologies, the built environment and caregiving intersect , 2018, Visualization in Engineering.

[20]  Chris D. Nugent,et al.  Ontological user modelling and semantic rule-based reasoning for personalisation of Help-On-Demand services in pervasive environments , 2014, Future Gener. Comput. Syst..

[21]  Stefano Chessa,et al.  Personalized real-time anomaly detection and health feedback for older adults , 2019, J. Ambient Intell. Smart Environ..

[22]  Sandeep K. Sood,et al.  Quantum Computing-Inspired Network Optimization for IoT Applications , 2020, IEEE Internet of Things Journal.

[23]  Abdelhamid Bouchachia,et al.  Online and interactive self-adaptive learning of user profile using incremental evolutionary algorithms , 2014, Evol. Syst..

[24]  Dieter Hayn,et al.  The Internet of Things for Ambient Assisted Living , 2010, 2010 Seventh International Conference on Information Technology: New Generations.

[25]  Michael Friedewald,et al.  Perspectives of ambient intelligence in the home environment , 2005 .

[26]  Cengiz Acarturk,et al.  The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults , 2018, Universal Access in the Information Society.

[27]  Ryszard Kowalczyk,et al.  Smart CloudBench—A framework for evaluating cloud infrastructure performance , 2016, Inf. Syst. Frontiers.

[28]  C. C. Sobin,et al.  A Survey on Architecture, Protocols and Challenges in IoT , 2020, Wireless Personal Communications.

[29]  Hacer Güner,et al.  The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults , 2020, Universal Access in the Information Society.

[30]  Steve Gardner,et al.  Towards ambient intelligence in assisted living: The creation of an Intelligent Home Care , 2013, 2013 Science and Information Conference.

[31]  Keith Cheverst,et al.  Exploring Issues of User Model Transparency and Proactive Behaviour in an Office Environment Control System , 2005, User Modeling and User-Adapted Interaction.

[32]  Changrui Ren,et al.  A process definition language for Internet of things , 2012, Proceedings of 2012 IEEE International Conference on Service Operations and Logistics, and Informatics.

[33]  Diane J. Cook,et al.  Author's Personal Copy Pervasive and Mobile Computing Ambient Intelligence: Technologies, Applications, and Opportunities , 2022 .

[34]  Liming Chen,et al.  A semantics-based approach to sensor data segmentation in real-time Activity Recognition , 2019, Future Gener. Comput. Syst..

[35]  Brian D. Woerner,et al.  Interference cancellation for a multicellular CDMA environment , 1996, Wirel. Pers. Commun..

[36]  Jong Hyuk Park,et al.  An enhanced security framework for home appliances in smart home , 2017, Human-centric Computing and Information Sciences.

[37]  Abdulmotaleb El-Saddik,et al.  RecAm: a collaborative context-aware framework for multimedia recommendations in an ambient intelligence environment , 2016, Multimedia Systems.

[38]  Gorka Epelde,et al.  TV as a human interface for Ambient Intelligence environments , 2011, 2011 IEEE International Conference on Multimedia and Expo.

[39]  Mohammed Atiquzzaman,et al.  Interoperability in Internet of Things: Taxonomies and Open Challenges , 2018, Mobile Networks and Applications.

[40]  Neelakantan Pattathil Chandrasekharamenon,et al.  Connectivity analysis of one-dimensional vehicular ad hoc networks in fading channels , 2012, EURASIP Journal on Wireless Communications and Networking.

[41]  Tiffany Ya Tang,et al.  The role of user mood in movie recommendations , 2010, Expert Syst. Appl..

[42]  K. Vinoth Kumar,et al.  Optimal rough fuzzy clustering for user profile ontology based web page recommendation analysis , 2019, J. Intell. Fuzzy Syst..

[43]  Chris D. Nugent,et al.  The creation of simulated activity datasets using a graphical intelligent environment simulation tool , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[44]  Paul Müller,et al.  Ambient Intelligence in Assisted Living: Enable Elderly People to Handle Future Interfaces , 2007, HCI.

[45]  Daniela Fogli,et al.  Rule-based tools for the configuration of ambient intelligence systems: a comparative user study , 2017, Multimedia Tools and Applications.

[46]  Vanjica Ratkovic-Živanovic,et al.  DESIGNING AN INTELLIGENT HOME MEDIA CENTER , 2016 .

[47]  Chris D. Nugent,et al.  Semantic Smart Homes: Towards Knowledge Rich Assisted Living Environments , 2009 .

[48]  Juan Carlos Augusto,et al.  Past, Present and Future of Ambient Intelligence and Smart Environments , 2009, ICAART.

[49]  Youngja Park,et al.  Estimating Asset Sensitivity by Profiling Users , 2013, ESORICS.

[50]  Chris D. Nugent,et al.  A user profile ontology based approach for assisting people with dementia in mobile environments , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[51]  Mohd Abdul Ahad,et al.  IoT in Education: An Integration of Educator Community to Promote Holistic Teaching and Learning , 2018, Soft Computing in Data Analytics.

[52]  Honglei Li,et al.  Learners’ continuance participation intention of collaborative group project in virtual learning environment: an extended TAM perspective , 2019, Journal of Data, Information and Management.

[53]  David D. Gill A technology education teaching framework: factors that support and hinder intermediate technology education teachers , 2018, International Journal of Technology and Design Education.

[54]  Jamie Bennett,et al.  Healthcare in the Smart Home: A Study of Past, Present and Future , 2017 .

[55]  Chris D. Nugent,et al.  Genetic algorithm and pure random search for exosensor distribution optimisation , 2012, Int. J. Bio Inspired Comput..

[56]  Luiz Fernando Capretz,et al.  Game development software engineering process life cycle: a systematic review , 2016, Journal of Software Engineering Research and Development.

[57]  Jorge Ferraz de Abreu,et al.  Survey of Catch-up TV and other time-shift services: a comprehensive analysis and taxonomy of linear and nonlinear television , 2017, Telecommun. Syst..

[58]  Vasyl Pihur,et al.  MmPalateMiRNA, an R package compendium illustrating analysis of miRNA microarray data , 2013, Source Code for Biology and Medicine.