Abstract
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.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Abreu J, Nogueira J, Becker V, Cardoso B (2017) Survey of Catch-up TV and other time-shift services: a comprehensive analysis and taxonomy of linear and nonlinear television. Telecommunn Syst 64(1):57–74
Aleem S, Capretz LF, Ahmed F (2016) Game development software engineering process life cycle: a systematic review. J Softw Eng Res Dev 4(1):6
Alhamid MF, Rawashdeh M, Dong H, Hossain MA, Alelaiwi A, El Saddik A (2016) RecAm: a collaborative context-aware framework for multimedia recommendations in an ambient intelligence environment. Multimed Syst 22(5):587–601
Augusto JC (2009) Past, present and future of ambient intelligence and smart environments. In International conference on agents and artificial intelligence (pp. 3–15). Springer
Bao R, Chen L, Cui P (2020) User behavior and user experience analysis for social network services. Wireless Netw 3:1–7
Bassi A, Horn G (2008) Internet of Things in 2020: a roadmap for the future. Eur Commission Inform Soc Med 22:97–114
Batalla JM, Gonciarz F (2019) Deployment of smart home management system at the edge: mechanisms and protocols. Neural Comput Appl 31(5):1301–1315
Bennett J, Rokas O, Chen L (2017) Healthcare in the smart home: a study of past, present and future. Sustainability 9(5):840
Bhatia M, Sood SK (2020) Quantum computing-inspired network optimization for IoT applications. IEEE Internet of Things Journal.
Bouchachia A, Lena A, Vanaret C (2014) Online and interactive self-adaptive learning of user profile using incremental evolutionary algorithms. Evolv Syst 5(3):143–157
Brambilla M, Umuhoza E, Acerbis R (2017) Model-driven development of user interfaces for IoT systems via domain-specific components and patterns. J Internet Serv Appl 8(1):14
Cabitza F, Fogli D, Lanzilotti R, Piccinno A (2017) Rule-based tools for the configuration of ambient intelligence systems: a comparative user study. Multimed Tools Appl 76(4):5221–5241
Carnemolla P (2018) Ageing in place and the internet of things–how smart home technologies, the built environment and caregiving intersect. Visualiz Eng 6(1):7
Chen L, Nugent C, Mulvenna M, Finlay D, Hong X (2009) Semantic smart homes: towards knowledge rich assisted living environments. In intelligent patient management. Springer
Chen F, Ren C, Wang Q, Shao B (2012) A process definition language for Internet of Things. In Proceedings of 2012 IEEE International Conference on Service Operations and Logistics, and Informatics (pp. 107–110). IEEE.
Cheverst K, Byun HE, Fitton D, Sas C, Kray C, Villar N (2005) Exploring issues of user model transparency and proactive behaviour in an office environment control system. User Model User-Adap Inter 15(3–4):235–273
Chhetri MB, Chichin S, Vo QB, Kowalczyk R (2016) Smart CloudBench—A framework for evaluating cloud infrastructure performance. Inf Syst Front 18(3):413–428
Cook DJ, Augusto JC, Jakkula VR (2009) Ambient intelligence: technologies, applications, and opportunities. Perv Mobile Comput 5(4):277–298
Davidovic B, Labus A (2015) A smart home system based on sensor technology. Facta Univ Series Elect Energetics 29(3):451–460
De Vries K (2010) Identity, profiling algorithms and a world of ambient intelligence. Ethics Inf Technol 12(1):71–85
Dohr A, Modre-Opsrian R, Drobics M, Hayn D, Schreier G (2010) The internet of things for ambient assisted living. In 2010 seventh international conference on information technology: new generations (pp. 804–809). IEEE.
Ducatel K, Union européenne. Technologies de la société de l’information, Union européenne. Institut d’études de prospectives technologiques, and Union européenne. Société de l’information conviviale. (2001). Scenarios for ambient intelligence in 2010.
Đurić I, Ratković-Živanović V, Labus M, Groj D, Milanović N (2015) Designing an intelligent home media center. Facta Univ Series Elect Energy 29(3):461–474
Epelde G, Valencia X, Abascal J, Díaz U, Zinnikus I, Husodo-Schulz C (2011) TV as a human interface for ambient intelligence environments. In 2011 IEEE International Conference on Multimedia and Expo (pp. 1–6). IEEE.
Friedewald M, Da Costa O, Punie Y, Alahuhta P, Heinonen S (2005) Perspectives of ambient intelligence in the home environment. Telematics Inform 22(3):221–238
Gill DD (2019) A technology education teaching framework: factors that support and hinder intermediate technology education teachers. Int J Technol Des Educ 29(4):669–684
Guhr N, Werth O, Blacha PPH, Breitner MH (2020) Privacy concerns in the smart home context. SN Appl Sci 2(2):247
Guner H, Acarturk C (2020) The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults. Univ Access Inf Soc 19(2):311–330
Hlaoui YB, Zouhaier L, Ayed LB (2019) Model driven approach for adapting user interfaces to the context of accessibility: case of visually impaired users. J Multimodal User Interf 13(4):293–320
Kang WM, Moon SY, Park JH (2017) An enhanced security framework for home appliances in smart home. Hum-centric Comput Inform Sci 7(1):6
Kleinberger T, Becker M, Ras E, Holzinger A, Müller P (2007) Ambient intelligence in assisted living: enable elderly people to handle future interfaces. In International conference on universal access in human-computer interaction (pp. 103–112). Springer.
Li H, Yu J (2020) Learners’ continuance participation intention of collaborative group project in virtual learning environment: an extended TAM perspective. J Data Inform Manag 2(1):39–53
Mohanty SN, Rejina Parvin J, Vinoth Kumar K, Ramya KC, Sheeba Rani S, Lakshmanaprabu SK (2019) Optimal rough fuzzy clustering for user profile ontology based Web page recommendation analysis. J Intell Fuzzy Syst 37(1):205–216
Mowafey, S., Gardner, S. (2013, October). Towards ambient intelligence in assisted living: the creation of an Intelligent Home Care. In 2013 Science and Information Conference (pp. 51–60). IEEE.
Noura M, Atiquzzaman M, Gaedke M (2019) Interoperability in internet of things: taxonomies and open challenges. Mobile Netw Appl 24(3):796–809
Park Y, Gates C, Gates SC (2013) Estimating asset sensitivity by profiling users. In European Symposium on Research in Computer Security (pp. 94–110). Springer.
Parra L, Sendra S, Jiménez JM, Lloret J (2016) Multimedia sensors embedded in smartphones for ambient assisted living and e-health. Multimed Tools Appl 75(21):13271–13297
Parra-Arnau J, Rebollo-Monedero D, Forné J (2014) Measuring the privacy of user profiles in personalized information systems. Futur Gener Comput Syst 33:53–63
Parvin P, Chessa S, Kaptein M, Paternò F (2019) Personalized real-time anomaly detection and health feedback for older adults. J Ambient Intell Smart Environ 11(5):453–469
Poland MP, Nugent CD, Wang H, Chen L (2012) Genetic algorithm and pure random search for exosensor distribution optimisation. Internat J Bio-Inspired Comput 4(6):359–372
Ram K (2013) Git can facilitate greater reproducibility and increased transparency in science. Source Code Biol Med 8(1):1–8
Sandhu R, Sood SK (2017) A stochastic game net-based model for effective decision-making in smart environments. Concurr Comput Pract Exp 29(20):e3843
Singh M, Mehrotra M (2016) Bridging the gap between users and recommender systems: a change in perspective to user profiling. in intelligent systems technologies and applications. Springer, Cham
Skillen KL, Chen L, Nugent CD, Donnelly MP, Solheim I (2012) A user profile ontology based approach for assisting people with dementia in mobile environments. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 6390–6393). IEEE.
Skillen KL, Chen L, Nugent CD, Donnelly MP, Burns W, Solheim I (2014) Ontological user modelling and semantic rule-based reasoning for personalisation of Help-On-Demand services in pervasive environments. Futur Gener Comput Syst 34:97–109
Sobin CC (2020) A survey on architecture, protocols and challenges in IoT. Wireless Personal Commun 3:1–47
Synnott J, Chen L, Nugent CD, Moore G (2014) The creation of simulated activity datasets using a graphical intelligent environment simulation tool. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 4143–4146). IEEE.
Toudji D, Hilia M, Djouani K, Chibani A (2017) A knowledge oriented approach for composing ambient intelligence services. Proc Comput Sci 109:584–591
Triboan D, Chen L, Chen F, Wang Z (2019) A semantics-based approach to sensor data segmentation in real-time activity recognition. Futur Gener Comput Syst 93:224–236
Tripathi G, Ahad MA (2019) IoT in education: an integration of educator community to promote holistic teaching and learning. In soft computing in data analytics. Springer, pp 675–683
Verbeek PP (2009) Ambient intelligence and persuasive technology: the blurring boundaries between human and technology. Nanoethics 3(3):231
Winoto P, Tang TY (2010) The role of user mood in movie recommendations. Expert Syst Appl 37(8):6086–6092
Wu Z, Itälä T, Tang T, Zhang C, Ji Y, Hämäläinen M, Liu Y (2012) A web-based two-layered integration framework for smart devices. EURASIP J Wirel Commun Netw 2012(1):1–12
Wylde MA (1998) Consumer knowledge of home modifications. Technol Disabil 8(1–2):51–68
Yachir A, Amirat Y, Chibani A, Badache N (2015) Event-aware framework for dynamic services discovery and selection in the context of ambient intelligence and Internet of Things. IEEE Trans Autom Sci Eng 13(1):85–102
You Q, Bhatia S, Luo J (2016) A picture tells a thousand words—about you! User interest profiling from user generated visual content. Signal Proc 124:45–53
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Đuric, I., Barac, D., Bogdanovic, Z. et al. Model of an intelligent smart home system based on ambient intelligence and user profiling. J Ambient Intell Human Comput 14, 5137–5149 (2023). https://doi.org/10.1007/s12652-021-03081-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-021-03081-4