As discussed previously, different user context dimensions should be taken into account to expand the scope of this study. Applied the architecture and the sample implementation, we should look into different types of context data, among which, health data extracted from wearable device is the most potential resource. From this source of data, we can identify the physical state of users when they get home when they get home, if the user has done any sport activity, and how much exercise they have been doing. And these analysis will decide which state of the house should be the best fit for user comfort. Water temperature can be adjusted to better fit after-activity human body, room temperature can also be set accordingly, and possibly different than a usual state. This direction of work is slightly towards adaptive to abnormal behaviors, which is an interesting and popular research area.
Although the results of our study are positive, its scope is confined within a single-user context, which somewhat restrains the use cases. Future research has plenty of space to extend from this ground. One possible direction is to extend such principles and model to a multi-user environment. This direction poses challenging in teaching the smart home to adapt to personalized context based on their preference, in other word, to differentiate each user and react to the various context of a distinguishable subject. As already men-tioned insection 6.1, dealing with multi-user environment can be taken as the next step in expanding the system. In order to achieve this goal, we need to identify different types of user and look into research of user recognition based on personalized characteristics.
Additionally, expanding the context builder module is another possibility to continue this work, where machine learning strength can be applied to learn from user behavior and develop an informative knowledge base to improve HAS energy efficiency. From this point, our rule-based dictionary can be extended. Cooperative with more user context dimensions, the smart home system is expected to contribute significant improvements for energy efficiency.
Aipperspach, Ryan, Elliot Cohen, and John Canny (2010). “Modeling Human Behavior from Simple Sensors in the Home”. In:Pervasive6030.783, pp. 62–79.DOI:10.1007/
978-3-642-12654-3.
Balta-Ozkan, Nazmiye, Rosemary Davidson, Martha Bicket, and Lorraine Whitmarsh (Dec. 2013). “Social barriers to the adoption of smart homes”. In: Energy Policy 63, pp. 363–374.DOI:10.1016/j.enpol.2013.08.043.
Becker, Christoph et al. (2015). “Requirements: The Key to Sustainability”. In: IEEE Softw.DOI:10.1109/ms.2015.158.
Bouchard, Bruno, Sébastien Gaboury, Kévin Bouchard, and Yannick Francillette (2018).
“Modeling Human Activities Using Behaviour Trees in Smart Homes”. In:Proc. 11th PErvasive Technol. Relat. to Assist. Environ. Conf. - PETRA ’18. DOI: 10 . 1145 / 3197768.3201522.
Buckman, A H, M Mayfield, and Stephen B M Beck (2014). “Smart and Sustainable Built Environment What is a Smart Building? What is a Smart Building?” In:Smart Sustain.
Built Environ. Facil. Environ. Iss Facil.310.13, pp. 92–109.
Business Insider (2019).The Internet of Things Report. Tech. rep.
Chahuara, Pedro, François Portet, and Michel Vacher (2017). “Context-aware decision making under uncertainty for voice-based control of smart home”. In:Expert Syst. Appl.
75, pp. 63–79.DOI:10.1016/j.eswa.2017.01.014.
Chan, Marie, Eric Campo, Daniel Estève, and Jean-Yves Fourniols (2009). “Smart homes-Current features and future perspectives”. In:Maturitas64, pp. 90–97.DOI:10.1016/
j.maturitas.2009.07.014.
Chen, Liming, Chris D. Nugent, and Hui Wang (June 2012). “A Knowledge-Driven Ap-proach to Activity Recognition in Smart Homes”. In: IEEE Trans. Knowl. Data Eng.
24.6, pp. 961–974. DOI:10.1109/TKDE.2011.51.
Cook, Diane J., Aaron S. Crandall, Brian L. Thomas, and Narayanan C. Krishnan (July 2013). “CASAS: A Smart Home in a Box”. In:Computer (Long. Beach. Calif). 46.7, pp. 62–69. DOI:10.1109/MC.2012.328.
D’Souza, Michelle, Nelsha Wilfred, Rochel Pereira, Thanya Rayen, and Aparna Telgote (2018). “Home automation using Internet of Things”. In:2017 Int. Conf. Energy, Com-mun. Data Anal. Soft Comput. ICECDS 2017.DOI:10.1109/ICECDS.2017.8389498.
Demeure, Alexandre, Sybille Caffiau, Elias Elias, and Camille Roux (2015). “Building and Using Home Automation Systems: A Field Study”. In:End-User Dev. SE - 99083, pp. 125–140.DOI:10.1007/978-3-319-18425-8_9.
Duboc, Leticia et al. (June 2019). “Do we really know what we are building? Raising awareness of potential Sustainability Effects of Software Systems in Requirements En-gineering”. In:IEEE Int. Requir. Eng. Conf.IEEE Computer Society.
Fagnant, Daniel J. and Kara Kockelman (July 2015). “Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendations”. In:Transp. Res. Part A Policy Pract.77, pp. 167–181.DOI:10.1016/j.tra.2015.04.003.
Farmani, Farid, Mehdi Parvizimosaed, Hassan Monsef, and Ashkan Rahimi-Kian (2018).
“A conceptual model of a smart energy management system for a residential building equipped with CCHP system”. In: Int. J. Electr. Power Energy Syst.95, pp. 523–536.
DOI:10.1016/j.ijepes.2017.09.016.
Ford, Rebecca, Marco Pritoni, Angela Sanguinetti, and Beth Karlin (Oct. 2017). “Cate-gories and functionality of smart home technology for energy management”. In:Build.
Environ.123, pp. 543–554.DOI:10.1016/j.buildenv.2017.07.020.
Gartner (2012). Gartner’s 2012 Hype Cycle for Emerging Technologies Identifies "Tip-ping Point". Tech. rep.
GeSI (2015). “ICT Solutions for 21 st Century Challenges”. In:
Home Assistant (2019).Home Assistant Data Science.
Hong, Zheng, Pan Li, and Wang Jingxiao (2013). “Context-aware scheduling algorithm in smart home system”. In:China Commun.DOI:10.1109/CC.2013.6674219.
Klimova, Alexandra (2018). “Systematic Literature Review of Using Knowledge Man-agement Systems and Processes in Green ICT and ICT for Greening”. In: Technol.
Smart Futur. Cham: Springer International Publishing, pp. 329–344. DOI: 10.1007/
978-3-319-60137-3_16.
Kor, Ah-Lian, Eric Rondeau, Karl Andersson, Jari Porras, and Jean-Philippe Georges (2019). “Education in green ICT and control of smart systems : A first hand expe-rience from the International PERCCOM masters programme”. In: 12th IFAC Symp.
Adv. Control Educ. ACE 2019.
Korkmaz, Ilker et al. (2015). “A cloud based and Android supported scalable home au-tomation system”. In: Comput. Electr. Eng. 43, pp. 112–128. DOI: 10 . 1016 / j . compeleceng.2014.11.010.
Mainetti, Luca, Vincenzo Mighali, and Luigi Patrono (May 2015). “A location-aware ar-chitecture for heterogeneous building automation systems”. In:Proc. 2015 IFIP/IEEE Int. Symp. Integr. Netw. Manag. IM 2015. IEEE, pp. 1065–1070.DOI:10.1109/INM.
2015.7140434.
Marikyan, Davit, Savvas Papagiannidis, and Eleftherios Alamanos (2019). “A systematic review of the smart home literature: A user perspective”. In: Technol. Forecast. Soc.
Change138.August 2018, pp. 139–154.DOI:10.1016/j.techfore.2018.08.015.
Mark (2012).Classification Algorithms in Human Activity Recognition using Smartphones Mohd. Tech. rep.
McCarthy, John (1980). “Circumscription-A form of non-monotonic reasoning”. In:Artif.
Intell. DOI:10.1016/0004-3702(80)90011-9.
Moro, Alberto and Laura Lonza (Oct. 2018). “Electricity carbon intensity in European Member States: Impacts on GHG emissions of electric vehicles”. In:Transp. Res. Part D Transp. Environ.64, pp. 5–14.DOI:10.1016/j.trd.2017.07.012.
Nicol, J. F. and M. A. Humphreys (July 2002). “Adaptive thermal comfort and sustainable thermal standards for buildings”. In: Energy Build. Vol. 34. 6. Elsevier, pp. 563–572.
DOI:10.1016/S0378-7788(02)00006-3.
Oasis Energy (n.d.).APPLIANCE ELECTRICITY USAGE. Tech. rep.
Poulson, David, C A Nicolle, and Magdalen Galley (2002).Review of the current status of research on smart homes and other domestic assistive technologies in support of the TAHI trials.
Principi, Emanuele, Stefano Squartini, Roberto Bonfigli, Giacomo Ferroni, and Francesco Piazza (2015). “An integrated system for voice command recognition and emergency detection based on audio signals”. In: Expert Syst. Appl. 42.13, pp. 5668–5683. DOI: 10.1016/j.eswa.2015.02.036.
Reinisch, Christian, Mario J. Kofler, Félix Iglesias, and Wolfgang Kastner (2011). “Thinkhome energy efficiency in future smart homes”. In:Eurasip J. Embed. Syst.2011.1, p. 104617.
DOI:10.1155/2011/104617.
Risteska Stojkoska, Biljana L. and Kire V. Trivodaliev (2017). “A review of Internet of Things for smart home: Challenges and solutions”. In:J. Clean. Prod.140, pp. 1454–
1464. DOI:10.1016/j.jclepro.2016.10.006.
Roy, Patrice C., Bruno Bouchard, Abdenour Bouzouane, and Sylvain Giroux (2010).
“Possibilistic Activity Recognition in Smart Homes”. In:ICAART 2010 - 2nd Int. Conf.
Agents Artif. Intell.Pp. 1–6.
Sangogboye, Fisayo Caleb, Olaf Droegehorn, and Jari Porras (2016). “Analyzing the Payback Time of Investments in Building Automation”. In: Sustain. Ecol. Eng. Des.
Pp. 367–381.DOI:10.1007/978-3-319-32646-7_25.
Sarmento, Henrique Reinaldo et al. (2017). “Improving Energy Efficiency of Residential Building Automation System Considering User contexts enriched by Smartphones -German Use case -”. In:
Serral, Estefanía, Pedro Valderas, and Vicente Pelechano (2010). “Supporting runtime system evolution to adapt to user behaviour”. In: Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics)6051 LNCS, pp. 378–392.
DOI:10.1007/978-3-642-13094-6_30.
Shin, Jungwoo, Yuri Park, and Daeho Lee (2018). “Who will be smart home users? An analysis of adoption and diffusion of smart homes”. In:Technol. Forecast. Soc. Change 134, pp. 246–253.DOI:10.1016/j.techfore.2018.06.029.
Shuhaiber, Ahmed and Ibrahim Mashal (2019). “Understanding users’ acceptance of smart homes”. In: Technol. Soc. March 2018, pp. 1–9. DOI:10 . 1016 / j . techsoc . 2019.01.003.
Sri Harsha, S. L.S., S. Chakrapani Reddy, and S. Prince Mary (2017). “Enhanced home automation system using Internet of Things”. In:Proc. Int. Conf. IoT Soc. Mobile, Anal.
Cloud, I-SMAC 2017, pp. 89–93.DOI:10.1109/I-SMAC.2017.8058302.
Suzuki, Takuji and Miwako Doi (2001). “LifeMinder”. In:LifeMinder an evidence-based wearable Healthc. Assist.New York, New York, USA: CHI ’01 Extended Abstracts on Human Factors in Computing Systems Press, pp. 127–128. DOI: 10.1145/634067.
634144.
Toschi, Guilherme Mussi, Leonardo Barreto Campos, and Carlos Eduardo Cugnasca (2017).
“Home automation networks: A survey”. In:Comput. Stand. Interfaces50, pp. 42–54.
DOI:10.1016/j.csi.2016.08.008.
Vainio, Antti-Matti, Harri Pensas, and Jukka Vanhala (2014). “Context recognition in a smart home”. In:Proc. 18th Int. Acad. MindTrek Conf. Media Business, Manag. Con-tent Serv. - Acad. ’14, pp. 167–170.DOI:10.1145/2676467.2676479.
Vaishnavi, Vijay, Bill Kuechler, and Stacie Petter (n.d.).DESIGN SCIENCE RESEARCH IN INFORMATION SYSTEMS. Tech. rep.
Vázquez, Félix Iglesias, Wolfgang Kastner, and Mario Kofler (Jan. 2013). “Holistic smart homes for air quality and thermal comfort”. In: Intell. Decis. Technol. Ed. by Ilias Maglogiannis, Lazaros Iliadis, and Harris Papadopoulos. Vol. 7. 1, pp. 23–43. DOI: 10.3233/IDT-120149.
Vázquez, Felix Iglesias et al. (Sept. 2011). “Impact of user habits in smart home control”.
In:IEEE Int. Conf. Emerg. Technol. Fact. Autom. ETFA. IEEE, pp. 1–8.DOI:10.1109/
ETFA.2011.6059104.
Villanueva, Marcel Lowell G and Prof Olaf Droegehorn (2018). “Using Gestures to In-teract with Home Automation Systems : - a Socio-Technical Study on Motion Capture Technologies for Smart Homes”. In: October.
Wigginton, Michael. (June 2013). Intelligent Skins. Routledge, p. 176. DOI: 10 . 4324 / 9780080495446.
Williams, Dorothy Giles and Earl R. Babbie (2006). “The Practice of Social Research.”
In:Contemp. Sociol.DOI:10.2307/2062956.
Yang, Heetae, Hwansoo Lee, and Hangjung Zo (Feb. 2017). “User acceptance of smart home services: an extension of the theory of planned behavior”. In: Ind. Manag. Data Syst.117.1, pp. 68–89.DOI:10.1108/IMDS-01-2016-0017.
Youngjae Kim and Dongman Lee (2008). “A personal context-aware universal remote controller for a smart home environment”. In: DOI:10.1109/icact.2006.206274.
Turn on heating at 16:30
- id: " 1 5 5 6 3 8 8 6 7 2 3 3 7 "
a l i a s : T u r n h e a t i n g / c o o l i n g on f r o m 1 6 : 3 0 t r i g g e r :
- at : " 1 6 : 3 0 : 0 0 "
p l a t f o r m : t i m e c o n d i t i o n :
- c o n d i t i o n : s t a t e
e n t i t y _ i d : c a l e n d a r . h a s s i o s t a t e : " off "
a c t i o n :
- a l i a s : " T u r n t h e r m o m o d e on "
s e r v i c e : c l i m a t e . s e t _ o p e r a t i o n _ m o d e d a t a :
e n t i t y _ i d : c l i m a t e . h va c o p e r a t i o n _ m o d e : " a u t o "
Turn off heating at 08:00
- id: " 1 5 5 6 3 8 8 6 7 2 3 3 7 "
a l i a s : T u r n h e a t i n g / c o o l i n g off f r om 0 8 : 0 0 t r i g g e r :
- at : " 1 8 : 0 0 : 0 0 "
p l a t f o r m : t i m e a c t i o n :
- a l i a s : " T u r n t h e r m o m o d e off "
s e r v i c e : c l i m a t e . s e t _ o p e r a t i o n _ m o d e d a t a :
e n t i t y _ i d : c l i m a t e . h va c o p e r a t i o n _ m o d e : " off "
Configuration Tool
Figure 22: The interface to work with Home Assistant Configuration Tool.
Figure 23:The setting of HA server and network infrastructure.