literature review of smart home automation system

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Literature Review on Home Automation System

One of the topics which is gaining popularity is Home Automation System because of itsinnumerous advantages. Home automation refers to the monitoring and controlling of home appliances remotely. with the never-ending growth of the Internet and its applications, there is much potential and scope for remote access and control and monitoring of such network enabled appliances. This paper deals with discussion of different intelligent home automation systems and technologies from a various features standpoint. The effort targeted on the home automation concept of where the controlling and monitoring operations are expediting through smart devices. Wide-ranging home automation systems and technologies considered in review with central controller based (Arduino or Raspberry pi), cloud-based, Bluetooth-based, SMS based, ZigBee based, mobile-based, RF Module based, web based and the Internet with performance.

Related Papers

IRJET Journal

International Journal of Advance Research and Innovative Ideas in Education

Due to the proliferation of modern technology, these days, the world is increasingly experienced the use of wireless devices. The devices such as remote control and GSM phone could provide means for monitoring and controlling home appliances in a more convenient way. This project has explored the concept of home automation and ZigBee technology. A home automated system based on Arduino and ZigBee are developed which is tried to be integrated with Android application through Home Gateway for network interoperability. To show the effectiveness and feasibility of this proposed system, a remote control, indoor control and outdoor control systems have been developed and evaluated. However, integrating the system with android application remains unsuccessful

Home Automation using GSM and Arduino

Home appliances can be remotely be controlled using home automation system and makes it easily to accessed and effectively controlled. With the use of telecommunication device like mobile phone, computer and electronic technology electrical appliance can be controlled from any part of the world. The main reasons for home automation system are to make peoples’ lives easy, greater amount of energy will be saved and driven more by technology. Among others, home automation systems available are either based on Bluetooth technology, ZigBee technology, Infrared Remote (IR) controller, Radio Frequency (RF) technology. Though these systems are good, unfortunately, they can work effectively from a distance of (100 meters maximum) automation within a particular locality. This pose a big challenge/risk of electrical disaster to people outside their vicinities that mistakenly left their appliances ON/OFF, as the case may be, and could also lead to energy to wastage for appliances left connected to the mains for a period longer than required. Hence the need for effective means of remotely controlling home appliances beyond one's vicinity. This brought about the prose project for home automation using Arduino and GSM module (SIM900). The system uses SMS to send commands in order to remotely turn ON and OFF electrical devices. The system development involves the implementation of different hardware modules such as power supply, GSM, microcontroller, relays, and loads which make up the system as well as programming the system controller.

Revathi nunna95

With the increase in consumption of energy and population, there is a grave need to conserve energy in every way possible. The inability to access and control the appliances from remote locations is one of the major reasons for energy loss. A web or an android application is used by the users to give instructions to these systems. This system can make use of a host of communication methods such as Wi-Fi, GSM, Bluetooth, ZigBee. Different controlling devices and configurations can be found in existing systems. Such systems have been found already in many places for a wide variety of applications. This paper presents a survey of all such systems.

Prashant Chaudhary

Home automation trade has drawn goodish attention of researchers for quite a decade. The main attraction of any automated system is reducing human labor, effort, time and errors due to human negligence. With the development of modern technology, smart phones have become a necessity for every person on this planet. With the increase in consumption of energy and population, there is a grave need to conserve energy in every way possible. The inability to access and control the appliances from remote locations is one of the major reasons for energy loss. This paper presents a survey of all such systems.

Shanjedul Hassan

The home automation is one of the most emerging trends in modernization of home appliance control. Presently, conventional wall switches are located in different parts of the house and one has to physically go near them and press them to turn the loads on/off. It becomes very difficult for the elderly or physically handicapped people to do so. This system is designed to provide control of home appliances remote and via Bluetooth Android based Smart phone app. The proposed system does not require a dedicated server PC with respect to similar systems and offers a novel communication protocol to monitor and control the home environment with more than just the these devices can be controlled through a web application or via Bluetooth Android based Smart phone app. The proposed system does not require a dedicated server PC with respect to similar systems and offers a novel communication protocol to monitor and control the home environment with more than just the switching functionality. To demonstrate the feasibility and effectiveness of this system, devices such as light switches, temperature sensor, gas sensor and motion sensors have been integrated with the proposed home control system. This paper presents a low cost and flexible home control and environmental monitoring system.

Jatin Bajaj

The development of smart home automation system has great potential in today’s age of technology. According to the Smart Home Energy, a smart home, or smart house, is a home that incorporates advanced automation systems to provide the inhabitants with sophisticated monitoring and control over the building's functions. Such systems make use of different types of sensors to examine the environment and maintain a control over home appliances using latest communication and networking methods. The purpose of this paper is to provide information about the implementation and design of existing smart home technologies. This paper also discusses about our wireless, voice control Smart Home System that allow people control their home devices by voice command at home.

abhishek kumar

— Home automation which is playing a very vital role in modern times due to its flexibility, reliable in using at different places with high precision and in which will save money and thus time by decreasing human hardwork. General idea in automation of home shows the various quality of human being at the house. Main focus of technology is in controlling the household equipment " s like light, TV, fan, door, AC etc. automatically. In case of hazardous condition, it is useful for many old aged and handicapped persons. In Home Automation, remote, wireless controlled switches, PC, Laptop or smartphone are used for operating the appliance. In this paper we detailed a survey on home control automation using GSM and Bluetooth by considering the parameters like efficiency of working, controllers used, type of communication, the apps developed etc. A comparative analysis of home automation system is done at last.

RELATED PAPERS

5th AIAA/CEAS Aeroacoustics Conference and Exhibit

Diana Rubio

Rev. Esp. Herp

Adolfo Marco

REUNIR Revista de Administração Contabilidade e Sustentabilidade

Teresa Carneiro

Património Cultural de Gaia. Património Humano - Personalidades

ANTÓNIO CONDE

American Journal of Speech-Language Pathology

Kazuki Sekine

Ian Hardianto Siahaan

Acta Cirurgica Brasileira

Frederico Ozanan Barros Monteiro

Colloquium Mathematicum

Nakhlé Asmar

Revista Transilvană de Ştiinţe Administrative

ALEXANDRU PAVEL

Optics Express

Falk Lederer

Interactive cardiovascular and thoracic surgery

Armando Del Prete

IEEE Transactions on Automatic Control

Naser Prljača

Remote Sensing of Environment

Nicoleta Cristea

Journal of Clinical Child & Adolescent Psychology

Eduardo Cumba-Aviles

DINAMIKA KESEHATAN JURNAL KEBIDANAN DAN KEPERAWATAN

Ilma Ifadah

njjfr hggtgrf

Phycological Research

Chandan Guria

Procedia. Economics and finance

Atis Egliņš-Eglītis

npj Parkinson's Disease

Oury Monchi

Marie Ludvikova

Revista Ciencia Em Extensao

Gláucia Maria Pereira Pavarini

Heat Transfer-Asian Research

Anjanna Matta

Clinical Neurophysiology

Tomás Segura

日本薬理学会年会要旨集 =

Sachio Morimoto

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Smart home reasoning systems: a systematic literature review

• Original Research
• Published: 15 November 2019
• Volume 12 , pages 4485–4502, ( 2021 )

Cite this article

• Dagmawi Neway Mekuria   ORCID: orcid.org/0000-0003-2076-5353 1 ,
• Paolo Sernani 1 ,
• Nicola Falcionelli 1 &
• Aldo Franco Dragoni 1  

2161 Accesses

33 Citations

Explore all metrics

A smart home is a residence equipped with technologies that facilitate monitoring of residents, promote independence and increase the quality of life. In general, smart homes are used to control the operations of the home environment and, to automatically adapt it to its inhabitants’ needs. The smart home reasoning system (SHRS) is in charge of determining the automatic control and adaptation operations of the home system. Recently, there has been extensive research concerning different aspects of the SHRS. However, there is a clear lack of systematic investigation targeted at these systems. To close the gap, this paper explores the SHRS domain. For this reason, we applied the systematic literature review (SLR) method by conducting automatic and manual searches on six electronic databases, and in-depth analysis of 135 literature. From the SRL, this paper identifies about 43% of smart homes are designed to provide general home automation services. It also presents twelve major requirements of an SHRS. In addition, the study finds out that 55.5% of the research contributions in SHRS domain are conceptual and, 51.5% of them are based on symbolic artificial intelligence techniques. Further, it characterizes the usage and application trends of different reasoning techniques in smart home domain and, evaluates the major assumptions, strengths, and limitations of the proposed systems in the literature. Additionally, it discusses the challenges of reasoning in ambient assisted living environments. Finally, it underlines in the importance of utilizing hybrid reasoning approaches and the need to handle overlapping, simultaneous and conflicting multiple inhabitants’ activities and goals.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Artificial intelligence for waste management in smart cities: a review

AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems

Data Science and Analytics: An Overview from Data-Driven Smart Computing, Decision-Making and Applications Perspective

ACM End-user policy specifically prohibits automatic downloading of articles.

The set of related keywords was defined according to the reviewers’ subjective knowledge and experience on the field.

Abdeen Mustafa O (2008) Energy, environment and sustainable development. Renew Sustain Energy Rev 12(9):2265–2300

Article   Google Scholar  

Acampora G, Loia V, Vitiello A (2011) Distributing emotional services in ambient intelligence through cognitive agents. Serv Orient Comput Appl 5(1):17–35

Ahmed B, Abdelouahed G, Kazar O (2017) Semantic-based approach to context management in ubiquitous environment. Proc Comput Sci 109:592–599

Alhafidh BM, Allen W (2016) Design and simulation of a smart home managed by an intelligent self-adaptive system. Int J Eng Res Appl 6(8):64–90

Google Scholar  

Alirezaie M, Renoux J, Köckemann U, Kristoffersson A, Karlsson L, Blomqvist E, Tsiftes N, Voigt T, Loutfi A (2017) An ontology-based context-aware system for smart homes: E-care@ home. Sensors 17(7):1586

Al-Muhtadi J, Ranganathan A, Campbell R, Mickunas MD (2003) Cerberus: a context-aware security scheme for smart spaces. In: Proceedings of the first IEEE international conference on pervasive computing and communications (PerCom 2003). IEEE, pp 489–496

Alshammari N, Alshammari T, Sedky M, Champion J, Bauer C (2017) Openshs: open smart home simulator. Sensors 17(5):1003

Antunes M, Gomes D, Aguiar R (2013) Towards behaviour inference in smart environments. In: 2013 Conference on future internet communications (CFIC). IEEE, pp 1–8

Augusto JC, Liu J, McCullagh P, Wang H, Yang J-B (2008) Management of uncertainty and spatio-temporal aspects for monitoring and diagnosis in a smart home. Int J Comput Intell Syst 1(4):361–378

Brereton P, Kitchenham BA, Budgen D, Turner M, Khalil M (2007) Lessons from applying the systematic literature review process within the software engineering domain. J Syst Softw 80(4):571–583

Calvaresi D, Cesarini D, Sernani P, Marinoni M, Dragoni AF, Sturm A (2017) Exploring the ambient assisted living domain: a systematic review. J Ambient Intell Humaniz Comput 8(2):239–257

Carner P (2009) Beyond home automation: designing more effective smart home systems. In: 9th. IT & T conference, p 14

Chahuara P, Portet F, Vacher M (2017) Context-aware decision making under uncertainty for voice-based control of smart home. Expert Syst Appl 75:63–79

Chan M, Estève D, Escriba C, Campo E (2008) A review of smart homes-present state and future challenges. Comput Methods Programs Biomed 91(1):55–81

Chen L, Nugent CD, Mulvenna M, Finlay D, Hong X, Poland M (2008) A logical framework for behaviour reasoning and assistance in a smart home. Int J Assist Robot Mechatron 9(4):20–34

Chen L, Nugent C, Al-Bashrawi A (2009) Semantic data management for situation-aware assistance in ambient assisted living. In: Proceedings of the 11th international conference on information integration and web-based applications & services. ACM, pp 298–305

Chen, C, Das B, Cook DJ (2010a) A data mining framework for activity recognition in smart environments. In: 2010 Sixth international conference on intelligent environments. IEEE, pp 80–83

Chen YS, Chen IC, Chang W (2010b) Context-aware services based on OSGI for smart homes. In: 2010 3rd IEEE international conference on UBI-media computing (u-media), vol 11, p 392

Corno F, Razzak F (2012) Intelligent energy optimization for user intelligible goals in smart home environments. IEEE Trans Smart Grid 3(4):2128–2135

Dahmen J, Thomas BL, Cook DJ, Wang X (2017) Activity learning as a foundation for security monitoring in smart homes. Sensors 17(4):737

Das B, Chen C, Dasgupta N, Cook DJ, Seelye AM (2010) Automated prompting in a smart home environment. In: 2010 IEEE international conference on data mining workshops (ICDMW). IEEE, pp 1045–1052

Degeler V, Lazovik A (2013) Dynamic constraint reasoning in smart environments. In: 2013 IEEE 25th international conference on tools with artificial intelligence (ICTAI). IEEE, pp 167–174

Degeler V, Curry E (2014) Human-assisted rule satisfaction in partially observable environments. In: 2014 IEEE 11th international conference on ubiquitous intelligence and computing, IEEE 11th international conference on and autonomic and trusted computing, IEEE 14th international conference on scalable computing and communications and its associated workshops (UTC-ATC-ScalCom). IEEE, pp 171–178

Demiris G, Hensel BK (2008) Technologies for an aging society: a systematic review of “smart home” applications. Yearb Med Inform 17(01):33–40

Doebel C, Ament C (2014) Enkos—a smart home control system basing on learning classifier systems. IFAC Proc Vol 47(3):1465–1470

Falcionelli N, Sernani P, Brugués A, Mekuria DN, Calvaresi D, Schumacher M, Dragoni AF, Bromuri S (2018) Indexing the event calculus: towards practical human-readable personal health systems. Artif Intell Med 96:154–166

Gayathri KS, Easwarakumar KS (2016) Intelligent decision support system for dementia care through smart home. Proc Comput Sci 93:947–955

Gokul V, Kannan P, Kumar S, Jacob SG (2016) Deep q-learning for home automation. Int J Comput Appl 152(6):1–5

Hui TKL, Sherratt RS, Sánchez DD (2017) Major requirements for building smart homes in smart cities based on internet of things technologies. Future Gen Comput Syst 76:358–369

Jakkula V, Cook D (2011) Detecting anomalous sensor events in smart home data for enhancing the living experience. In: Workshops at the twenty-fifth AAAI conference on artificial intelligence

Kabir MH, Hoque MR, Seo H, Yang S-H (2015) Machine learning based adaptive context-aware system for smart home environment. Int J Smart Home 9(11):55–62

Kitchenham B (2004) Procedures for performing systematic reviews. Keele UK Keele Univ 33(2004):1–26

Lee H, Choi JS, Elmasri R (2009) A dynamic evidential network for multisensor context reasoning in home-based care. In: IEEE international conference on systems, man and cybernetics, 2009. SMC 2009. IEEE, pp 4994–4999

Li C, Suna L, Hua X (2012) A context-aware lighting control system for smart meeting rooms. Syst Eng Proc 4:314–323

Lim CH, Anthony P, Fan LC (2009) Applying multi-agent system in a context aware smart home. Learning 24:53–64

Liu L, Stroulia E, Nikolaidis I, Miguel-Cruz A, Rincon AR (2016) Smart homes and home health monitoring technologies for older adults: a systematic review. Int J Med Inform 91:44–59

Lu Z, Augusto J, Liu J, Wang H (2012) A linguistic truth-value temporal reasoning (ltr) system and its application to the design of an intelligent environment. Int J Comput Intell Syst 5(1):173–196

Lu C-H, Wu C-L, Weng M-Y, Chen W-C, Fu L-C (2017) Context-aware energy saving system with multiple comfort-constrained optimization in m2m-based home environment. IEEE Trans Autom Sci Eng 14(3):1400–1414

Marschollek M (2012) Decision support at home (ds@ home)-system architectures and requirements. BMC Med Inform Decis Mak 12(1):43

Mekuria DN, Sernani P, Falcionelli N, Dragoni AF (2018) Reasoning in multi-agent based smart homes: a systematic literature review. In: Proceedings of the 9th Italian ambient assisted forum. Springer

Ni Q, García Hernando AB, Pau de la Cruz I (2016) A context-aware system infrastructure for monitoring activities of daily living in smart home. J Sens 2016:9493047

Panagiotou C, Panagiotakopoulos T, Kameas A (2015) A multi: modal decision making system for an ambient assisted living environment. In: Proceedings of the 8th ACM international conference on PErvasive technologies related to assistive environments. ACM, p 44

Qela B, Mouftah HT (2012) Observe, learn, and adapt (ola)-an algorithm for energy management in smart homes using wireless sensors and artificial intelligence. IEEE Transn Smart Grid 3(4):2262–2272

Ray A, Kumar Leng Gang, McGinnity T Martin, Coleman Sonya A, Maguire Liam P (2013) Dynamically reconfigurable online self-organising fuzzy neural network with variable number of inputs for smart home application. In: IJCCI, pp 507–514

Sanchez A, Tercero R, Saldaña D, Burnell-Ball L (2009) Sdbi: an ontology based smart home lab environment. In: Proceedings WILE-8th MICAI, pp 217–226

Sernani P, Claudi A, Calvaresi P, Accattoli D, Tofani R, Dragoni AF (2014) Using 3d simulators for the ambient assisted living. In: Proceedings of the 3rd international conference on artificial intelligence and assistive medicine, vol 1213. Citeseer, pp 16–20

Si H, Kawahara Y, Morikawa H, Aoyama T (2005) A stochastic approach for creating context-aware services based on context histories in smart home. Cognit Sci Res Pap Univ Sussex CSRP 577:37

Sianaki OA, Masoum MAS (2013) A fuzzy topsis approach for home energy management in smart grid with considering householders’ preferences. In: 2013 IEEE PES innovative smart grid technologies conference (ISGT). IEEE, pp 1–6

Sukanya P, Gayathri KS (2013) An unsupervised pattern clustering approach for identifying abnormal user behaviors in smart homes. Int J Comput Sci Netw 2(3):2277–5420

Tiberghien T, Mokhtari M, Aloulou H, Biswas J (2012) Semantic reasoning in context-aware assistive environments to support ageing with dementia. In: International semantic web conference. Springer, pp 212–227

Vainio AM, Valtonen M, Vanhala J (2006) Learning and adaptive fuzzy control system for a smart home. In: Proceedings of the First International Conference on Ambient Intelligence Developments. Springer, pp 28–47

Van Solingen R (2002) The goal/question/metric approach. Encycl Softw Eng 2:578–583

Van Nguyen T, Kim JG, Choi D (2009a) Iss: the interactive smart home simulator. In: 2009 11th international conference on advanced communication technology, vol 3. IEEE, pp 1828–1833

Van Nguyen T, Woo YC, Choi D (2009b) CCBR: chaining case based reasoning in context-aware smart home. In: 2009 First asian conference on intelligent information and database systems. IEEE, pp 453–458

Van Nguyen T, Lim W, Nguyen H, Choi D, Lee C (2010) Context ontology implementation for smart home. arXiv preprint arXiv:1007.1273

Velasco JR, Marsá-Maestre I, Navarro A, López-Carmona MA, de Vicente AJ, De La Hoz E, Paricio A, Machuca M (2005) Location-aware services and interfaces in smart homes using multiagent systems. PSC 5:104–110

Velik R, Zucker G, Dietrich D (2011) Towards automation 2.0: a neurocognitive model for environment recognition, decision-making, and action execution. EURASIP J Embed Syst 2011:4

Vivekananthan C, Mishra Y, Li F (2015) Real-time price based home energy management scheduler. IEEE Trans Power Syst 30(4):2149–2159

Wilson C, Hargreaves T, Hauxwell-Baldwin R (2015) Smart homes and their users: a systematic analysis and key challenges. Pers Ubiquit Comput 19(2):463–476

Xiao B, Chen L, Liu M, Cao Y, Yang Y (2015) Design and implementation of rule-based uncertainty reasoning in smart house. In: 2015 IEEE 16th international conference on communication technology (ICCT). IEEE, pp 441–448

Xu B, Ge Y, Chen J, Chen Z, Ling Y (2012) Elderly personal safety monitoring in smart home based on host space and travelling pattern identification. Inf Technol J 11(8):1063–1069

Youngblood GM, Cook DJ, Holder LB (2005) Managing adaptive versatile environments. Pervasive Mobile Comput 1(4):373–403

Zhang S, McClean S, Scotney B, Nugent C (2008) Learning under uncertainty in smart home environments. In: Engineering in medicine and biology society, 2008. EMBS 2008. 30th Annual international conference of the IEEE. IEEE, pp 2083–2086

Zhang S, McCullagh P, Nugent C, Zheng H, Black N (2013) An ontological framework for activity monitoring and reminder reasoning in an assisted environment. J Ambient Intell Humaniz Comput 4(2):157–168

Download references

Author information

Authors and affiliations.

Università Politecnica delle Marche, Ancona, Italy

Dagmawi Neway Mekuria, Paolo Sernani, Nicola Falcionelli & Aldo Franco Dragoni

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Dagmawi Neway Mekuria .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Mekuria, D.N., Sernani, P., Falcionelli, N. et al. Smart home reasoning systems: a systematic literature review. J Ambient Intell Human Comput 12 , 4485–4502 (2021). https://doi.org/10.1007/s12652-019-01572-z

Download citation

Received : 10 December 2018

Accepted : 06 November 2019

Published : 15 November 2019

Issue Date : April 2021

DOI : https://doi.org/10.1007/s12652-019-01572-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Smart homes
• Ambient assisted living
• Ambient intelligence
• Reasoning systems
• Decision support system
• Systematic literature review
• Find a journal
• Publish with us
• Track your research

Literature Review of IoT based Home Automation System

Ieee account.

• Change Username/Password
• Update Address

Purchase Details

• Payment Options
• Order History
• View Purchased Documents

Profile Information

• Communications Preferences
• Profession and Education
• Technical Interests
• US & Canada: +1 800 678 4333
• Worldwide: +1 732 981 0060
• Contact & Support
• About IEEE Xplore
• Accessibility
• Terms of Use
• Nondiscrimination Policy
• Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2024 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.