A Review of Smart Design Based on Interactive Experience in Building Systems
Abstract
:1. Introduction
2. Method
2.1. Step 1: Identifying the Research Question
2.2. Step 2: Collecting Studies
2.3. Step 3: Screening Literature
2.4. Step 4: Analyzing Literature
3. A Survey of Research on Smart Design Based on Interactive Experience
3.1. Trends
3.1.1. Publications in Years
3.1.2. Applications in Geographical Areas
3.1.3. Application Fields
3.2. Review Results
3.2.1. The Visual Interaction
3.2.2. The Voice Interaction
3.2.3. The Tactile Interaction
3.2.4. The Cognitive Interaction
3.2.5. Emotional Interaction
3.2.6. Interactive Combination
4. Conclusions
5. Future Research Suggestions and Directions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Wang, Z.; Wei, S.; Shi, L.; Liu, Z. The Analysis and Implementation of Smart Home Control System. In Proceedings of the 2009 International Conference on Information Management and Engineering, Kuala Lumpur, Malaysia, 3–5 April 2009; pp. 546–549. [Google Scholar]
- Zhu, J.; Wang, X.; Wang, P.; Wu, Z.; Kim, M.J. Integration of BIM and GIS: Geometry from IFC to shapefile using open-source technology. Autom. Constr. 2019, 102, 105–119. [Google Scholar] [CrossRef]
- Zhu, J.; Wu, P.; Chen, M.; Kim, M.J.; Wang, X.; Fang, T. Automatically Processing IFC Clipping Representation for BIM and GIS Integration at the Process Level. Appl. Sci. 2020, 10, 2009. [Google Scholar] [CrossRef] [Green Version]
- Hu, X.; Chong, H.-Y.; Wang, X. Sustainability perceptions of off-site manufacturing stakeholders in Australia. J. Clean. Prod. 2019, 227, 346–354. [Google Scholar] [CrossRef]
- White, C. Health Care Spending Growth: How Different is the United States from the rest of the OECD? Health Aff. 2007, 26, 154–161. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Carnemolla, P. Ageing in place and the internet of things—How smart home technologies, the built environment and caregiving intersect. Vis. Eng. 2018, 6, 7. [Google Scholar] [CrossRef] [Green Version]
- Shelley, M.; Krippendorff, K. Content Analysis: An Introduction to its Methodology. J. Am. Stat. Assoc. 1984, 79, 240. [Google Scholar] [CrossRef] [Green Version]
- Zhang, Y.; Ling, Z. The application of autostereoscopic display in smart home system based on mobile devices. In Proceedings of the Sixth International Conference on Graphic and Image Processing (ICGIP 2014), Beijing, China, 18 March 2015; Volume 9443. [Google Scholar]
- Kim, B.Y.; Lee, J. Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review. JMIR mHealth uHealth 2017, 5, e69. [Google Scholar] [CrossRef] [Green Version]
- Fogli, D.; Peroni, M.; Stefini, C. ImAtHome: Making trigger-action programming easy and fun. J. Vis. Lang. Comput. 2017, 42, 60–75. [Google Scholar] [CrossRef]
- Natephra, W.; Motamedi, A.; Fukuda, T.; Yabuki, N. Integrating building information modeling and virtual reality development engines for building indoor lighting design. Vis. Eng. 2017, 5. [Google Scholar] [CrossRef] [Green Version]
- Rook, K.; Witt, B.; Bailey, R.; Geigel, J.; Hu, P.; Kothari, A. A Study of User Intent in Immersive Smart Spaces. In Proceedings of the 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kyoto, Japan, 11–15 March 2019; Volume 2019, pp. 227–232. [Google Scholar]
- Ai, H.; Li, T. A smart home system based on embedded technology and face recognition technology. Intell. Autom. Soft Comput. 2016, 23, 405–418. [Google Scholar] [CrossRef]
- Mejía, D.; Kubis, T.; Klimeck, G. NemoViz: A visual interactive system for atomistic simulations design. Vis. Eng. 2018, 6, 6. [Google Scholar] [CrossRef] [Green Version]
- Wang, K.-J.; Zheng, C.Y.; Mao, Z.-H. Human-Centered, Ergonomic Wearable Device with Computer Vision Augmented Intelligence for VR Multimodal Human-Smart Home Object Interaction. In Proceedings of the 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Daegu, Korea, 11–14 March 2019; pp. 767–768. [Google Scholar]
- Jang, J.; Bednarz, T. HoloSensor for smart home, health entertainment. In ACM SIGGRAPH 2018 Appy Hour; Association for Computing Machinery: New York, NY, USA, 2018. [Google Scholar] [CrossRef]
- Caporuscio, M.; Weyns, D.; Andersson, J.; Axelsson, C.; Petersson, G. Iot-enabled physical telerehabilitation platform. In Proceedings of the 2017 IEEE International Conference on Software Architecture Workshops (ICSAW), Gothenburg, Sweden, 5–7 April 2017; pp. 112–119. [Google Scholar]
- Zhang, R.; He, S.; Yang, X.; Wang, X.; Li, K.; Huang, Q.; Yu, Z.; Zhang, X.; Tang, D.; Li, Y.; et al. An EOG-Based Human–Machine Interface to Control a Smart Home Environment for Patients with Severe Spinal Cord Injuries. IEEE Trans. Biomed. Eng. 2019, 66, 89–100. [Google Scholar] [CrossRef] [PubMed]
- Wang, K.-J.; Tung, H.-W.; Huang, Z.; Thakur, P.; Mao, Z.-H.; You, M.-X. EXGbuds: Universal wearable assistive device for disabled people to interact with the environment seamlessly. In Companion of the 2018 ACM, Proceedings of the IEEE International Conference on Human-Robot Interaction, Chicago, IL, USA, 5–8 March 2018; ACM: New York, NY, USA, 2018; pp. 369–370. [Google Scholar]
- Song, P.; Zhao, L. Research on Visible Light Communication Control System Based on Steady-State Visual Evoked Potential. In Proceedings of the 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, Hangzhou, China, 26–27 August 2015; Volume 2, pp. 284–287. [Google Scholar]
- Majaranta, P.; Laitinen, J.; Kangas, J.; Isokoski, P. Inducing gaze gestures by static illustrations. In Proceedings of the 11th ACM Symposium on Eye Tracking Research and Applications, Denver, CO, USA, 25–28 June 2019. [Google Scholar]
- Jacob, R.; Stellmach, S. What you look at is what you get. Interactions 2016, 23, 62–65. [Google Scholar] [CrossRef]
- Shin, J.-H.; Lee, S.-J. An Analysis on the Degree of 3D Sense Following Distance and Location through 3D Depth Level Change. Int. J. Smart Home 2012, 6, 6. [Google Scholar]
- Hussein, D. A user preference modelling method for the assessment of visual complexity in building façade. Smart Sustain. Built Environ. 2020. [Google Scholar] [CrossRef] [Green Version]
- Liu, S.; Helal, S.; Lee, J.W. Activity Playback Modeling for Smart Home Simulation. In Inclusive Smart Cities and e-Health. ICOST 2015. Lecture Notes in Computer Science; Springer: Cham, Switzerland, 2015; Volume 9102, pp. 92–102. [Google Scholar] [CrossRef]
- Garcia-Rodriguez, J.; Chamizo, J.M.G. Surveillance and human–computer interaction applications of self-growing models. Appl. Soft Comput. 2011, 11, 4413–4431. [Google Scholar] [CrossRef]
- Guamán, S.; Calvopiña, A.; Orta, P.; Tapia, F.; Yoo, S.G. Device Control System for a Smart Home using Voice Commands. In Proceedings of the 2018 10th International Conference on Information Management and Engineering—ICIME 2018, Salford, UK, 22–24 September 2018; pp. 86–89. [Google Scholar]
- Portet, F.; Vacher, M.; Golanski, C.; Roux, C.; Meillon, B. Design and evaluation of a smart home voice interface for the elderly: Acceptability and objection aspects. Pers. Ubiquitous Comput. 2011, 17, 127–144. [Google Scholar] [CrossRef] [Green Version]
- Vacher, M.; Lecouteux, B.; Istrate, D.; Joubert, T. Evaluation of a real-time voice order recognition system from multiple audio channels in a home. In Proceedings of the 14th Annual Conference of the International Speech Communication Association, INTERSPEECH, Lyon, France, 25–29 August 2013; pp. 2062–2064. [Google Scholar]
- Dumitrescu, S.D. Cassandra smart-home system description. In Proceedings of the 2017 International Conference on Speech Technology and Human-Computer Dialogue (SpeD), Bucharest, Romania, 6–9 July 2017; pp. 1–6. [Google Scholar]
- Drosos, K.; Floros, A.; Agavanakis, K.; Tatlas, N.-A.; Kanellopoulos, N.-G. Emergency voice/stress-level combined recognition for intelligent house applications. In Audio Engineering Society Convention 132; Audio Engineering Society: New York, NY, USA, 2012. [Google Scholar]
- Song, L.; Yuan, L. Design of IOS smart Home System Based on MQTT Protocol and Speech Recognition. J. Phys. Conf. Ser. 2018, 1069, 012046. [Google Scholar] [CrossRef]
- Yusri, M.M.; Kasim, S.; Hassan, R.; Abdullah, Z.; Ruslai, H.; Jahidin, K.; Arshad, M.S. Smart mirror for smart life. In Proceedings of the 2017 6th ICT International Student Project Conference (ICT-ISPC), Skudai, Malaysia, 23–24 May 2017; pp. 1–5. [Google Scholar]
- Brenon, A.; Portet, F.; Vacher, M. Arcades: A deep model for adaptive decision making in voice controlled smart-home. Pervasive Mob. Comput. 2018, 49, 92–110. [Google Scholar] [CrossRef] [Green Version]
- Tiwari, V.; Hashmi, M.F.; Keskar, A.; Shivaprakash, N. Speaker identification using multi-modal i-vector approach for varying length speech in voice interactive systems. Cogn. Syst. Res. 2018, 57, 66–77. [Google Scholar] [CrossRef]
- Mittal, Y.; Toshniwal, P.; Sharma, S.; Singhal, D.; Gupta, R.; Mittal, V.K. A voice-controlled multi-functional Smart Home Automation System. In Proceedings of the 2015 Annual IEEE India Conference (INDICON), New Delhi, India, 17–20 December 2015; pp. 1–6. [Google Scholar]
- Pereira, A.; Silva, F.; Ribeiro, J.C.B.; Marcelino, I.; Barroso, J. Smart Remote Control Design for Seniors. In Universal Access in Human-Computer Interaction. Access to Interaction. UAHCI 2015. Lecture Notes in Computer Science; Antona, M., Stephanidis, C., Eds.; Springer: Cham, Switzerland, 2015; Volume 9176, pp. 484–495. [Google Scholar]
- Wu, L.; Lu, J.; Zhang, T.; Gong, J. Robot-assisted intelligent emergency system for individual elderly independent living. In Proceedings of the 2016 IEEE Global Humanitarian Technology Conference (GHTC), Seattle, WA, USA, 13–16 October 2016; pp. 628–633. [Google Scholar]
- Pérez-Espinosa, H.; Martínez-Miranda, J.; Espinosa-Curiel, I.; Rodríguez-Jacobo, J.; Avila-George, H. Using acoustic paralinguistic information to assess the interaction quality in speech-based systems for elderly users. Int. J. Hum. Comput. Stud. 2017, 98, 1–13. [Google Scholar] [CrossRef]
- Djaid, N.T.; Saadia, N.; Ramdane-Cherif, A. Multimodal Fusion Engine for an Intelligent Assistance Robot Using Ontology. Procedia Comput. Sci. 2015, 52, 129–136. [Google Scholar] [CrossRef] [Green Version]
- Dogariu, M.; Cucu, H.; Buzo, A.; Burileanu, D.; Fratu, O. Speech applications in the eWALL project. In Proceedings of the 2015 International Conference on Speech Technology and Human-Computer Dialogue (SpeD), Bucharest, Romania, 14–17 October 2015; pp. 1–7. [Google Scholar]
- Potamianos, G.; Huang, J.; Marcheret, E.; Libal, V.; Balchandran, R.; Epstein, M.; Seredi, L.; Labský, M.; Ures, L.; Black, M.; et al. Far-Field Multimodal Speech Processing and Conversational Interaction in Smart Spaces. In Proceedings of the 2008 Hands-Free Speech Communication and Microphone Arrays Conference, Trento, Italy, 6–8 May 2008; pp. 119–123. [Google Scholar] [CrossRef]
- Xue, S.; Yan, Z.; Yu, T.; Liu, Z. A Study on Improving Acoustic Model for Robust and Far-Field Speech Recognition. In Proceedings of the 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), Shanghai, China, 19–21 November 2018; pp. 1–5. [Google Scholar]
- Caranica, A.; Cucu, H.; Burileanu, C.; Portet, F.; Vacher, M. Speech recognition results for voice-controlled assistive applications. In Proceedings of the 2017 International Conference on Speech Technology and Human-Computer Dialogue (SpeD), Bucharest, Romania, 6–9 July 2017; pp. 1–8. [Google Scholar]
- Lin, F.; Song, C.; Xu, X.; Cavuoto, L.; Xu, W. Patient Handling Activity Recognition through Pressure-Map Manifold Learning Using a Footwear Sensor. Smart Health 2017, 1–2, 77–92. [Google Scholar] [CrossRef]
- Xu, H.; Yuan, C.; Li, P.; Wang, Y. Design and implementation of action recognition system based on RFID sensor. In Proceedings of the 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), Guilin, China, 29–31 July 2017; pp. 3021–3025. [Google Scholar]
- Rashid, K.M.; Louis, J.; Fiawoyife, K.K. Wireless electric appliance control for smart buildings using indoor location tracking and BIM-based virtual environments. Autom. Constr. 2019, 101, 48–58. [Google Scholar] [CrossRef]
- Abid, M.; Petriu, E.M.; Amjadian, E. Dynamic Sign Language Recognition for Smart Home Interactive Application Using Stochastic Linear Formal Grammar. IEEE Trans. Instrum. Meas. 2014, 64, 596–605. [Google Scholar] [CrossRef]
- Luria, M.; Hoffman, G.; Zuckerman, O. Comparing Social Robot, Screen and Voice Interfaces for Smart-Home Control. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, CO, USA, 6–11 May 2017; pp. 580–628. [Google Scholar]
- Feng, Z.; Yang, B.; Xu, T.; Yang, X.; Xie, W.; Ai, C.; Chen, Z. FM: Flexible mapping from one gesture to multiple semantics. Inf. Sci. 2018. [Google Scholar] [CrossRef]
- Panëels, S.A.; Ritsos, P.D.; Rodgers, P.; Roberts, J.C. Prototyping 3D haptic data visualizations. Comput. Graph. 2013, 37, 179–192. [Google Scholar] [CrossRef]
- Hussain, M.A.; Ahsan, K.; Iqbal, S.; Nadeem, A. Supporting deafblind in congregational prayer using speech recognition and vibro-tactile stimuli. Int. J. Hum. Comput. Stud. 2019, 123, 70–96. [Google Scholar] [CrossRef]
- Vega-Barbas, M.; Pau, I.; Augusto, J.C.; Seoane, F. Interaction Patterns for Smart Spaces: A Confident Interaction Design Solution for Pervasive Sensitive IoT Services. IEEE Access 2018, 6, 1126–1136. [Google Scholar] [CrossRef]
- Yue, P.; Jing, L.; Lei, X. A Study on Intelligent Housekeeper of Smart Home System. In Proceedings of the 2017 9th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), Changsha, China, 14–15 January 2017; pp. 124–127. [Google Scholar]
- Rognini, G.; Blanke, O.; Information, P.E.K.F.C. Cognetics: Robotic Interfaces for the Conscious Mind. Trends Cogn. Sci. 2016, 20, 162–164. [Google Scholar] [CrossRef]
- Glodek, M.; Honold, F.; Geier, T.; Krell, G.; Nothdurft, F.; Reuter, S.; Schüssel, F.; Hörnle, T.; Dietmayer, K.; Minker, W.; et al. Fusion paradigms in cognitive technical systems for human–computer interaction. Neurocomputing 2015, 161, 17–37. [Google Scholar] [CrossRef] [Green Version]
- Lee, E.-J.; Park, S.-J. Configuring a Residential Hologram System to Complement the Cognitive Function of the Elderly. J. Archit. Inst. Korea Plan. Des. 2018, 34, 67–74. [Google Scholar]
- Civitarese, G.; Belfiore, S.; Bettini, C. Let the objects tell what you are doing. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing—UbiComp’ 16, Heidelberg, Germany, 12–16 September 2016; pp. 773–782. [Google Scholar]
- Fortin-Simard, D.; Bilodeau, J.-S.; Gaboury, S.; Bouchard, B.; Bouzouane, A. Bastien Method of Recognition and Assistance Combining Passive RFID and Electrical Load Analysis That Handles Cognitive Errors. Int. J. Distrib. Sens. Netw. 2015, 2015, 1–18. [Google Scholar] [CrossRef]
- Källström, M.; Berdal, S.; Joshi, S.G. Designing an Indoor Navigation System for Elderly People’s Capabilities. Lect. Notes Comput. Sci. 2015, 9194, 435–445. [Google Scholar] [CrossRef]
- Zhao, H.; Ma, Y.; Wang, S.; Watson, A.; Zhou, G. MobiGesture: Mobility-aware hand gesture recognition for healthcare. Smart Health 2018, 9–10, 129–143. [Google Scholar] [CrossRef]
- Yamazaki, T.; Yamazaki, T. Communicative robot interface for the ageing society. In Proceedings of the 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV), Guangzhou, China, 5–7 December 2012; pp. 668–671. [Google Scholar]
- Gross, H.-M.; Schroeter, C.; Mueller, S.; Volkhardt, M.; Einhorn, E.; Bley, A.; Langner, T.; Merten, M.; Huijnen, C.; Heuvel, H.V.D.; et al. Further progress towards a home robot companion for people with mild cognitive impairment. In Proceedings of the 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Seoul, Korea, 14–17 October 2012; pp. 637–644. [Google Scholar]
- Mokhtari, M.; Aloulou, H.; Tiberghien, T.; Biswas, J.; Racoceanu, D.; Yap, P. New Trends to Support Independence in Persons with Mild Dementia—A Mini-Review. Gerontology 2012, 58, 554–563. [Google Scholar] [CrossRef]
- Alrajhi, W.; Alaloola, D.; Albarqawi, A. Smart home: Toward daily use of BCI-based systems. In Proceedings of the International Conference on Informatics, Health & Technology (ICIHT), Riyadh, Saudi Arabia, 21–23 February 2017; pp. 1–5. [Google Scholar]
- Fredericks, E.M.; Bowers, K.M.; Price, K.A.; Hariri, R.H. CAL: A Smart Home Environment for Monitoring Cognitive Decline. In Proceedings of the 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), Vienna, Austria, 2–6 July 2018; pp. 1500–1506. [Google Scholar]
- Schwan, J.; Ghaleb, E.; Hortal, E.; Asteriadis, S. High-performance and lightweight real-time deep face emotion recognition. In Proceedings of the 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP), Bratislava, Slovakia, 9–10 July 2017; pp. 76–79. [Google Scholar] [CrossRef]
- Chen, M.; Ma, Y.; Hao, Y.; Li, Y.; Wu, D.; Zhang, Y.; Song, E. CP-Robot: Cloud-Assisted Pillow Robot for Emotion Sensing and Interaction. In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Wan, J., Humar, I., Zhang, D., Eds.; Springer: Cham, Switzerland, 2016; pp. 81–93. [Google Scholar]
- Rodic, A.; Jovanović, M.; Stevanović, I.; Karan, B.; Potkonjak, V. Building technology platform aimed to develop service robot with embedded personality and enhanced communication with social environment. Digit. Commun. Netw. 2015, 1, 112–124. [Google Scholar] [CrossRef] [Green Version]
- Qian, Y.; Lu, J.; Miao, Y.; Ji, W.; Jin, R.; Song, E. AIEM: AI-enabled affective experience management. Futur. Gener. Comput. Syst. 2018, 89, 438–445. [Google Scholar] [CrossRef]
- Huang, Y.-C.; Wu, K.-Y.; Liu, Y.-T. Future home design: An emotional communication channel approach to smart space. Pers. Ubiquitous Comput. 2013, 17, 1281–1293. [Google Scholar] [CrossRef]
- Costa, Â.; Rincon, J.A.; Carrascosa, C.; Julian, V.; Novais, P. Emotions detection on an ambient intelligent system using wearable devices. Future Gener. Comput. Syst. 2019, 92, 479–489. [Google Scholar] [CrossRef] [Green Version]
- Thakur, N.; Han, C.Y. A complex activity based emotion recognition algorithm for affect aware systems. In Proceedings of the 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 8–10 January 2018; pp. 748–753. [Google Scholar]
- Gamecho, B.; Da Silva, H.P.; Guerreiro, J.; Gardeazabal, L.; Abascal, J. A Context-Aware Application to Increase Elderly Users Compliance with Physical Rehabilitation Exercises at Home via Animatronic Biofeedback. J. Med. Syst. 2015, 39. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Curumsing, M.K.; Fernando, N.; Abdelrazek, M.; Vasa, R.; Mouzakis, K.; Grundy, J. Emotion-oriented requirements engineering: A case study in developing a smart home system for the elderly. J. Syst. Softw. 2019, 147, 215–229. [Google Scholar] [CrossRef]
- Mano, L.Y. Emotional condition in the Health Smart Homes environment: Emotion recognition using ensemble of classifiers. In Proceedings of the 2018 Innovations in Intelligent Systems and Applications (INISTA) Conference, Adana, Turkey, 4–6 October 2018; pp. 1–8. [Google Scholar] [CrossRef]
- Marti, P.; Iacono, I. Social and empathic behaviours: Novel interfaces and interaction modalities. In Proceedings of the 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), Kobe, Japan, 31 August–4 September 2015; pp. 217–222. [Google Scholar]
- Wei, J.; Liu, H.; Wang, B.; Sun, F. Lifelong learning for tactile emotion recognition. Interact. Stud. 2019, 20, 25–41. [Google Scholar] [CrossRef]
- Lanjewar, R.B.; Mathurkar, S.; Patel, N. Implementation and Comparison of Speech Emotion Recognition System Using Gaussian Mixture Model (GMM) and K-Nearest Neighbor (K-NN) Techniques. Procedia Comput. Sci. 2015, 49, 50–57. [Google Scholar] [CrossRef] [Green Version]
- Yang, S.-H.; Liu, X.-W.; Lo, Y.-C. A design framework for smart TV: Case study of the TaipeiTech smart TV system. In Proceedings of the 2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), Nantou, Taiwan, 27–29 May 2016; pp. 1–2. [Google Scholar]
- Rathnayake, K.A.S.V.; Wanniarachchi, W.K.I.L.; Nanavakkara, W.H.K.P. Human Computer Interaction System for Impaired People by using Kinect Motion Sensor: Voice and Gesture Integrated Smart Home. In Proceedings of the 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), Coimbatore, India, 20–21 April 2018; pp. 531–536. [Google Scholar]
- Almusaylim, Z.A.; Zaman, N. A review on smart home present state and challenges: Linked to context-awareness internet of things (IoT). Wirel. Netw. 2018, 25, 3193–3204. [Google Scholar] [CrossRef]
- Lee, H.J.; Kim, K.H.; Kim, Y.H. Wireless Sensor Network-Based 3D Home Control System for Smart Home Environment. Int. J. Smart Home 2016, 10, 159–168. [Google Scholar] [CrossRef]
Country or Region | Number of Publications | Percentage of Publication (%) |
---|---|---|
China | 15 | 19.40 |
United States | 9 | 10.45 |
France | 4 | 5.97 |
India | 3 | 4.48 |
Australia | 3 | 4.48 |
Spain | 3 | 4.48 |
Romania | 3 | 4.48 |
Italy | 2 | 2.97 |
Japan | 2 | 2.97 |
Netherlands | 2 | 2.97 |
Greece | 2 | 2.97 |
Portugal | 2 | 2.97 |
Taiwan | 2 | 2.97 |
Canada | 2 | 2.97 |
Sweden, Finland, Singapore, Arabia, Earl, Malaysia, Mexico, Algeria, Israel, Pakistan, South Korea, Norway, Switzerland, Germany, Brazil, Serbia, Sri Lanka | 2 | 1.49 |
Total | 72 | 100 |
Interaction Type | Quantity | Percentage (%) |
---|---|---|
visual interaction | 15 | 20.59 |
voice interaction | 22 | 30.88 |
tactile interaction | 10 | 14.70 |
cognitive interaction | 14 | 19.12 |
emotional interaction | 15 | 20.59 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, Z.; Zhang, J.; Li, M.; Huang, J.; Wang, X. A Review of Smart Design Based on Interactive Experience in Building Systems. Sustainability 2020, 12, 6760. https://doi.org/10.3390/su12176760
Li Z, Zhang J, Li M, Huang J, Wang X. A Review of Smart Design Based on Interactive Experience in Building Systems. Sustainability. 2020; 12(17):6760. https://doi.org/10.3390/su12176760
Chicago/Turabian StyleLi, Zhen, Jiao Zhang, Mengwan Li, Jizhuo Huang, and Xiangyu Wang. 2020. "A Review of Smart Design Based on Interactive Experience in Building Systems" Sustainability 12, no. 17: 6760. https://doi.org/10.3390/su12176760
APA StyleLi, Z., Zhang, J., Li, M., Huang, J., & Wang, X. (2020). A Review of Smart Design Based on Interactive Experience in Building Systems. Sustainability, 12(17), 6760. https://doi.org/10.3390/su12176760