A Context Aware Smart Classroom Architecture for Smart Campuses
Source abstract
Abstract
The Smart campus is a concept of an education institute using technologies, such as information systems, internet of things (IoT), and context-aware computing, to support learning, teaching, and administrative activities. Classrooms are important building blocks of a school campus. Therefore, a feasible architecture for building and running smart classrooms is essential for a smart campus. However, most studies related to the smart classroom are focused on studying or addressing particular technical or educational issues, such as networking, AI applications, lecture quality, and user responses to technology. In this study, an architecture for building and running context-aware smart classrooms is proposed. The proposed architecture consists of three parts including a prototype of a context-aware smart classroom, a model for technology integration, and supporting measures for the operation of smart classrooms in this architecture. The classroom prototype was designed based on our study results and a smart classroom project in Ming Chuan University (MCU). The integration model was a layered model uses Raspberry Pi in the bottom layer of the model to integrate underlying technologies and provide application interfaces to the higher layer applications for the ease of building context-aware smart classroom applications. As a result, application interfaces were implemented using Raspberry Pi based on the proposed technology integration model, and a context-aware energy-saving smart classroom application was implemented based on the proposed classroom prototype and the implemented web application interface. The result shows that, in terms of technology, the proposed architecture is feasible for building context-aware smart classrooms in smart campuses.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: IoT-based Smart Home Systems · Water Quality Monitoring Technologies · Context-Aware Activity Recognition Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Science and Engineering, Tatung University, No.40, Sec. 3, Zhong Shan N. Rd., Taipei City 104, Taiwan
Department of New Media and Communication Administration, Ming Chuan University, 250 Zhong Shan N. Rd., Sec. 5, Taipei City 111, Taiwan
References (85)
Show source-provided references
1. Muhamad, W., Kurniawan, N.B., and Yazid, S. (2017, January 23–24). Smart campus features, technologies, and applications: A systematic literature review. Proceedings of the 2017 International Conference on Information Technology Systems and Innovation (ICITSI), Bandung, Indonesia.10.1109/ICITSI.2017.8267975 ↗
2. (2019, April 24). Jisc Home Page. Available online: https://www.jisc.ac.uk/.
3. (2019, April 24). Guide to the Intelligent Campus. Available online: https://repository.jisc.ac.uk/6882/1/Intelligent_Campus_Guide.pdf.
4. Malatji, E.M. (2017, January 21–23). The Development of a Smart Campus—African Universities Point of View. Proceedings of the 2017 8th International Renewable Energy Congress (IREC), Amman, Jordan.10.1109/IREC.2017.7926010 ↗
5. John, T.M., Ucheaga, E.G., Badejo, J.A., and Atayero, A.A. (2017, January 14–16). A Framework for a Smart Campus: A Case of Covenant University. Proceedings of the 2017 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA.10.1109/CSCI.2017.239 ↗
6. Alghamdi, A., and Shetty, S. (2016, January 22–24). Survey Toward a Smart Campus Using the Internet of Things. Proceedings of the 2016 IEEE 4th International Conference on Future Internet of Things and Cloud (FiCloud), Vienna, Austria.10.1109/FiCloud.2016.41 ↗
7. (2018, November 23). Raspberry Pi Home Page. Available online: https://www.raspberrypi.org/.
8. System for recognizing lecture quality based on analysis of physical parameters10.1016/j.tele.2017.06.014 ↗
9. A comprehensive study of parameters in physical environment that impact students’ focus during lecture using Internet of Things10.1016/j.chb.2015.07.023 ↗
10. Students’ Perceived Effectiveness of Educational Technologies and Motivation in Smart Classroom
11. Transformation of classroom spaces: Traditional versus active learning classroom in colleges10.1007/s10734-014-9742-0 ↗
12. Bridging approaches: Classroom Physical Space as a learning ecosystem
13. (2018, December 20). Future Classroom Lab. Available online: http://www.eun.org/professional-development/future-classroom-lab.
14. (2018, December 21). European Schoolnet Home Page. Available online: http://www.eun.org/home.
15. (2018, December 21). Learning Zones of the Future Classroom Lab. Available online: http://fcl.eun.org/documents/10180/13526/FCL+learning+zones+Dec+2016/a091a761-7a63-443e-afe0-d1870e430686.
16. ARS Interactive Teaching Mode for Financial Accounting Course based on Smart Classroom10.3991/ijet.v14i03.10104 ↗
17. Xie, W., Shi, Y., Xu, G., and Xie, D. (2001, January 24–26). Smart Classroom—An Intelligent Environment for Tele-education. Proceedings of the Advances in Multimedia Information Processing—PCM 2001, Beijing, China.10.1007/3-540-45453-5_85 ↗
18. (2018, October 14). The Open Agent Architecture. Available online: http://www.ai.sri.com/~oaa/.
19. Mao, Y., Xie, W., Shi, Y., Xu, G., and Xiang, X. (2002, January 16–18). Building the Software Infrastructure for Smart Classroom: From Open Agent Architecture (OAA) to Smart Platform. Proceedings of the Advances in Multimedia Information Processing—PCM 2002, Hsinchu, Taiwan.10.1007/3-540-36228-2_65 ↗
20. Network Education Ware: An open-source web-based system for synchronous distance education10.1109/TE.2005.854577 ↗
21. (2018, December 13). The Network Education Ware Project. Available online: https://netlab.gmu.edu/NEW/.
22. CAMPS: A middleware for providing context-aware services for Smart Space10.1007/11745693_63 ↗
23. Open Smart Classroom: Extensible and Scalable Learning System in Smart Space Using Web Service Technology10.1109/TKDE.2008.117 ↗
24. The smart classroom: Merging technologies for seamless tele-education10.1109/MPRV.2003.1203753 ↗
25. Developing a NFC-equipped smart classroom: Effects on attitudes toward computer science10.1016/j.chb.2013.09.002 ↗
26. Determinants of interactive white board success in teaching in higher education institutions10.1016/j.compedu.2010.10.024 ↗
27. Co-Designing Collaborative Smart Classroom Curriculum for Secondary School Science
28. Students’ Perceptions and Behaviour in Technology-Rich Classroom and Multi-Media Classroom
29. An initial development and validation of a Digital Natives Assessment Scale (DNAS)10.1016/j.compedu.2013.02.012 ↗
30. A Survey on Role of Internet of Things in Education
31. Augmented Reality in a Smart Classroom-Case Study: SaCI10.1109/RITA.2017.2776419 ↗
32. Towards Emotionally Aware AI Smart Classroom: Current Issues and Directions for Engineering and Education10.1109/ACCESS.2018.2791861 ↗
33. Learning analytics tasks as services in smart classrooms10.1007/s10209-017-0525-0 ↗
34. A core model supporting location-aware computing in smart classroom10.1007/11528043_1 ↗
35. Energy-aware and intelligent storage features for multimedia devices in smart classroom10.1007/s11042-015-3019-1 ↗
36. Understanding students’ preferences toward the smart classroom learning environment: Development and validation of an instrument10.1016/j.compedu.2018.03.015 ↗
37. (2018, October 12). Python Home Page. Available online: https://www.python.org/.
38. (2018, October 12). Flask microframework Home Page. Available online: http://flask.pocoo.org/.
39. Parikh, V., Keskar, M., Dharia, D., and Gotmare, P. (2018, January 20–21). A Tourist Place Recommendation and Recognition System. Proceedings of the 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), Coimbatore, India.10.1109/ICICCT.2018.8473077 ↗
40. Nepomuceno, T., Carneiro, T., Carneiro, T., Korn, C., and Martin, A. (2018, January 12–13). A GUI-based Platform for Quickly Prototyping Server-side IoT Applications. Proceedings of the Smart SysTech 2018; European Conference on Smart Objects, Systems and Technologies, Munich, Germany.
41. Kauling, D., and Mahmoud, Q.H. (2017, January 8–11). Sensorian Hub: An IFTTT-based platform for collecting and processing sensor data. Proceedings of the 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA.10.1109/CCNC.2017.7983159 ↗
42. Gharibi, G., Alanazi, R., and Lee, Y. (2018, January 10–13). Automatic Hierarchical Clustering of Static Call Graphs for Program Comprehension. Proceedings of the 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA.10.1109/BigData.2018.8622426 ↗
43. Tiankaew, U., Chunpongthong, P., and Mettanant, V. (2018, January 11–13). A Food Photography App with Image Recognition for Thai Food. Proceedings of the 2018 Seventh ICT International Student Project Conference (ICT-ISPC), Nakhonpathom, Thailand.10.1109/ICT-ISPC.2018.8523925 ↗
44. Çelık, N., and Oğul, H. (2017, January 15–18). A web application for content based geographic image retrieval. Proceedings of the 2017 25th Signal Processing and Communications Applications Conference (SIU), Antalya, Turkey.10.1109/SIU.2017.7960325 ↗
45. Singh, S., Kaushik, A., and Chitkara, S.S. (2017, January 10–11). Ubiquitously controlled personalized smartlock. Proceedings of the 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, India.10.1109/I-SMAC.2017.8058266 ↗
46. Patil, S.M., Vijayalashmi, M., and Tapaskar, R. (2017, January 1–2). IoT based solar energy monitoring system. Proceedings of the 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), Chennai, India.10.1109/ICECDS.2017.8389711 ↗
47. Vogel, P., Klooster, T., Andrikopoulos, V., and Lungu, M. (2017, January 18–19). A Low-Effort Analytics Platform for Visualizing Evolving Flask-Based Python Web Services. Proceedings of the 2017 IEEE Working Conference on Software Visualization (VISSOFT), Shanghai, China.10.1109/VISSOFT.2017.13 ↗
48. (2019, April 20). PHP Home Page. Available online: https://www.php.net/.
49. (2019, April 22). Programming Languages Used in Most Popular Websites. Available online: https://en.wikipedia.org/wiki/Programming_languages_used_in_most_popular_websites.
50. (2019, April 22). MariaDB Home Page. Available online: https://mariadb.org/.
51. (2019, April 22). MySQL Home Page. Available online: https://www.mysql.com/.
52. RFID Infrastructure Design: A Case Study of Two Australian RFID Projects10.1109/MIC.2009.18 ↗
53. (2019, April 22). RS-485. Available online: https://en.wikipedia.org/wiki/RS-485.
54. (2019, April 22). RS-232. Available online: https://en.wikipedia.org/wiki/RS-232.
55. Learning in an Ambient Intelligent World: Enabling Technologies and Practices10.1109/TKDE.2008.143 ↗
56. Unified framework for IoT and smartphone based different smart city related applications
57. (2018, December 08). Arduino Home. Available online: https://www.arduino.cc/.
58. Energy management and planning in smart cities10.1016/j.rser.2015.10.133 ↗
59. A Hierarchical Decision-Making Strategy for the Energy Management of Smart Cities10.1109/TASE.2016.2593101 ↗
60. Decentralized Resource Allocation and Load Scheduling for Multicommodity Smart Energy Systems10.1109/TSTE.2015.2441107 ↗
61. Carli, R., and Dotoli, M. (2015, January 15–18). A decentralized resource allocation approach for sharing renewable energy among interconnected smart homes. Proceedings of the 2015 54th IEEE Conference on Decision and Control (CDC), Osaka, Japan.10.1109/CDC.2015.7403147 ↗
62. Energy Management System for an Energy District With Demand Response Availability10.1109/TSG.2014.2318894 ↗
63. Cooperative Distributed Control for the Energy Scheduling of Smart Homes with Shared Energy Storage and Renewable Energy Source10.1016/j.ifacol.2017.08.1544 ↗
64. A SCADA system for energy management in intelligent buildings10.1016/j.enbuild.2012.01.041 ↗
65. Carli, R., and Dotoli, M. (2014, January 15–17). Energy scheduling of a smart home under nonlinear pricing. Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, CA, USA.10.1109/CDC.2014.7040273 ↗
66. The study of energy-saving strategy for direct expansion air conditioning system10.1016/j.enbuild.2008.02.023 ↗
67. Potential opportunities for energy conservation in existing buildings on university campus: A field survey in Korea10.1016/j.enbuild.2014.04.018 ↗
68. Life cycle cost analysis and payback period of lighting retrofit at the University of Malaya10.1016/j.rser.2010.10.014 ↗
69. Data association mining for identifying lighting energy waste patterns in educational institutes10.1016/j.enbuild.2013.02.049 ↗
70. (2019, February 20). Ming Chuan University Official Website. Available online: https://web.mcu.edu.tw/en.
71. (2019, April 18). Overview of the Internet of Things. Available online: http://handle.itu.int/11.1002/1000/11559.
72. NIST (2011). The NIST Definition of Cloud Computing, NIST.
73. Internet of Things (IoT): A vision, architectural elements, and future directions10.1016/j.future.2013.01.010 ↗
74. NIST (2018). Fog Computing Conceptual Model, NIST.
75. Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012, January 17). Fog computing and its role in the internet of things. Proceedings of the first edition of the MCC workshop on Mobile cloud computing, Helsinki, Finland.10.1145/2342509.2342513 ↗
76. Burt, J. (2019, April 18). Fog Computing Aims to Reduce Processing Burden of Cloud Systems. Available online: https://www.eweek.com/networking/fog-computing-aims-to-reduce-processing-burden-of-cloud-systems.
77. Rahmani, A., Thanigaivelan, N.K., Tuan Nguyen, G., Granados, J., Negash, B., Liljeberg, P., and Tenhunen, H. (2015, January 9–12). Smart e-Health Gateway: Bringing intelligence to Internet-of-Things based ubiquitous healthcare systems. Proceedings of the 2015 12th Annual IEEE Consumer Communications and Networking Conference (CCNC).10.1109/CCNC.2015.7158084 ↗
78. Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach10.1016/j.future.2017.02.014 ↗
79. Hentschel, K., Jacob, D., Singer, J., and Chalmers, M. (2016, January 22–24). Supersensors: Raspberry Pi Devices for Smart Campus Infrastructure. Proceedings of the 2016 IEEE 4th International Conference on Future Internet of Things and Cloud (FiCloud), Vienna, Austria.10.1109/FiCloud.2016.16 ↗
80. Wang, Y., Saez, B., Szczechowicz, J., Ruisi, J., Kraft, T., Toscano, S., Vacco, Z., and Nicolas, K. (2017, January 19–21). A smart campus internet of things framework. Proceedings of the 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON), New York City, NY, USA.10.1109/UEMCON.2017.8249106 ↗
81. Narendrakumar, T., and Pillai, A.S. (2017, January 6–7). Smart connected campus. Proceedings of the 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Kannur, Kerala, India.10.1109/ICICICT1.2017.8342808 ↗
82. Haghi, A., Burney, K., Kidd, F.S., Valiente, L., and Peng, Y. (2017, January 6–9). Fast-paced development of a smart campus IoT platform. Proceedings of the 2017 Global Internet of Things Summit (GIoTS), Geneva, Switzerland.10.1109/GIOTS.2017.8016214 ↗
83. Research on Key Technologies of Smart Campus Teaching Platform Based on 5G Network10.1109/ACCESS.2019.2894129 ↗
84. Situational Awareness System in the Smart Campus10.1109/ACCESS.2018.2877428 ↗
85. (2018, December 01). International Conference on Smart Campus and Exhibition, iCSC&E. Available online: http://icsc.tku.edu.tw/.