{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T09:25:10Z","timestamp":1772616310081,"version":"3.50.1"},"reference-count":66,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,8,26]],"date-time":"2020-08-26T00:00:00Z","timestamp":1598400000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,8,26]],"date-time":"2020-08-26T00:00:00Z","timestamp":1598400000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100010329","name":"University of Bradford","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100010329","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Inf Syst Front"],"published-print":{"date-parts":[[2023,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The emerging information revolution makes it necessary to manage vast amounts of unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors that can sense their surroundings and communicate with each other, a digital environment has been created with vast volumes of volatile and diverse data. Traditional AI and machine learning techniques designed for deterministic situations are not suitable for such environments. With a large number of parameters required by each device in this digital environment, it is desirable that the AI is able to be adaptive and self-build (i.e. self-structure, self-configure, self-learn), rather than be structurally and parameter-wise pre-defined. This study explores the benefits of self-building AI and machine learning with unsupervised learning for empowering big data analytics for smart city environments. By using the growing self-organizing map, a new suite of self-building AI is proposed. The self-building AI overcomes the limitations of traditional AI and enables data processing in dynamic smart city environments. With cloud computing platforms, the self-building AI can integrate the data analytics applications that currently work in silos. The new paradigm of the self-building AI and its value are demonstrated using the IoT, video surveillance, and action recognition applications.<\/jats:p>","DOI":"10.1007\/s10796-020-10056-x","type":"journal-article","created":{"date-parts":[[2020,8,26]],"date-time":"2020-08-26T20:02:46Z","timestamp":1598472166000},"page":"221-240","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":81,"title":["Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities"],"prefix":"10.1007","volume":"25","author":[{"given":"Damminda","family":"Alahakoon","sequence":"first","affiliation":[]},{"given":"Rashmika","family":"Nawaratne","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Daswin","family":"De Silva","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6401-540X","authenticated-orcid":false,"given":"Uthayasankar","family":"Sivarajah","sequence":"additional","affiliation":[]},{"given":"Bhumika","family":"Gupta","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,8,26]]},"reference":[{"key":"10056_CR1","doi-asserted-by":"crossref","unstructured":"Adikari, A., De Silva, D., Alahakoon, D., & Yu, X. (2019). A cognitive model for emotion awareness in industrial Chatbots. 2019 IEEE 17th international conference on industrial informatics (INDIN), 1, 183\u2013186.","DOI":"10.1109\/INDIN41052.2019.8972196"},{"issue":"3","key":"10056_CR2","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1109\/72.846732","volume":"11","author":"D Alahakoon","year":"2000","unstructured":"Alahakoon, D., Halgamuge, S. K., & Srinivasan, B. (2000). Dynamic self-organizing maps with controlled growth for knowledge discovery. IEEE Transactions on Neural Networks, 11(3), 601\u2013614. https:\/\/doi.org\/10.1109\/72.846732.","journal-title":"IEEE Transactions on Neural Networks"},{"key":"10056_CR3","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.cities.2019.01.032","volume":"89","author":"Z Allam","year":"2019","unstructured":"Allam, Z., & Dhunny, Z. A. (2019). On big data, artificial intelligence and smart cities. Cities, 89, 80\u201391.","journal-title":"Cities"},{"key":"10056_CR4","doi-asserted-by":"crossref","unstructured":"Alter, S. (2019). Making sense of smartness in the context of smart devices and smart systems. Information Systems Frontiers, 1\u201313.","DOI":"10.1007\/s10796-019-09919-9"},{"key":"10056_CR5","doi-asserted-by":"publisher","unstructured":"Bandaragoda, T., Adikari, A., Nawaratne, R., Nallaperuma, D., Luhach, A, Kr., Kempitiya, T., Nguyen, S., Alahakoon, D., De Silva, D., & Chilamkurti, N. (2020). Artificial intelligence based commuter behaviour profiling framework using internet of things for real-time decision-making. Neural Computing and Applications. https:\/\/doi.org\/10.1007\/s00521-020-04736-7.","DOI":"10.1007\/s00521-020-04736-7"},{"issue":"3","key":"10056_CR6","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/S0370-1573(99)00096-4","volume":"329","author":"S Boccaletti","year":"2000","unstructured":"Boccaletti, S., Grebogi, C., Lai, Y. C., Mancini, H., Maza, D., & Lai, Y.-C. (2000). The control of chaos: Theory and applications. Physics Reports, 329(3), 103\u2013197. https:\/\/doi.org\/10.1016\/S0370-1573(99)00096-4.","journal-title":"Physics Reports"},{"key":"10056_CR7","unstructured":"Bundy, A. (2017). Preparing for the future of artificial intelligence. Springer"},{"key":"10056_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2019\/5232374","volume":"2019","author":"L Carey","year":"2019","unstructured":"Carey, L., Walsh, A., Adikari, A., Goodin, P., Alahakoon, D., De Silva, D., Ong, K.-L., Nilsson, M., & Boyd, L. (2019). Finding the intersection of neuroplasticity, stroke recovery, and learning: Scope and contributions to stroke rehabilitation. Neural Plasticity., 2019, 1\u201315. https:\/\/doi.org\/10.1155\/2019\/5232374.","journal-title":"Neural Plasticity."},{"issue":"2","key":"10056_CR9","doi-asserted-by":"publisher","first-page":"268","DOI":"10.5539\/cis.v3n2p268","volume":"3","author":"Y Chen","year":"2010","unstructured":"Chen, Y., Qin, B., Liu, T., Liu, Y., & Li, S. (2010). The comparison of SOM and K-means for text clustering. Computer and Information Science, 3(2), 268\u2013274.","journal-title":"Computer and Information Science"},{"issue":"4","key":"10056_CR10","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1109\/MCOM.2019.1800628","volume":"57","author":"B-W Chen","year":"2019","unstructured":"Chen, B.-W., Imran, M., Nasser, N., & Shoaib, M. (2019). Self-aware Autonomous City: From sensing to planning. IEEE Communications Magazine, 57(4), 33\u201339. https:\/\/doi.org\/10.1109\/MCOM.2019.1800628.","journal-title":"IEEE Communications Magazine"},{"key":"10056_CR11","doi-asserted-by":"crossref","unstructured":"Choi, W., Shahid, K., & Savarese, S. (2009). What are they doing?: Collective activity classification using spatio-temporal relationship among people. Computer vision workshops (ICCV workshops), 2009 IEEE 12th international conference on, 1282\u20131289.","DOI":"10.1109\/ICCVW.2009.5457461"},{"key":"10056_CR12","doi-asserted-by":"publisher","unstructured":"Cziko, G, A. (2016). Unpredictability and indeterminism in human behavior: Arguments and implications for educational Research: Educational Researcher. https:\/\/doi.org\/10.3102\/0013189X018003017,","DOI":"10.3102\/0013189X018003017"},{"key":"10056_CR13","doi-asserted-by":"publisher","unstructured":"Dalal, N., & Triggs, B. (2005). Histograms of oriented gradients for human detection. 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201905), 1, 886\u2013893 vol. 1. https:\/\/doi.org\/10.1109\/CVPR.2005.177.","DOI":"10.1109\/CVPR.2005.177"},{"issue":"2","key":"10056_CR14","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1109\/MIE.2019.2952165","volume":"14","author":"D De Silva","year":"2020","unstructured":"De Silva, D., Sierla, S., Alahakoon, D., Osipov, E., Yu, X., & Vyatkin, V. (2020). Toward intelligent industrial informatics: A review of current developments and future directions of artificial intelligence in industrial applications. IEEE Industrial Electronics Magazine, 14(2), 57\u201372. https:\/\/doi.org\/10.1109\/MIE.2019.2952165.","journal-title":"IEEE Industrial Electronics Magazine"},{"key":"10056_CR15","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1016\/j.ijinfomgt.2019.04.017","volume":"49","author":"KA Eldrandaly","year":"2019","unstructured":"Eldrandaly, K. A., Abdel-Basset, M., & Abdel-Fatah, L. (2019). PTZ-surveillance coverage based on artificial intelligence for smart cities. International Journal of Information Management., 49, 520\u2013532. https:\/\/doi.org\/10.1016\/j.ijinfomgt.2019.04.017.","journal-title":"International Journal of Information Management."},{"issue":"4","key":"10056_CR16","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1007\/s10796-013-9481-2","volume":"17","author":"A Emam","year":"2015","unstructured":"Emam, A. (2015). Intelligent drowsy eye detection using image mining. Information Systems Frontiers, 17(4), 947\u2013960.","journal-title":"Information Systems Frontiers"},{"key":"10056_CR17","doi-asserted-by":"publisher","unstructured":"Fonseka, A., & Alahakoon, D. (2010). Exploratory data analysis with multi-layer growing self-organizing maps. 2010 fifth international conference on information and automation for sustainability, 132\u2013137. https:\/\/doi.org\/10.1109\/ICIAFS.2010.5715648.","DOI":"10.1109\/ICIAFS.2010.5715648"},{"key":"10056_CR18","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1007\/978-3-642-24958-7_88","volume-title":"Neural information processing","author":"A Fonseka","year":"2011","unstructured":"Fonseka, A., Alahakoon, D., & Rajapakse, J. (2011). A dynamic unsupervised laterally connected neural network architecture for integrative pattern discovery. In B.-L. Lu, L. Zhang, & J. Kwok (Eds.), Neural information processing (pp. 761\u2013770). Berlin Heidelberg: Springer."},{"issue":"9","key":"10056_CR19","doi-asserted-by":"publisher","first-page":"1441","DOI":"10.1016\/0893-6080(94)90091-4","volume":"7","author":"B Fritzke","year":"1994","unstructured":"Fritzke, B. (1994). Growing cell structures\u2014A self-organizing network for unsupervised and supervised learning. Neural Networks, 7(9), 1441\u20131460.","journal-title":"Neural Networks"},{"key":"10056_CR20","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/978-3-642-24958-7_23","volume-title":"Neural information processing","author":"H Ganegedara","year":"2011","unstructured":"Ganegedara, H., & Alahakoon, D. (2011). Scalable data clustering: A Sammon\u2019s projection based technique for merging GSOMs. In B.-L. Lu, L. Zhang, & J. Kwok (Eds.), Neural information processing (pp. 193\u2013202). Berlin Heidelberg: Springer."},{"key":"10056_CR21","doi-asserted-by":"publisher","unstructured":"Ganegedara, H., & Alahakoon, D. (2012). Redundancy reduction in self-organising map merging for scalable data clustering. The 2012 International Joint Conference on Neural Networks (IJCNN), 1\u20138. https:\/\/doi.org\/10.1109\/IJCNN.2012.6252722.","DOI":"10.1109\/IJCNN.2012.6252722"},{"key":"10056_CR22","doi-asserted-by":"publisher","unstructured":"Garcia-Font, V., Garrigues, C., & Rif\u00e0-Pous, H. (2016). A comparative study of anomaly detection techniques for Smart City wireless sensor networks. Sensors (Basel, Switzerland), 16(6). https:\/\/doi.org\/10.3390\/s16060868.","DOI":"10.3390\/s16060868"},{"key":"10056_CR23","doi-asserted-by":"publisher","unstructured":"Guelzim, T., & Obaidat, M. S. (2016). Cloud computing systems for smart cities and homes. In M. S. Obaidat & P. Nicopolitidis (Eds.), Smart Cities and Homes (pp. 241\u2013260). Morgan Kaufmann. https:\/\/doi.org\/10.1016\/B978-0-12-803454-5.00012-2.","DOI":"10.1016\/B978-0-12-803454-5.00012-2"},{"key":"10056_CR24","doi-asserted-by":"publisher","unstructured":"Gunawardena, P., Amila, O., Sudarshana, H., Nawaratne, R., Luhach, A, Kr., Alahakoon, D., Perera, A, S., Chitraranjan, C., Chilamkurti, N., & De Silva, D. (2020). Real-time automated video highlight generation with dual-stream hierarchical growing self-organizing maps. Journal of Real-Time Image Processing. https:\/\/doi.org\/10.1007\/s11554-020-00957-0.","DOI":"10.1007\/s11554-020-00957-0"},{"issue":"3","key":"10056_CR25","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1007\/s10796-019-09911-3","volume":"21","author":"P Gupta","year":"2019","unstructured":"Gupta, P., Chauhan, S., & Jaiswal, M. P. (2019). Classification of Smart City research\u2014A descriptive literature review and future research agenda. Information Systems Frontiers, 21(3), 661\u2013685. https:\/\/doi.org\/10.1007\/s10796-019-09911-3.","journal-title":"Information Systems Frontiers"},{"key":"10056_CR26","volume-title":"The vision of a smart city (BNL-67902; 04042)","author":"RE Hall","year":"2000","unstructured":"Hall, R. E., Bowerman, B., Braverman, J., Taylor, J., Todosow, H., & Von Wimmersperg, U. (2000). The vision of a smart city (BNL-67902; 04042). Upton, NY (US): Brookhaven National Lab https:\/\/www.osti.gov\/biblio\/773961."},{"key":"10056_CR27","unstructured":"Hebb, D, O. (1949). The organization of behavior; a neuropsychological theory. Wiley."},{"key":"10056_CR28","doi-asserted-by":"publisher","unstructured":"Jayaratne, M., Alahakoon, D., Silva, D, D., & Yu, X. (2017). Apache spark based distributed self-organizing map algorithm for sensor data analysis. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, 8343\u20138349. https:\/\/doi.org\/10.1109\/IECON.2017.8217465","DOI":"10.1109\/IECON.2017.8217465"},{"key":"10056_CR29","doi-asserted-by":"publisher","unstructured":"Jayaratne, M., Silva, D. de, & Alahakoon, D. (2019). Unsupervised machine learning based scalable fusion for active perception. IEEE Transactions on Automation Science and Engineering, 1\u201311. https:\/\/doi.org\/10.1109\/TASE.2019.2910508.","DOI":"10.1109\/TASE.2019.2910508"},{"key":"10056_CR30","doi-asserted-by":"crossref","unstructured":"Jones, S., Irani, Z., Sivarajah, U., & Love, P, E. (2017). Risks and rewards of cloud computing in the UK public sector: A reflection on three Organisational case studies. Information Systems Frontiers, 1\u201324.","DOI":"10.1007\/s10796-017-9756-0"},{"issue":"3","key":"10056_CR31","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s10796-019-09930-0","volume":"21","author":"AK Kar","year":"2019","unstructured":"Kar, A. K., Ilavarasan, V., Gupta, M. P., Janssen, M., & Kothari, R. (2019). Moving beyond smart cities: Digital nations for social innovation & sustainability. Information Systems Frontiers, 21(3), 495\u2013501.","journal-title":"Information Systems Frontiers"},{"issue":"4","key":"10056_CR32","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1159\/000377679","volume":"1","author":"AA Khadartsev","year":"2014","unstructured":"Khadartsev, A. A., & Eskov, V. M. (2014). Chaos theory and self-Organization Systems in Recovery Medicine: A scientific review. Integrative Medicine International, 1(4), 226\u2013233. https:\/\/doi.org\/10.1159\/000377679.","journal-title":"Integrative Medicine International"},{"issue":"2","key":"10056_CR33","doi-asserted-by":"publisher","first-page":"36","DOI":"10.3390\/jimaging4020036","volume":"4","author":"BR Kiran","year":"2018","unstructured":"Kiran, B. R., Thomas, D. M., & Parakkal, R. (2018). An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos. Journal of Imaging, 4(2), 36. https:\/\/doi.org\/10.3390\/jimaging4020036.","journal-title":"Journal of Imaging"},{"issue":"1","key":"10056_CR34","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1109\/ICNN.1996.548907","volume":"1","author":"K Kiviluoto","year":"1996","unstructured":"Kiviluoto, K. (1996). Topology preservation in self-organizing maps. Proceedings of International Conference on Neural Networks (ICNN\u201996), 1(1), 294\u2013299. https:\/\/doi.org\/10.1109\/ICNN.1996.548907.","journal-title":"Proceedings of International Conference on Neural Networks (ICNN\u201996)"},{"key":"10056_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/IJCNN.2019.8852471","volume":"2019","author":"D Kleyko","year":"2019","unstructured":"Kleyko, D., Osipov, E., Silva, D. D., Wiklund, U., & Alahakoon, D. (2019). Integer self-organizing maps for digital hardware. International Joint Conference on Neural Networks (IJCNN), 2019, 1\u20138. https:\/\/doi.org\/10.1109\/IJCNN.2019.8852471.","journal-title":"International Joint Conference on Neural Networks (IJCNN)"},{"key":"10056_CR36","doi-asserted-by":"crossref","unstructured":"Kohonen, T. (1997). Exploration of very large databases by self-organizing maps. Neural Networks, 1997., International Conference On, 1, PL1-PL6 vol. 1.","DOI":"10.1109\/ICNN.1997.611622"},{"issue":"2","key":"10056_CR37","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1109\/MITS.2018.2806634","volume":"10","author":"I Lana","year":"2018","unstructured":"Lana, I., Ser, J. D., Velez, M., & Vlahogianni, E. I. (2018). Road traffic forecasting: Recent advances and new challenges. IEEE Intelligent Transportation Systems Magazine, 10(2), 93\u2013109. https:\/\/doi.org\/10.1109\/MITS.2018.2806634.","journal-title":"IEEE Intelligent Transportation Systems Magazine"},{"issue":"2","key":"10056_CR38","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/s10796-014-9492-7","volume":"17","author":"S Li","year":"2015","unstructured":"Li, S., Da Xu, L., & Zhao, S. (2015). The internet of things: A survey. Information Systems Frontiers, 17(2), 243\u2013259.","journal-title":"Information Systems Frontiers"},{"issue":"6","key":"10056_CR39","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1016\/j.ijinfomgt.2012.04.001","volume":"32","author":"A Lin","year":"2012","unstructured":"Lin, A., & Chen, N.-C. (2012). Cloud computing as an innovation: Percepetion, attitude, and adoption. International Journal of Information Management, 32(6), 533\u2013540. https:\/\/doi.org\/10.1016\/j.ijinfomgt.2012.04.001.","journal-title":"International Journal of Information Management"},{"key":"10056_CR40","unstructured":"Liu, B. (2018). Natural intelligence\u2014The human factor in AI."},{"key":"10056_CR41","doi-asserted-by":"crossref","unstructured":"Liu, W, C., & Lin, C, H. (2017). A hierarchical license plate recognition system using supervised K-means and support vector machine. 2017 international conference on applied system innovation (ICASI), 1622\u20131625.","DOI":"10.1109\/ICASI.2017.7988244"},{"key":"10056_CR42","doi-asserted-by":"publisher","unstructured":"Lu, C., Shi, J., & Jia, J. (2013). Abnormal event detection at 150 FPS in MATLAB. 2013 IEEE international conference on computer vision, 2720\u20132727. https:\/\/doi.org\/10.1109\/ICCV.2013.338.","DOI":"10.1109\/ICCV.2013.338"},{"key":"10056_CR43","doi-asserted-by":"publisher","first-page":"1975","DOI":"10.1109\/CVPR.2010.5539872","volume":"2010","author":"V Mahadevan","year":"2010","unstructured":"Mahadevan, V., Li, W., Bhalodia, V., & Vasconcelos, N. (2010). Anomaly detection in crowded scenes. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, 1975\u20131981. https:\/\/doi.org\/10.1109\/CVPR.2010.5539872.","journal-title":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition"},{"key":"10056_CR44","unstructured":"Marinescu, D, C. (2017). Cloud computing: Theory and practice. Morgan Kaufmann."},{"issue":"8\u20139","key":"10056_CR45","doi-asserted-by":"publisher","first-page":"1041","DOI":"10.1016\/S0893-6080(02)00078-3","volume":"15","author":"S Marsland","year":"2002","unstructured":"Marsland, S., Shapiro, J., & Nehmzow, U. (2002). A self-organising network that grows when required. Neural Networks, 15(8\u20139), 1041\u20131058.","journal-title":"Neural Networks"},{"key":"10056_CR46","doi-asserted-by":"publisher","first-page":"100206","DOI":"10.1016\/j.imu.2019.100206","volume":"16","author":"NA Melo Riveros","year":"2019","unstructured":"Melo Riveros, N. A., Cardenas Espitia, B. A., & Aparicio Pico, L. E. (2019). Comparison between K-means and self-organizing maps algorithms used for diagnosis spinal column patients. Informatics in Medicine Unlocked, 16, 100206. https:\/\/doi.org\/10.1016\/j.imu.2019.100206.","journal-title":"Informatics in Medicine Unlocked"},{"issue":"1","key":"10056_CR47","doi-asserted-by":"publisher","first-page":"103237","DOI":"10.1016\/j.im.2019.103237","volume":"57","author":"P Mikalef","year":"2020","unstructured":"Mikalef, P., Pappas, I. O., Krogstie, J., & Pavlou, P. A. (2020). Big data and business analytics: A research agenda for realizing business value. Information & Management, 57(1), 103237.","journal-title":"Information & Management"},{"key":"10056_CR48","doi-asserted-by":"publisher","first-page":"60376","DOI":"10.1109\/ACCESS.2019.2913784","volume":"7","author":"N Mohammad","year":"2019","unstructured":"Mohammad, N., Muhammad, S., Bashar, A., & Khan, M. A. (2019). Formal analysis of human-assisted smart city emergency services. IEEE Access, 7, 60376\u201360388.","journal-title":"IEEE Access"},{"key":"10056_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TITS.2019.2924883","volume":"20","author":"D Nallaperuma","year":"2019","unstructured":"Nallaperuma, D., Nawaratne, R., Bandaragoda, T., Adikari, A., Nguyen, S., Kempitiya, T., Silva, D. D., Alahakoon, D., & Pothuhera, D. (2019). Online incremental machine learning platform for big data-driven smart traffic management. IEEE Transactions on Intelligent Transportation Systems, 20, 1\u201312. https:\/\/doi.org\/10.1109\/TITS.2019.2924883.","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10056_CR50","doi-asserted-by":"publisher","unstructured":"Nawaratne, R., Bandaragoda, T., Adikari, A., Alahakoon, D., De Silva, D., & Yu, X. (2017). Incremental knowledge acquisition and self-learning for autonomous video surveillance. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, 4790\u20134795. https:\/\/doi.org\/10.1109\/IECON.2017.8216826","DOI":"10.1109\/IECON.2017.8216826"},{"key":"10056_CR51","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1016\/j.future.2018.02.049","volume":"86","author":"R Nawaratne","year":"2018","unstructured":"Nawaratne, R., Alahakoon, D., De Silva, D., Chhetri, P., & Chilamkurti, N. (2018). Self-evolving intelligent algorithms for facilitating data interoperability in IoT environments. Future Generation Computer Systems, 86, 421\u2013432. https:\/\/doi.org\/10.1016\/j.future.2018.02.049.","journal-title":"Future Generation Computer Systems"},{"key":"10056_CR52","doi-asserted-by":"publisher","unstructured":"Nawaratne, R., Alahakoon, D., Silva, D. D., & Yu, X. (2019a). Spatiotemporal anomaly detection using deep learning for real-time video surveillance. IEEE Transactions on Industrial Informatics, 16, 1\u20131\u20131\u2013402. https:\/\/doi.org\/10.1109\/TII.2019.2938527.","DOI":"10.1109\/TII.2019.2938527"},{"key":"10056_CR53","doi-asserted-by":"publisher","unstructured":"Nawaratne, Rashmika, Alahakoon, D., De Silva, D., Kumara, H., & Yu, X. (2019b). Hierarchical two-stream growing self-organizing maps with transience for human activity recognition. IEEE Transactions on Industrial Informatics, 1\u20131. https:\/\/doi.org\/10.1109\/TII.2019.2957454.","DOI":"10.1109\/TII.2019.2957454"},{"key":"10056_CR54","doi-asserted-by":"publisher","unstructured":"Nawaratne, Rashmika, Alahakoon, D., De Silva, D., & Yu, X. (2019c). HT-GSOM: Dynamic self-organizing map with transience for human activity recognition. 2019 IEEE 17th international conference on industrial informatics (INDIN), 1, 270\u2013273. https:\/\/doi.org\/10.1109\/INDIN41052.2019.8972260.","DOI":"10.1109\/INDIN41052.2019.8972260"},{"key":"10056_CR55","doi-asserted-by":"crossref","unstructured":"Pappas, I, O., Mikalef, P., Giannakos, M, N., Krogstie, J., & Lekakos, G. (2018). Big data and business analytics ecosystems: Paving the way towards digital transformation and sustainable societies. Springer.","DOI":"10.1007\/s10257-018-0377-z"},{"issue":"6","key":"10056_CR56","first-page":"e1331","volume":"9","author":"W Peng","year":"2019","unstructured":"Peng, W., Adikari, A., Alahakoon, D., & Gero, J. (2019). Discovering the influence of sarcasm in social media responses. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(6), e1331.","journal-title":"Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"},{"issue":"1","key":"10056_CR57","doi-asserted-by":"publisher","first-page":"e2931","DOI":"10.1002\/ett.2931","volume":"28","author":"R Petrolo","year":"2017","unstructured":"Petrolo, R., Loscr\u00ec, V., & Mitton, N. (2017). Towards a smart city based on cloud of things, a survey on the smart city vision and paradigms. Transactions on Emerging Telecommunications Technologies, 28(1), e2931. https:\/\/doi.org\/10.1002\/ett.2931.","journal-title":"Transactions on Emerging Telecommunications Technologies"},{"key":"10056_CR58","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1109\/ISIE.2011.5984262","volume":"2011","author":"DD Silva","year":"2011","unstructured":"Silva, D. D., Yu, X., Alahakoon, D., & Holmes, G. (2011). Incremental pattern characterization learning and forecasting for electricity consumption using smart meters. IEEE International Symposium on Industrial Electronics, 2011, 807\u2013812. https:\/\/doi.org\/10.1109\/ISIE.2011.5984262.","journal-title":"IEEE International Symposium on Industrial Electronics"},{"key":"10056_CR59","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.jbusres.2016.08.001","volume":"70","author":"U Sivarajah","year":"2017","unstructured":"Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of big data challenges and analytical methods. Journal of Business Research, 70, 263\u2013286.","journal-title":"Journal of Business Research"},{"key":"10056_CR60","unstructured":"Tan, P, N., Steinbach, M., & Kumar, V. (2016). Introduction to data mining. Pearson Education India."},{"issue":"6","key":"10056_CR61","doi-asserted-by":"publisher","first-page":"868","DOI":"10.18178\/ijmlc.2019.9.6.885","volume":"9","author":"OO Varlamov","year":"2019","unstructured":"Varlamov, O. O., Chuvikov, D. A., Adamova, L. E., Petrov, M. A., Zabolotskaya, I. K., & Zhilina, T. N. (2019). Logical, philosophical and ethical aspects of AI in medicine. International Journal of Machine Learning and Computing, 9(6), 868\u2013873.","journal-title":"International Journal of Machine Learning and Computing"},{"key":"10056_CR62","doi-asserted-by":"publisher","unstructured":"Wang, T., & Snoussi, H. (2012). Histograms of optical flow orientation for visual abnormal events detection. 2012 IEEE ninth international conference on advanced video and signal-based surveillance, 13\u201318. https:\/\/doi.org\/10.1109\/AVSS.2012.39.","DOI":"10.1109\/AVSS.2012.39"},{"issue":"2","key":"10056_CR63","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s10796-008-9130-3","volume":"12","author":"L Wang","year":"2010","unstructured":"Wang, L., Xu, L., Liu, R., & Wang, H. H. (2010). An approach for moving object recognition based on BPR and CI. Information Systems Frontiers, 12(2), 141\u2013148.","journal-title":"Information Systems Frontiers"},{"issue":"2","key":"10056_CR64","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1088\/0954-898X_2_2_003","volume":"2","author":"CS Webber","year":"1991","unstructured":"Webber, C. S. (1991). Competitive learning, natural images and cortical cells. Network: Computation in Neural Systems, 2(2), 169\u2013187.","journal-title":"Network: Computation in Neural Systems"},{"key":"10056_CR65","unstructured":"World population projection by UN. (2018). UN DESA | United Nations Department of Economic and Social Affairs. https:\/\/www.un.org\/development\/desa\/en\/news\/population\/2018-revision-of-world-urbanization-prospects.html"},{"key":"10056_CR66","doi-asserted-by":"publisher","first-page":"976","DOI":"10.1016\/j.future.2017.12.012","volume":"108","author":"J Yang","year":"2020","unstructured":"Yang, J., Han, Y., Wang, Y., Jiang, B., Lv, Z., & Song, H. (2020). Optimization of real-time traffic network assignment based on IoT data using DBN and clustering model in smart city. Future Generation Computer Systems, 108, 976\u2013986.","journal-title":"Future Generation Computer Systems"}],"container-title":["Information Systems Frontiers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-020-10056-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10796-020-10056-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-020-10056-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,3]],"date-time":"2023-02-03T02:19:49Z","timestamp":1675390789000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10796-020-10056-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,26]]},"references-count":66,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["10056"],"URL":"https:\/\/doi.org\/10.1007\/s10796-020-10056-x","relation":{},"ISSN":["1387-3326","1572-9419"],"issn-type":[{"value":"1387-3326","type":"print"},{"value":"1572-9419","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,26]]},"assertion":[{"value":"26 August 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}