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Data Mining for Internet of Things: A Survey
Abstract
It sounds like mission impossible to connect everything on the Earth together via Internet, but Internet of Things (IoT) will dramatically change our life in the foreseeable future, by making many "impossibles" possible. To many, the massive data generated or captured by IoT are considered having highly useful and valuable information. Data mining will no doubt play a critical role in making this kind of system smart enough to provide more convenient services and environments. This paper begins with a discussion of the IoT. Then, a brief review of the features of "data from IoT" and "data mining for IoT' is given. Finally, changes, potentials, open issues, and future trends of this field are addressed.
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“Data mining and machine learning approaches have been used for IoT data processing and analysis [52], [53].”
From Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things (2021) · cites this paper as [52]
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BackgroundA Systematic Review for Smart City Data Analytics
Moustaka, V., Vakali, A. I., & Anthopoulos, L. G. (2018) · ACM Computing Surveys · doi:10.1145/3239566 · Cited by 122
Liu, R. W., Guo, Y., Nie, J., Hu, Q., Xiong, Z., Yu, H., & Guizani, M. (2022) · IEEE Transactions on Green Communications and Networking · doi:10.1109/tgcn.2022.3158004 · Cited by 127
“The previous data mining techniques, developed for traditional IoT systems [27], [28], could be theoretically extended to MIoT.”
MethodDeep Learning in Mobile and Wireless Networking: A SurveyPreprint
Zhang, C., Patras, P., & Haddadi, H. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1803.04311 · Cited by 121
“outlook of deep learning for recommender systems. D 7 7 Yu et al. [33] A survey on networking big data. D Alsheikh et al. [34] A survey on machine learning in wireless sensor networks. D Tsai et al. [35] A survey on data mining in IoT. D Cheng et al. [36] An introductions mobile big data its applications. D 7 Bkassiny…”
BackgroundHe, H., Maple, C. R., Watson, T., Tiwari, A., Mehnen, J., Jin, Y., & Gabryś, B. (2016) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2016.7743900 · Cited by 120
“[41] generalised an architecture of IoT with KDD (Fig.”
BackgroundEnergy Harvesting Techniques for Wireless Sensor Networks/Radio-Frequency Identification: A Review
Alsharif, M. H., Kim, S., & Kuruoğlu, N. (2019) · Symmetry · doi:10.3390/sym11070865 · Cited by 120
“To process these enormous sensor payload, huge processing and analytics capabilities are needed, which, in turn, consumes huge energy resources [7,8].”
BackgroundSystematic survey of big data and data mining in internet of things
Shadroo, S., & Rahmani, A. M. (2018) · Computer Networks · doi:10.1016/j.comnet.2018.04.001 · Cited by 117
“control, and monitor each object on earth (usually called things) via the internet [1, 2, 3, 4, 5].”
BackgroundInfluentialA Distributed Consensus Algorithm for Decision Making in Service-Oriented Internet of Things
Li, S., Oikonomou, G., Tryfonas, T., Chen, T., & Xu, L. D. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2306331 · Cited by 116
“1, a three-layer architecture of the IoT is summarized [1] – [6], [9], [11], [12], which contains three basic layers: 1) the application layer ; 2) the network layer ; and 3) the sensing layer .”
BackgroundEvaluation of design alternatives of End-Of-Life products using internet of things
Joshi, A. D., & Gupta, S. M. (2018) · International Journal of Production Economics · doi:10.1016/j.ijpe.2018.12.010 · Cited by 115
Qays, M. O., Ahmad, I., Abu‐Siada, A., Hossain, M. L., & Yasmin, F. (2023) · Energy Reports · doi:10.1016/j.egyr.2023.01.085 · Cited by 114
Internet of things and data mining: An application oriented survey
Sunhare, P., Chowdhary, R. R., & Chattopadhyay, M. K. (2020) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2020.07.002 · Cited by 123
A multi-stage anomaly detection scheme for augmenting the security in IoT-enabled applications
Garg, S., Kaur, K., Batra, S., Kaddoum, G., Kumar, N., & Boukerche, A. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2019.09.038 · Cited by 112
A Simulation-driven Methodology for IoT Data Mining Based on Edge Computing
Savaglio, C., & Fortino, G. (2021) · ACM Transactions on Internet Technology · doi:10.1145/3402444 · Cited by 110
Ullah, I., Adhikari, D., Su, X., Palmieri, F., Wu, C., & Choi, C. (2024) · Digital Communications and Networks · doi:10.1016/j.dcan.2024.02.007 · Cited by 111
Analyzing challenges to Internet of Things (IoT) adoption and diffusion: An Indian context
Luthra, S., Garg, D., Mangla, S. K., & Berwal, Y. P. S. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2017.12.094 · Cited by 108
Bansal, M., Chana, I., & Clarke, S. (2020) · ACM Computing Surveys · doi:10.1145/3419634 · Cited by 110
“Specifically, we categorize the surveys related to IoTBD into three main categories: (1) surveys on IoT big data analysis [1, 91, 94, 98, 130, 154]; (2) domain-specific surveys on IoTBD [53, 54, 59, 83, 103]; (3) surveys on challenges in IoTBD [23, 37, 43, 76, 78, 134].”
MethodIntelligent integrated sensing and communication: a survey
Zhang, J., Lu, W., Xing, C., Zhao, N., Al‐Dhahir, N., Karagiannidis, G. K., & Yang, X. (2024) · Science China Information Sciences · doi:10.1007/s11432-024-4205-8 · Cited by 119
“IoT aims to connect all things, such as various devices, vehicles, and sensors, via the Internet and facilitate the efficient exchange of information among them [147].”
Towards Efficient Mobile M2M Communications: Survey and Open Challenges
Pereira, C., & Aguiar, A. (2014) · Sensors · doi:10.3390/s141019582 · Cited by 104
“Other M2M communications’ surveys focus mainly in home networks [16], 3GPP Long-Term Evolution (LTE) networks [17], service platforms [18], or data mining techniques [19].”
BackgroundInformation traceability platforms for asset data lifecycle: blockchain-based technologies
Brandín, R., & Abrishami, S. (2021) · Smart and Sustainable Built Environment · doi:10.1108/sasbe-03-2021-0042 · Cited by 121
Montori, F., Bedogni, L., Felice, M. D., & Bononi, L. (2018) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2018.08.002 · Cited by 103
“issue-specific surveys), large attention is devoted to sensor data management and knowledge extraction [24][25][26][27][28][29][30].”
BackgroundDeep learning based underwater acoustic OFDM communications
Zhang, Y., Li, J., Zakharov, Y. V., Li, X., & Li, J. (2019) · Applied Acoustics · doi:10.1016/j.apacoust.2019.04.023 · Cited by 99
“tial research works demonstrate the successful application of deep learning in various communication applications[13, 14].”
BackgroundReviewing Cyber-Physical System as a Part of Smart Factory in Industry 4.0
Sinha, D., & Roy, R. (2020) · IEEE Engineering Management Review · doi:10.1109/emr.2020.2992606 · Cited by 98
“Emerging IT including IoT, IoS, networked control wireless sensor-actuator network (WSAN), data mining [15], [16], big data [17] handling, cloud [18], fog, edge computing, smartphones, smart devices, high-performance computers, 5G/6G communication, high-speed Internet, arti fi cial intelligence (AI)…”
BackgroundTracing Knowledge Development Trajectories of the Internet of Things Domain: A Main Path Analysis
Fu, H., Wang, M., Li, P., Jiang, S., Hu, W., Guo, X., & Cao, M. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2929414 · Cited by 94
“In 2014, Tsai analyzed types of IoT data and the characteristics of data mining, and in another article in the same year, proposed a data mining and intelligent data management framework based on group optimization [20], [54].”
An overview of smart agriculture using internet of things (IoT) and web services
Choudhary, V., Guha, P., Pau, G., & Mishra, S. (2025) · Environmental and Sustainability Indicators · doi:10.1016/j.indic.2025.100607 · Cited by 94
Optimizing Information Freshness in Computing-Enabled IoT Networks
Xu, C., Yang, H. H., Wang, X., & Quek, T. Q. S. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2947419 · Cited by 93
“With the help of IoT, devices can sense and even interact with the physical surrounding environment, thereby providing us with many valuable and remarkable context-aware real time applications at an efficient cost, such as automatic control of electric appliance [5], intelligent transportation network [6], and event m…”
Background
Metadata
- Authors
- Tsai, C.-W., Lai, C.-F., Chiang, M.-C., & Yang, L. T.
- Affiliations
- Chia Nan University of Pharmacy and Science (TW)
- National Chung Cheng University (TW)
- National Sun Yat-sen University (TW)
- Huazhong University of Science and Technology (CN)
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2014
- Volume
- 16
- Issue
- 1
- Pages
- 77-97
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W2041785419
- Cited by
- 620
- References
- 156
- Citations by year
- 2026: 7 · 2025: 17 · 2024: 29 · 2023: 35 · 2022: 44 · 2021: 58 · 2020: 73 · 2019: 87 · 2018: 86 · 2017: 92 · 2016: 55 · 2015: 25 · 2014: 11
- FWCI
- 168.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Keywords
- Internet of Things, data mining, IoT data, big data, smart environments, open problems, future trends
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