Abstract
Internet of Things (IoT) is a budding field. It finds its base in the science of electronic equipments, communication technologies and computing algorithms. It is the network of physical devices, vehicles, home appliances and other items embedded with electronics, software, sensors, actuators, and connectivity which enable these objects to connect and exchange data. All things on the IoT may develop a data overflow that encompasses various types of relevant information. Data can be generated as a result of communication between humans, between human and systems, and between systems themselves. This data can be used to improve the services offered by IoT and thus it becomes important to work on the IoT generated data. This paper presents a model for implementing an IoT system, collecting data from it and performing data analytics on the collected data with the intent of deducing knowledge from this data. This paper also proposes some new areas where IoT can be put to use, thus bringing in sight a ground-breaking view of what IoT can and will do. This, in turn, will change the way we live, work and communicate. The hurdles that may come in the way of implementing IoT have also been discussed in this paper. Finally, the methods of analyzing IoT data have also been discussed with focus on frequent pattern mining. Implementation and results of our work have been shown vividly.
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Shafi, M., Shah, S.Z.A., Amjad, M. (2020). Modeling Internet of Things Data for Knowledge Discovery. In: Hemanth, D.J., Kumar, V.D.A., Malathi, S., Castillo, O., Patrut, B. (eds) Emerging Trends in Computing and Expert Technology. COMET 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-030-32150-5_45
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