An Advanced IoT Data Collection Service for Data-centric Smart Cities
Ryong Lee1, Minwoo Park2, Sang-Hwan Lee3
1Ryong Lee, Research Data Hub Center, Korea Institute of Science and Technology Information, Daehak-Ro, Yuseong-Gu, Daejeon, Korea, East Asian.
2Minwoo Park, Research Data Hub Center, Korea Institute of Science and Technology Information, Daehak-Ro, Yuseong-Gu, Daejeon, Korea, East Asian.
3Sang-Hwan Lee, Research Data Hub Center, Korea Institute of Science and Technology Information, Daehak-Ro, Yuseong-Gu, Daejeon, Korea, East Asian.
Manuscript received on 20 June 2019 | Revised Manuscript received on 27 June 2019 | Manuscript Published on 22 June 2019 | PP: 323-327 | Volume-8 Issue-8S2 June 2019 | Retrieval Number: H10590688S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: On behalf of the prevalent IoT, Big Data, and AI technologies, the advance of smart cities are being rapidly accelerated based on data which are made out of numerous sensors and used for deep learning techniques to solve various real-world problems instead of humans. However, it is still a difficult problem to collect and integrate data from diverse sources of different forms due to the heterogeneity and the massive volume of data. Methods/Statistical analysis: In order to support the complicated work to collect various IoT data from different types of data sources, particularly relieving burdens to develop and manage one-time collectors, we developed an IoT Data Collection Service System, with which users can easily design their own data collectors and control their working statuses to gather and store IoT data. Especially, the proposed system features a simplified workflow from creation to activation of user-defined data collectors. Findings: In this work, based on an IoT data collection service system for smart cities, we attempted to collect real-time urban sensing data and make them visible on a web-based user interface. The data service requires not only an elaborate procedure to enable users easily to conduct their data collection work, but also hiding the complicated task and overcoming the inherent heterogeneity and complexity of data sources. In particular, it is essential to consider various cases of data collecting scenarios to keep the flexibility and the extendibility of the service. Improvements/Applications: The expected heterogeneity of IoT data sources can be considerably resolved in our data service enabling users to easily collect data and utilize them for supporting higher-levels of data analyses or application services for smart cities.
Keywords: IoT Data Collection, Data Service, Smart City, Heterogeneity, Data Integration
Scope of the Article: Smart Sensors and Internet of Things for Smart City