4.3 Article

Intelligent Internet of Things gateway supporting heterogeneous energy data management and processing

Publisher

WILEY
DOI: 10.1002/ett.3919

Keywords

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Funding

  1. Ministry of Education, School of Computer Science and Engineering, Kyungpook National University [21A20131600005]
  2. Korea government (MSIT) [2019R1F1A1042721]
  3. National Research Foundation of Korea [2019R1F1A1042721] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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The increasing demand for electrical energy, smart grid, and renewable energy has created opportunities for Electrical Energy Data Management and Processing Systems (EEDMS). However, implementing and maintaining EEDMS is a challenging task, and the heterogeneous energy data generated from residential and commercial sectors pose challenges for standard IoT architecture. In order to overcome these challenges, a scalable multitasking IoT gateway (IoTGW) is proposed, along with a Data Loading and Storing Module (DLSM) that enables a high dynamic distributed framework.
The requisition for electrical energy, smart grid, and renewable energy paradigm extend a new space for Electrical Energy Data Management and Processing Systems (EEDMS), in such a way that can mitigate the consumption of electrical energy. Similarly, the implementation and maintenance of the EEDMS is a challenging task. Moreover, the heterogeneous energy data generated from residential and commercial sector are the leading challenges for standard Internet of Things (IoT) architecture. This contributes enormous energy data preprocessing and analyzing solutions to IoT landscape. To overcome these challenges, we present a scalable multitasking Internet of Things Gateway (IoTGW) for the modern era of IoT by placing reliance on a new entity called Data Loading and Storing Module (DLSM). The provided DLSM module combine with the Gateway module services like orchestrator, flexibility of bridging front end grid, back end grid and fast formatted data trade between sensing domain and application domain enables a high dynamic distributed framework. Specifically, we add Adaboost-Multilayer Perceptron hybrid data classifier module to the proposed work to enhance service provision of IoT gateway toward various IoT application services and protocols to facilitate IoT demands such as multitasking, interoperability, classification, and fast data delivery between different modules. IoTGW is implemented and tested using a real-time IoT data streaming network. The experimental results confirms the superiority of proposed work in terms of scalability to serve novel applications and facilitate broad scope of IoT.

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