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Opensource Based IoT Platform and LoRa Communications with Edge Device Calibration for Real-Time Monitoring Systems

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1121))

Abstract

Internet of Things (IoT) is an attractive part of our daily life. However, the development of IoT applications still faces many challenges, such as handling unstructured data, intelligent analytics, connectivity, compatibility and interoperability, integration, and data security and privacy. In this paper, first, a real-time monitoring system is proposed based on opensource platform (called BKThings) and long-range (LoRa) communication technology. Specifically, a LoRa gateway prototype is implemented to collect, store and forward monitored data from the IoT devices. In addition, LoRa end devices are developed, where data calibrations on the low-cost sensors to accurately measure environmental and gas air parameters are integrated. Second, an opensource based IoT platform functional architecture is developed. The implementation includes main functionalists of a typical IoT platform such as user management, device registration, monitoring, connectivity, data acquisition, processing, storage, and visualization on the dashboards. The achieved results demonstrate that the tested implementation of the opensource IoT platform and the LoRa IoT gateway were suitable and scalable for sensing environmental parameters in certain data visualization.

This research is funded by the Ministry of Science and Technology of Vietnam under the framework of “research and development of information technology products for e-Government” (Ref: KC.01/16-20) with the research project titled “Research and development of Internet of Things platform (IoT), application to management of high technology, industrial zones”, the mission code is KC.01.17/16-20.

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Correspondence to Ha Duyen Trung .

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Trung, H.D., Hung, N.T., Trung, N.H. (2020). Opensource Based IoT Platform and LoRa Communications with Edge Device Calibration for Real-Time Monitoring Systems. In: Le Thi, H., Le, H., Pham Dinh, T., Nguyen, N. (eds) Advanced Computational Methods for Knowledge Engineering. ICCSAMA 2019. Advances in Intelligent Systems and Computing, vol 1121. Springer, Cham. https://doi.org/10.1007/978-3-030-38364-0_37

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