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Supporting Data Communications in IoT-Enabled Waste Management

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10531))

Abstract

The Internet of Things (IoT) enables Smart Cities with novel services. Such services demand low power, high throughput and low-cost sensor data collection technologies. The number of devices, their variety, the breadth of their distribution, and the number of standards are continuously increasing. In this paper, we explore and critically analyze emerging IoT communication technologies. LoRaWAN has been selected for deployment in the smart waste management system (SWM) for collecting data from smart garbage bins. The paper proposes an architecture for SWM data collection and delivery as part of St. Petersburg pilot of Horizon-2020 bIoTope project. Extensive experiments with actual sensors and smart garbage bins were conducted for stress-testing the LoRaWAN technology, analyzing data rates and power consumption. The paper concludes with lessons learned and LoRaWAN wider deployment feasibility and improvements discussion.

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References

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Acknowledgments

Part of this work has been carried out in the scope of the project bIoTope which is co-funded by the European Commission under the Horizon-2020 program, contract number H2020-ICT-2015/688203 – bIoTope. The research has been carried out with the financial support of the Ministry of Education and Science of the Russian Federation under grant agreement RFMEFI58716X0031.

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Correspondence to Petr Fedchenkov .

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Fedchenkov, P., Zaslavsky, A., Medvedev, A., Anagnostopoulos, T., Sosunova, I., Sadov, O. (2017). Supporting Data Communications in IoT-Enabled Waste Management. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. ruSMART NsCC NEW2AN 2017 2017 2017. Lecture Notes in Computer Science(), vol 10531. Springer, Cham. https://doi.org/10.1007/978-3-319-67380-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-67380-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67379-0

  • Online ISBN: 978-3-319-67380-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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