Abstract
Rapid growth of smart and other Internet of Things (IoT) network devices in urban areas has brought an increase in the demand for bandwidth, as well as efficient and accurate IoT coverage systems. Traditional methods such as conventional sensors or sensors that use wide bandwidth, or WiFi as sensors have limitations in terms of coverage, accuracy, and scalability. In this paper, we propose a novel approach for IoT node coverage using Doppler enabled networks. Doppler enabled networks by leveraging the principles of Doppler shifting enable real-time, energy efficient communication coverage, and monitoring of information flow. By deploying a network of Doppler sensors in convenient and well placed location, we can capture and relay comprehensive data on reduced amounts of data bloat and relatively narrow bandwidth. The relayed Doppler data is processed more easily using advanced signal processing and machine learning techniques to extract valuable coverage information including area, information density, and congestion patterns. Our experimental evaluation demonstrates the effectiveness of a Doppler network in accurately rendering coverage and providing real-time insights for IoT coverage systems. The proposed approach has the potential to significantly enhance coverage capabilities, leading to more efficient systems, reduced congestion, and improved safety on the network. The simulation was built and made over Cooja on Contiki.
F. Mehmeti—Independent Researcher.
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Elmazi, D., Mehmeti, F., Kulla, E. (2024). Implementation and Optimization of Narrow-Band Internet of Things (NB-IoT) Nodes Coverage Using Doppler Effect Shift Chips. In: Barolli, L. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing . 3PGCIC 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 189. Springer, Cham. https://doi.org/10.1007/978-3-031-46970-1_14
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