Crowding Detection Combining Trace Elements from Heterogeneous Wireless Technologies
| Autor: | Fernando Brito e Abreu, Ruben Dias da Silva, Rui Marinheiro |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Engenharia e Tecnologia::Engenharia Eletrotécnica Eletrónica e Informática [Domínio/Área Científica] 02 engineering and technology law.invention Bluetooth law GSM Server 0202 electrical engineering electronic engineering information engineering Wireless 4G SDR Wi-Fi Edge computing business.industry Node (networking) Ciências Naturais::Ciências da Computação e da Informação [Domínio/Área Científica] 020207 software engineering Software-defined radio LoRaWAN 3G Crowding detection 020201 artificial intelligence & image processing business Mobile device Computer network |
| Zdroj: | WPMC |
| DOI: | 10.1109/wpmc48795.2019.9096131 |
| Popis: | Non-invasive crowding detection in quasi-real-time is required for a number of use cases, such as for mitigating tourism overcrowding. The present goal is a low-cost crowding detection technique combining personal trace elements obtained from heterogeneous wireless technologies (4G, 3G, GSM, Wi- Fi and Bluetooth) supported by mobile devices carried by most people. This work proposes detection nodes containing Raspberry-Pi boards equipped with several off-the-shelf Software Defined Radio (SDR) dongles. Those nodes perform spectrum analysis on the bands corresponding to the aforementioned wireless technologies, based on several open source software components. The outcome of this edge computing, performed in each node, is integrated in a cloud server using a Long Range Wide Area Network (LoRaWAN), a recent technology developed for IoT applications. Our preliminary results show that is possible to determine the number of mobile devices in the vicinity of each node, by combining information from several wireless technologies, each with its own detection range and precision. info:eu-repo/semantics/acceptedVersion |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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