Wireless Sensor Networks for Advanced Industrial and Biomedical Applications

Ballerini, Massimo (2020) Wireless Sensor Networks for Advanced Industrial and Biomedical Applications, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Ingegneria elettronica, telecomunicazioni e tecnologie dell'informazione, 32 Ciclo. DOI 10.6092/unibo/amsdottorato/9239.
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Abstract

In the modern industry, data processing systems must be able to receive, aggregate, and process information from different sources to achieve complex tasks of production control and coordination. Examples are the real-time monitoring of the quality and quantity of products, biometric data acquisition in the rehabilitation procedures. Energy efficiency in the data communication system is essential in wireless networks. Reduce power consumption in the data exchange can prolong the operating life of battery-powered devices and save energy on a global scale. In this direction, a fundamental step is to accurately model the energy consumption for data communication over a wireless link for the system of interest. The first part concerns the application scenario of the Body Sensor Network for motion reconstruction applications. Wireless systems that use wearable sensors have developed rapidly in recent years, and the requirements in terms of throughput and timing accuracy are challenging. This thesis presents a new general-purpose Inertial Measure Unit that exploits a dual-core architecture. A core offers processing capability, and the other one is a radio interface IEEE 802.15.4. I propose the whole system and a protocol to maximize the throughput, reduce the packet loss, and improve the robustness of wireless sensor nodes communication. In the second part of the thesis, I move the attention to the Low Power Wide Area Network in the IoT scenario. Today, the most promising long-range communication technologies are LoRaWAN and Narrow Band IoT (NB-IoT), which are driving a vast IoT ecosystem. A dedicated chapter evaluates the performance of LoRaWAN and NB-IoT with accurate in-field measurements using the same monitoring application for a comparison in terms of energy efficiency, lifetime, quality of service (QoS), and coverage. Finally, the last part provides configuration guidelines for future industrial applications with harsh requirements of long-range and low power wireless connectivity.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Ballerini, Massimo
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
32
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Wireless Sensor Network, Inertial Measurement Units, Motion Capture, time-triggered protocol, LPWAN, Long-Range Communcation, NB-IoT, LoRA, LoRaWAN, IoT, IIoT
URN:NBN
DOI
10.6092/unibo/amsdottorato/9239
Data di discussione
25 Marzo 2020
URI

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