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A LoRaWAN Tracking System for IoT

Antonio Eva

A LoRaWAN Tracking System for IoT.

Rel. Claudio Ettore Casetti. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022

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This thesis project was realised at Alten Italia R&D department in Bologna, with the intent of implementing an IoT asset-tracking system addressing the underlying principles of Industry 4.0. In global manufacturing and commerce, raw materials, components, and final goods can travel long distances, through warehouses and logistic hubs before arriving at their destination. The deployment of a fleet of programmable IoT devices able to track and store data of many unit loads provides a company valuable information for planning and optimization. This project studies the implementation steps around an IoT device capable to determine and send real-time position and condition of Unit Loads along the supply chain. LoRaWAN¿ was chosen as communication network since it is considered one of the best low-power wide-area (LPWA) networks to wirelessly connect devices to the internet and perfectly meets IoT requirements such as bi-directional communication, end-to-end security, and localization services. The workbench to develop the architecture was The Things Network (TTN) that provides tools to manage end devices and gateways. TTN is a global collaborative IoT ecosystem used by thousands of developers and companies around the world and guarantees free access to LoRaWAN¿ services in more than 150 countries. The tracking device used is the prototype STEVAL-STRKT01 board produced by STMicroelectronics that fully responds to compactness, low cost and low power consuming requirements. It has been programmed to collect positioning, temperature, humidity, pressure, orientation data of a Unit Load through GNSS module and environmental sensors . The access to device data has been guaranteed by MQTT protocol and have been processed with Nodered, a powerful editor to create JavaScript functions. Data are stored on a database from which is possible to retrieve and analyse them on a dashboard. The system was tested through several outdoor tests to prove the scalability of the architecture and it can provide important information on the quality of transport service, reporting the coordinates of critical events, where sensor thresholds are exceeded.

Relators: Claudio Ettore Casetti
Academic year: 2021/22
Publication type: Electronic
Number of Pages: 64
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: ALTEN ITALIA SPA
URI: http://webthesis.biblio.polito.it/id/eprint/23587
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