Gashi, Andi
(2024)
Smart monitoring system for automatic tensioning device through object detection neural network.
[Laurea magistrale], Università di Bologna, Corso di Studio in
Ingegneria elettronica [LM-DM270], Documento full-text non disponibile
Il full-text non è disponibile per scelta dell'autore.
(
Contatta l'autore)
Abstract
This thesis introduces Spiroll, an innovative device prepared for integration into railway systems. With Spiroll’s unique hardware-software co-design it is necessary to implement a real-time monitoring and control system by using Artificial Intelligence solutions combining information from different electronic components, such as temperature sensors and a USB camera. The coalescence of these driving technologies not only provides instantaneous data but also facilitates the foundation for a user friendly web app. This app empowers operators to efficiently supervise Spiroll’s functions, marking a significant leap in visioning high-tension cables within railway systems. The thesis navigates the conception, design, and implementation of Spiroll, unveiling an original paradigm in railway infrastructure management.
Abstract
This thesis introduces Spiroll, an innovative device prepared for integration into railway systems. With Spiroll’s unique hardware-software co-design it is necessary to implement a real-time monitoring and control system by using Artificial Intelligence solutions combining information from different electronic components, such as temperature sensors and a USB camera. The coalescence of these driving technologies not only provides instantaneous data but also facilitates the foundation for a user friendly web app. This app empowers operators to efficiently supervise Spiroll’s functions, marking a significant leap in visioning high-tension cables within railway systems. The thesis navigates the conception, design, and implementation of Spiroll, unveiling an original paradigm in railway infrastructure management.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Gashi, Andi
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
CURRICULUM ELECTRONICS FOR INTELLIGENT SYSTEMS, BIG-DATA AND INTERNET OF THINGS
Ordinamento Cds
DM270
Parole chiave
Raspberry Pi 4B,TensorFlow,TFLite,Web app,Spiroll
Data di discussione della Tesi
18 Marzo 2024
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Gashi, Andi
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
CURRICULUM ELECTRONICS FOR INTELLIGENT SYSTEMS, BIG-DATA AND INTERNET OF THINGS
Ordinamento Cds
DM270
Parole chiave
Raspberry Pi 4B,TensorFlow,TFLite,Web app,Spiroll
Data di discussione della Tesi
18 Marzo 2024
URI
Gestione del documento: