Alvin Matarozzo
Machine learning based approach to Ultra-WideBand (UWB) indoor localization.
Rel. Marcello Chiaberge, Marina Mondin. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022
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Abstract
Providing an accurate, reliable and low-cost estimate of indoor positioning remains an active area of research, despite the availability of popular localization techniques like Acoustic Systems, Infrared Systems, etc. The aim of this thesis is to introduce a new methodology for indoor localization combining Ultra-WideBand (UWB) technology with Artificial Intelligence (AI). Albeit UWB is not a new technology, it is now being revitalized and employed for wireless connections over short distances. Many companies such as Intel, Xiaomi, Sony, Samsung, Apple and Bosh claim that this technology could prove more successful than Bluetooth as it is faster, cheaper, less power consuming and more secure.
UWB is a short-range wireless communication protocol (like Wi-Fi or Bluetooth) using short radio pulses with large bandwidth
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