Pregled bibliografske jedinice broj: 1154249
Machine Learning as Tag Estimation Method for ALOHA- based RFID system
Machine Learning as Tag Estimation Method for ALOHA- based RFID system // 2021 6th International Conference on Smart and Sustainable Technologies (SpliTech)
Bol, Hrvatska: Institute of Electrical and Electronics Engineers (IEEE), 2021. str. 1-6 doi:10.23919/SpliTech52315.2021.9566455 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), ostalo)
CROSBI ID: 1154249 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Machine Learning as Tag Estimation Method for ALOHA-
based RFID system
Autori
Dujić Rodić, Lea ; Stančić, Ivo ; Zovko Kristina ; Šolić, Petar
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), ostalo
Izvornik
2021 6th International Conference on Smart and Sustainable Technologies (SpliTech)
/ - : Institute of Electrical and Electronics Engineers (IEEE), 2021, 1-6
Skup
6th International Conference on Smart and Sustainable Technologies (SpliTech)
Mjesto i datum
Bol, Hrvatska, 08.09.2021. - 11.09.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Internet of Things , RFID tags , RFID reader , Machine Learning , tag estimate method
Sažetak
Massive implementation of Machine Learning (ML) techniques in different domains of IoT brought many different advantages that enhance performances in different usage scenarios. In this paper, use-case feasibility analysis of implementation of ML algorithm for estimating ALOHA-based frame size in Radio Frequncy Identification (RFID) Gen2 system is provided. The results show that the given ML algorithm can be employed on modern state-of-the-art resource constrained microcontrollers where execution time is enough to meet protocol needs, keep-up with the latency and improve system throughput.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
UIP-2017-05-4206 - Internet stvari: istraživanja i primjene (IoTRA) (Šolić, Petar, HRZZ - 2017-05) ( CroRIS)
Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split
