Pregled bibliografske jedinice broj: 1136231
Markov Model as Approach to Parking Space Occupancy Prediction
Markov Model as Approach to Parking Space Occupancy Prediction // IEICE Proceedings Series 2021
Niš, Srbija: The Institute of Electronics, Information and Communication Engineers, 2021. 9, 4 doi:10.34385/proc.64.ICTF2020_paper_9 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1136231 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Markov Model as Approach to Parking Space Occupancy
Prediction
Autori
Dujić Rodić, Lea ; Perković, Toni ; Zupanović, Tomislav ; Solić, Petar
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
IEICE Proceedings Series 2021
/ - : The Institute of Electronics, Information and Communication Engineers, 2021
Skup
IEICE Information and Communication Technology Forum 2020
Mjesto i datum
Niš, Srbija, 10.09.2020. - 12.09.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Smart Parking, HMM, Viterbi, LoRa, RSSI, SNR
Sažetak
One of the most important infrastructures that enable IoT-based Smart Cities is Smart Parking. This paper introduces a machine learning technique based on Hidden Markov Model that applies a Viterbi algorithm for predicting occupancy lot status based solely on collected LoRa RSSI and SNR values.
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
