Pregled bibliografske jedinice broj: 329983
Location Determination in Indoor Environment based on RSS Fingerprinting and Artificial Neural Network
Location Determination in Indoor Environment based on RSS Fingerprinting and Artificial Neural Network // Proceedings of the 9th International Conference on Telecommunications ConTEL 2007 / Car, Željka ; Kušek , Mario (ur.).
Zagreb: Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu, 2007. str. 301-305 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 329983 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Location Determination in Indoor Environment based on RSS Fingerprinting and Artificial Neural Network
Autori
Stella, Maja ; Russo, Mladen ; Begušić, Dinko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 9th International Conference on Telecommunications ConTEL 2007
/ Car, Željka ; Kušek , Mario - Zagreb : Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu, 2007, 301-305
ISBN
978-953-184-110-8
Skup
9th International Conference on Telecommunications ConTEL 2007
Mjesto i datum
Zagreb, Hrvatska, 13.06.2007. - 15.06.2007
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
wireless sensor networks; position determination; fingerprinting; artificial neural network
Sažetak
Wireless microsensor networks have been identified as one of the most important technologies for the 21st century. Cheap, smart devices with multiple onboard sensors, networked through wireless links and the Internet and deployed in large numbers, provide unprecedented opportunities for instrumenting and controlling homes, cities, and the environment. One of the crucial issues in wireless sensor networks is position determination. In this work a positioning system based on Received Signal Strength (RSS) and WLAN is presented. In indoor environments, received signal strength is a complex function of distance. In this work artificial neural network is used to establish a relationship between RSS and location. The location determination accuracy of the proposed system has been investigated and promising results have been achieved. Although based on WLAN technology, the same positioning technique can be applied to any wireless mobile device or sensor in a wireless sensor networks.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
023-0231924-1660 - NAPREDNE HETEROGENE MREŽNE TEHNOLOGIJE (Begušić, Dinko, MZOS ) ( CroRIS)
023-0231924-1661 - ICT sustavi i usluge temeljeni na integraciji informacija (Rožić, Nikola, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split