Localizacao em ambientes internos utilizando redes Wi-Fi
share
This paper presents a localization method for indoor environments capable of improving the location accuracy that is hampered by instability in RSSI of the IEEE 802.11 networks. The method employs the k-Nearest Neighbors (kNN) algorithm and quartiles analysis in the data representation. The proposal had null error with only four APs and 10 readings per sample of each AP with just 0.69 second to locate. These values are important contributions, confirming that the method is promising to locate objects in indoor environments.
READ FULL TEXT