Abstract: “In many wireless applications, location awareness is of paramount importance and, therefore, there are many algorithms regarding localization problems in literature. Fingerprint-based algorithms are one of them, consisting of two phases; mapping and location estimation. In location estimation phases of some technics based on fingerprint, subfields are used for the purpose of filtering data. A subfield analysis could be complex in applications having big radio maps. In addition to this, unstable RSSI values could make the analysis more difficult. In such a state, different approaches can be used to increase the efficiency. In this paper, an alternative deterministic localization technique suggested by the authors of this paper in an earlier study was explained and then unlike the earlier study, a subfield analysis based on fuzzy was applied with the aim of examining a soft computing approach in localization. The results of the experiments were compared with the results of classical dete”

Keywords: WSN, RSSI, K-Means, KNN, Fuzzy