WSN's Based Noise Evading Decision Support System
Rahim Khan, M. Asif Suryani, Mushtaq Ahmad · 2014
2 Abstract: In different application areas, Wireless sensor networks (WSNs) are used as data acquisition tools for online decision support systems (DSS) but none of the existing techniques tackle noisy data. In this paper, a simplest noise evading algorithm is presented for online DSS that results in enhancing DSS's accuracy. The proposed algorithm has lowest worse case complexity of O (n) compared to O (n /2) of pattern anomaly 2 value (PAV) based algorithm. The proposed mechanism is tested and realized in real agriculture environment where sensor nodes are deployed to collect environmental and soil related data.