CFDDR: A Centralized Faulty Data Detection and Recovery Approach for WSN With Faults Identification

One of the most challenging problems in wireless sensor networks (WSNs) is detecting and recovering faulty data. Due to resource limitations, WSNs are subject to many failures, including hardware (permanent faults), software, and communication failures. To ensure data reliability, the data collected by WSNs must be clean of faults. This article presents a centralized faulty data detection and recovery approach, which can detect, recover, and recognize different types of faults (offset, gain, stuck-at, out of bound, and random faults). It operates in two phases: Faulty data detection and recovery and fault type identification (FTI). After detecting the fault, the faulty data will be discarded and replaced by an estimated value based on the Kalman filter. FTI provides a unique solution by determining the types of faults and report them to the end-user for an application-specific decision-making process. The effectiveness of the proposed approach is demonstrated through experimental results, with comparison to state-of-the-art techniques of the same application.