• Naresh Kumar

Wireless Sensor Networks are critical and vital platforms for the future, particularly with the recent emergence of the idea "Internet of Things." They are utilised in a variety of applications in business, health care, the environment, and the military for monitoring, tracking, and regulating. However, the quality of sensor node data is impacted by anomalies that arise for a variety of causes, including node failures, reading mistakes, odd occurrences, and malicious assaults. As a result, anomaly detection is an essential technique for ensuring the quality of sensor data prior to its use in decision-making. We discuss the difficulties associated with anomaly detection in WSNs and the needs for developing efficient and effective anomaly detection algorithms in this paper. Following that, we examine recent advances in data anomaly detection research in WSNs and group existing detection techniques into five broad categories based on the detection methodologies utilised to construct these systems. The many state-of-the-art models for each class are discussed in detail, as well as their shortcomings, in order to generate suggestions for future developments. Additionally, the studied alternatives are contrasted and rated in terms of their compliance with the specified criteria. Finally, the overall limits of present techniques are highlighted, along with potential avenues for future study.

IOT, Data, Anomaly

"A review on WSN and Data Anomaly ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.1209-1214, July-2018, Available :http://www.jetir.org/papers/JETIR180Z068.pdf

"A review on WSN and Data Anomaly ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp1209-1214, July-2018, Available at : http://www.jetir.org/papers/JETIR180Z068.pdf