• P.A.Mathina

Sensor nodes need to collect data periodically and transmit them to the data sink through multi-hops. The clustering method generally has better traffic load balancing than the tree data gathering method. Data compression, based on compressive sensing (CS) theory, is the best form of data aggregation, which has recently been receiving focal attention owing to its ability to reduce global communication cost without incurring intensive computation or transmission overhead. In the Proposed method, the nodes close to the leaf nodes transmit the original data using CS method. Principal Component Analysis (PCA) technique is used for dimensionality reduction and data classification. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly correlated variables.

PCA (Principal Component Analysis) ,CS (compressive sensing ) ,Sensor, Multi-hop

"PRINCIPAL COMPONENT ANALYSIS BASED COMPRESSED DATA SENSING FOR WSN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.315-318, February-2019, Available :http://www.jetir.org/papers/JETIR1902357.pdf

"PRINCIPAL COMPONENT ANALYSIS BASED COMPRESSED DATA SENSING FOR WSN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp315-318, February-2019, Available at : http://www.jetir.org/papers/JETIR1902357.pdf