WATER QUALITY PREDICTION USING SUPPORT VECTOR MACHINE IN WIRELESS SENSOR NETWORKS

Gopu Lakshmi Anjana, Ch.Suresh Babu

Abstract


In Aquaculture, the yields of the aquatic organism depend on the quality of water. To collect the data from the pond like temperature, dissolved oxygen, pH level, turbidity, carbon dioxide the sensors are placed inside the pond. The detection of water quality can be done using the data classification algorithms. In this project, we have proposed a Support Vector Machine (SVM) classifier to predict the quality of water in wireless sensor networks. The sensor nodes are placed in the pond. Here cluster head based routing protocol is used based on the fractional calculus artificial bee colony algorithm, in which the individual decision trees are merged along the routing path. Then, the results of cluster head-based routing protocol are sent to sink node, in which the proposed SVM classifier is used to classify the water quality parameter. From the results, we proved that, the proposed algorithm achieves the better prediction accuracy as 85%.


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