Wireless sensor system for chemical and biological parameters monitoring and classification Online publication date: Wed, 29-Jun-2022
by Naser Zaeri; Rusul R. Qasim
International Journal of Sensor Networks (IJSNET), Vol. 39, No. 2, 2022
Abstract: Wireless sensor systems provide powerful structures for monitoring and analysing data in complicated situations over extended periods of time. In this paper, we offer a smart integrated system composed of a number of buoys that are dispersed in the sea and are equipped with suites of sensors that can measure a variety of vital environmental, biological and chemical parameters. The system is a comprehensive and interactive multi-parameter monitoring structure with two-way communication through a wireless mobile network that implements machine learning to detect and categorise the various parameters. In pursuing so, four contemporary algorithms are applied and compared, namely: logistic regression, naïve Bayes, multilayer perceptron, and support vector machines. The experimental findings reveal that the support vector machine performs remarkably well, with best accurate classification rate of 86% with the corresponding weighted average precision, recall, F-score, and MMC of 0.86, 0.86, 0.858, and 0.84, respectively.
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