Sensor data classification using machine learning algorithm. Issue 2 (17th February 2020)

• Record Type: Journal Article
• Authors: Rose, Lina; Mary, X Anitha
• Is Part Of: Journal of statistics & management systems. Volume 23:Issue 2(2020)
• Page Start: 363
• Page End: 371
• Publication Date: 2020-02-17
• Subjects: 68Q32; Machine learning -- Optic sensor -- Total Dissolved Solvents -- Water quality; Statistics -- Periodicals; Mathematical models -- Periodicals; Mathematical models; Statistics; Periodicals; 519.5
• DOI: 10.1080/09720510.2020.1736319
• Languages: English
• ISSNs: 0972-0510

Abstract

Abstract: Water, the primary source of human existence, vastly occurs in the earth, our home. The major share of water resource comes from ocean and sea which is saline in nature. The remaining constitutes the freshwater or surface water resources on which we depend for our day to day life for domestic uses and consumption. In this context it is very necessary that better quality water ensure for human population and the environmental protection. Among various quality indices, Total Dissolved Solvents are considered as predominant that accounts for hardness and salinity, for the salt organic and inorganic constituents present. The lack of knowledge about the contents prevents common man to use such water or ill treatment of water bodies results in misuse of water resources. The work focuses on an alternative by identifying the solvents present in the water body ensuring to desalinate the particular ionic compound or metal.