Identification of Carbon Monoxide Levels
Bane Raman Raghunath1, Sonar Pratik2, Bane Megha R.3, Walke Sourabh4

1Bane Raman Raghunath*, Computer Engineering Department, Gharda Institute of Technology, Lavel, Tal- Khed, Dist- Ratnagiri, India.
2Sonar Pratik, Research Developer, Tata Consultancy Service (TCS), Pune, City- Pune, India.
3Bane Megha R., Reseach Scolar, Electronics Engineering Department, Shivaji University, Kolhapury, City, Kolhapu, Country, India.
4Walke Sourabh, Software Engineer, Pune, City- Pune, India.
Manuscript received on January 13, 2020. | Revised Manuscript received on January 21, 2020. | Manuscript published on February 10, 2020. | PP: 883-890 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1137029420/2020©BEIESP | DOI: 10.35940/ijitee.D1137.029420
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Abstract: With ever rising emission of pollutant gases from different sources like factories, auto mobiles and power, it is a subject of emerging concerns that some strong measures are required to monitor and control these pollutant. Breathing of these gases may cause serious harmful effects to anyone. In these gases, Carbon Monoxide (CO) is often called “Silent Killer” as being colour-less, odour-less and poisonous, it is undetectable by humans. When inhaled it, it deprives blood stream of oxygen and suffocates its victim. In this paper we are proposing a simple system to monitor Carbon Monoxide (CO). Carbon Monoxide (CO) detectors are used to detect CO. This paper also discusses analysis of amount of these CO based a data set from Kaggle and prediction of possible amount of CO in air using regression. The prediction accuracy which is measured as RMSE is 0.17766. 
Keywords: Pollutant Monitoring, Pollution, Air Quality, Pollution Control, CO Emission.
Scope of the Article:  Health Monitoring and Life Prediction of Structures