Abstract
The lack of air quality monitoring equipment in areas in Indonesia will have a negative impact on health if there is an unconscious decrease in air quality. This study aims to design an air quality monitoring tool using a fuzzy inference system using the Tsukamoto method to provide information in the form of air quality values. By using 3 different types of pollutant sensors, namely MQ2 to detect smoke, MQ7 to detect carbon monoxide (CO) and Sharp GP2YAUF to detect flying dust levels, the data from the readings of each sensor is processed using the fis tsukamoto method to get the result value and category. air quality which then the results will be displayed on a monitoring website as a medium of information. In the process, a series of tools need to be connected to the network in order to be able to carry out the process of sending sensor data into the database, after the data is stored in the database then the website will perform calculations using the Tsukamoto method automatically to get the results of values and categories of air quality that are read by the sensor which then the results will be displayed on the monitoring website. From this research will produce an air quality monitoring tool using the fuzzy inference system Tsukamoto method as a method to determine the results of values and categories. Keywords: Air Quality Monitoring; FIS Tsukamoto method; Fuzzy Logic
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
