Online Wireless Sensor System for Prediction of Carbon Monoxide Concentration Using Fuzzy Time Series

摘要

Uncontrollable spread of carbon monoxide (CO) produced from incomplete burning of hydrocarbon materials can affects both work health and safety. A smart system capable of early detection of the carbon monoxide (CO) quantitatively is therefore required. This research performed was aimingto develop a wireless sensor system that capable of transmitting data of CO content in atmosphere to the web server via internet connection. This sensor employed a semiconductor for CO detection installed properly in a remote terminal unit. Convenient computer software was applied for dataacquisition and delivery through online and in real time to a web server using an internet modem. For a web-based prediction of CO total concentration, a Fuzzy Time Series algorithm induced by Pritpal Sing matrix was used. This research used data of CO total concentration collected for twomonths monitoring. The result prediction of CO total concentration was displayed in real time on a dashboard. This prediction is for the next day’s forecast. The results show that the Fuzzy Time Series that is induced by Pritpal Sing matrix has an average error of 2.67%, calculated withits average forecasting error rate (AFER). This error value varies, depending on the number of data and data characteristics.