Dataset of short-term prediction of CO concentration based on a wireless sensor network.

This CO data is gathered from WSN (Wireless Sensor Network) sensors that is placed in some areas. To make this observation framework run effectively, examining the relationships between factors is required. We can utilize multiple wireless sensor devices. There are three parts of the system, including the sensor device, the sink node device, and the server. We use those devices to acquire data over a three-month period. In terms of the server infrastructure, we utilized an application server, a user interface server, and a database server to store our data. This study built a WSN framework for CO observations. We investigate, analyze, and predict the level of CO, and the results have been collected. The Random Forest algorithm achieved a 0.82 R2 Score.