Detection of Point Source Pollution with RPLIDAR Sensors

As the human population continues to grow, certain activities continue, which can produce air pollution like transportations, industrial productivity, and garbage incineration. To keep providing the information regarding the pollutant, there are some methods to do it. One example is detecting air pollution through LiDAR sensors. However, many LiDAR sensors are expensive yet provide stable performance. This will bring up the idea to do such an experiment in one of the low-cost LiDAR sensors called RPLIDAR, which many hardware companies have recently tried to develop regarding its data characteristics. This study also learns about the features of point source pollution, which can easily be traced. As a result, the LiDAR sensor can detect point source pollution properly. The data is processed and analyzed using an R programming language with a K-Means clustering method to determine the clusters of pollutants. The result of this study indicates that the low-cost LiDAR sensor can detect any object within angular 0-360 and distance 0-10 meters properly with consistent quality. Also, the pollutant can be clustered and distinguished from another thing.