Weighting Method in the Risk Recognition
Donghyok Suh, Kun-Soo Oh · Advanced science and technology letters · 2014
This study had each sensor distinguish each event through a fast analysis of the data sensed by each sensor in this condition. For this purpose, clustering was made with sensor data, and first, internal variance of event clus- ter classified by each sensor was calculated, and how this changed with the pas- sage of time was checked. Next, the cluster of each sensor sensing the same event was compared. Through this process, the sensed event could be more clearly distinguished. This study suggested the measure to divide a small quan- tity of sensors when it senses the several events. This measure can be used as application for the small mobile vehicle or robot to sense the peripheral situa- tion.