Intelligent Detection Algorithm for Fall from Height Based on Support Vector Machines

다국어 초록 (Multilingual Abstract)

Among the “five major injuries” in the construction industry—namely, falls from height, electric shock, objectstrike, mechanical injury, and collapse—fall accidents from height exhibit the highest incidence rate and posesignificant dangers. To mitigate the frequency of fall accidents, a fall detection algorithm was developed basedon three-axis acceleration sensors. This intelligent algorithm analyzes the acceleration data of the human bodyduring different motion states. It extracts eigenvalues from the acceleration data, processes and analyzes themusing the support vector machine method, and performs data classification to determine if a person hasundergone a fall. Through experimental testing and validation, this method has demonstrated a high level ofreliability in the detection of falling behavior. The accuracy of this algorithm surpasses that of traditionalthreshold detection methods and decision tree-based algorithms. This enhancement improves its potential forapplication in the detection of falls from heights in construction settings.