Resumen
The transportation of cargo inside shipping containers is a risky operation that requires constant monitoring activities and real-time operational actions. Yet, the detection of the real dynamics of the container and the surrounding infrastructure and extraction of true subsequent critical events is still an unresolved issue among engineers. In this paper, we analyze the new physical impact detection method, namely the Impact Detection Methodology (IDM), to detect the most obvious and force-dependent impacts from acceleration data, using the IoT sensor in an experimental environment using the heavy machinery of a seaport. By variating the threshold level, we have observed the changes in the number of impacts detected within three separate case studies. Results suggest that the optimal parameters tend to provide an adequate number of events, yet even the slightest change in the threshold level can increase or decrease the number of detected impacts in a non-linear fashion, making the detection harder, due to unforeseen external impacts on the dataset, the filtering of which is still the main priority of our future research.