Abstract: Some embodiments relate to a method and system for determining electrical motor fault comprising: measuring ambient vibration data of the electrical motor and performing spectral processing of the ambient vibration data; filtering noise data from the ambient vibration data, outputting a filtered ground truth vibration spectrum, clustering features of the filtered ground truth vibration spectrum, and determining temporal and spatial distance between the clustered features; measuring electrical data signals of the electrical motor, analysing the electrical data signals to extract features of the electrical data signals and storing the extracted features from the electrical data signal; assigning an operating state label to the ground truth vibration spectrum by comparing the clustered features of the ground truth operational vibration spectrum to a database of stored training data and ground truth algorithms; determining an accuracy of the operating state label; and determining electrical motor fault using a ne

Abstract: The disclosure provides a computer-implemented method of controlling safety operations at a designated site associated with Personal Protective Equipment (PPE) requirements. The method comprises: receiving sensor data from a sensor system monitoring the site; detecting an individual at the site based on the sensor data; identifying one or more items of PPE present on the individual based on the sensor data; determining a compliance score associated with the individual based, at least in part, on the one or more identified items of PPE and a PPE checklist associated with the designated site, the PPE checklist comprising one or more prescribed items of PPE; comparing the compliance score to a safety threshold; and controlling one or more safety operations at the site in dependence on the comparison between the determined compliance score and the safety threshold.

Abstract: A method of performing movement pattern anomaly detection with targeted alerts can include receiving input from each camera of a multi-camera system and for each input: performing video content analysis; generating a critical analysis matrix associated with the input from that camera; assigning a fusion value for each vector of the critical analysis matrix using a fusion map that indicates particular fusion values associated with possible elements of the critical analysis matrix; and triggering an alert according to whether the fusion value exceeds a threshold associated with that camera. The critical analysis matrix includes output from at least two different computer vision algorithms of the video content analysis applied to the input from a camera.

Abstract: A method of performing movement pattern anomaly detection with targeted alerts can include receiving input from each camera of a multi-camera system and for each input: performing video content analysis; generating a critical analysis matrix associated with the input from that camera; assigning a fusion value for each vector of the critical analysis matrix using a fusion map that indicates particular fusion values associated with possible elements of the critical analysis matrix; and triggering an alert according to whether the fusion value exceeds a threshold associated with that camera. The critical analysis matrix includes output from at least two different computer vision algorithms of the video content analysis applied to the input from a camera.