Pro-core Technologies Limited

Indus.ai Inc.

Lai Him Matthew Man

Mohammad Soltani

Ahmed Aly

Walid Aly

Seyedfarid Mirahadi

Jiazi Liu

An example computing platform comprising is configured to (i) receive, via one or more cameras positioned on a construction site, a plurality of images, (ii) detect, within the plurality of images, a plurality of objects being worn by respective workers on the construction site, (iii) select, from the plurality of images, a set of images depicting a particular worker, and (iv) based on the selected set of images depicting the particular worker, determine a plurality of trade probabilities for the particular worker, each trade probability in the plurality of trade probabilities indicating a likelihood that the particular worker belongs to a particular trade from among a plurality of trades.

Neural network-based recognition of trade workers present on industrial sites

A computer-implemented method for monitoring productivity, health and safety risks posed by activities and objects, and other signals present at industrial sites comprises: receiving data inputs from input devices at an industrial site; selecting a data model that is programmed to detect activities or objects associated with workers or equipment present at the industrial sites; applying the data inputs to the data model to receive output data specifying whether the activities or objects associated with workers or equipment are present at the industrial site; and if they are present: based the output data, determining characteristics of the activities or objects; based on the characteristics, determining whether that the activities or objects cause any productivity, health or safety risks at the industrial site; and if so, generating notifications indicating the health or safety risks at the industrial site.

Identifying and monitoring productivity, health, and safety risks in industrial sites

A computer-implemented method and system for neural network-based recognition of trade workers present on industrial sites is presented. In an embodiment, a method comprises: using a computing device, receiving a plurality of digital images depicting a particular worker; using the computing device, based on the plurality of digital images, determining a plurality of key-point sets of the digital images, each of the plurality of key-point sets comprising location information of key points identified within a depiction of the particular worker in a particular digital image; using the computing device, based on the plurality of key-point sets, determining a plurality of trade-specific activities that appear to be performed by the particular worker; using the computing device, based on the plurality of trade-specific activities, determining a plurality of trade probabilities, each trade probability among the trade probabilities indicating a likelihood that the particular worker belongs to a particular trade from among a plurality of different trades.

A computer-implemented method and system for monitoring activities in industrial sites using data models is presented. In an embodiment, a method comprises: using a computing device, receiving a plurality of data inputs from a plurality of data input devices in an industrial site; using the computing device, obtaining access to a data model that has been trained on training data for the industrial site and that is programmed to detect one or more anomalies associated with workers or equipment at the site; using the computing device, applying the plurality of data inputs to the data model and evaluating the data model with the data inputs to result in receiving output data specifying whether the plurality of data inputs indicates one or more anomalies occurring in the industrial site; using the computing device, in response to determining that the output data indicates a set of anomalies, of the one or more anomalies: generating a first set of notifications that corresponds to the set of anomalies occurring in the industrial site; for each first anomaly of the first set of anomalies: generating a first notification that includes a description of a first anomaly of the first set of anomalies; determining one or more first recipients of the first notification; transmitting the first notification to the one or more first recipients.

Monitoring activities in industrial sites

A method and a system for patch-based scene segmentation using neural networks are presented. In an embodiment, a method comprises: using one or more computing devices, receiving a digital image comprising test image; using the one or more computing devices, creating, based on the test image, a plurality of grid patches; using the one or more computing devices, receiving a plurality of classifiers that have been trained to identify one or more materials of a plurality of materials; using the one or more computing devices, for each patch of the plurality of grid patches, labelling each pixel of a patch with a label obtained by applying, to the patch, one or more classifiers from the plurality of classifiers; using the one or more computing devices, generating, based on labels assigned to pixels of the plurality of grid patches, a grid of labels for the test image.

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North York, Canada

Lai Him Matthew Man