Accenture has been granted a patent for a computer-implemented method that utilizes machine learning to analyze video footage of a human performing tasks. The method identifies gestures, compares them to expected standards, and provides feedback on adherence to standard operating procedures (SOPs). GlobalData’s report on Accenture gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Accenture, was a key innovation area identified from patents. Accenture's grant share as of July 2024 was 59%. Grant share is based on the ratio of number of grants to total number of patents.

Gesture-based standard operating procedure detection using machine learning

Source: United States Patent and Trademark Office (USPTO). Credit: Accenture Plc

The patent US12073027B2 outlines a computer-implemented method and system for gesture-based detection of standard operating procedures (SOPs). The method involves capturing video footage of a human performing a task and processing the images using machine learning (ML) models. Initially, a first set of images is analyzed to identify gestures from a predefined set. If a gesture is detected, a second set of images is processed to classify the gesture type. This classified gesture is then compared to an expected gesture type to assess compliance with the SOP. Feedback regarding this comparison is provided through a user interface, with the first set of images being smaller in number than the second.

Additionally, the patent describes the capability to process multiple videos, allowing for continuous monitoring and evaluation of task performance. If a gesture from a second video does not match the expected type, the system can display alerts and corrective messages. The ML models utilized in this process may include conventional neural networks (CNNs) or residual networks (ResNets). The predefined gesture set is specifically tailored to the SOPs relevant to the task being performed, ensuring that the system is aligned with operational standards. This technology aims to enhance task compliance and efficiency through real-time feedback and monitoring.

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