Industrial Site Activity Monitoring With Real-Time Anomaly Alerts
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Solution Overview
Problem
Managing large industrial sites is challenging due to the inefficiencies in monitoring safety, efficiency, and accountability, as traditional methods rely heavily on human observation and are prone to errors and distractions, and existing digital systems struggle with processing and timely analysis of vast amounts of data from cameras and sensors.
Innovation Solution
A computer-implemented decision support system that utilizes machine learning, computer vision, and statistical analysis to process data from a distributed network of sensors, including video cameras and digital sensors, to generate real-time alerts and metrics for safety, efficiency, and accountability, with features like person and equipment detection, event recognition, and resource tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital cameras are used to collect video streams and images from industrial sites, then safety monitoring capability is improved, but the complexity of processing and reviewing the collected data increases
Solution Approach 1:
The patent replaces manual review of video streams and images with an automated computerized system that uses machine learning and computer vision algorithms to process and analyze the collected data, thereby maintaining safety monitoring capability while reducing processing complexity
Solution Approach 2:
The patent introduces an intermediary computerized system that acts as a bridge between the cameras and human supervisors, automatically processing and filtering the vast amounts of collected data to present only relevant information, thus reducing the burden on both humans and systems
2Productivity
If computerized systems with servers are deployed to process data from multiple devices, then data processing capability is improved, but the timeliness of results delivery deteriorates
Solution Approach 1:
The patent implements preliminary action by pre-training machine learning models and preparing processing pipelines in advance, allowing the system to quickly process and deliver results when data is received, thereby maintaining high processing capability while improving timeliness
Solution Approach 2:
The patent introduces dynamic elements by implementing real-time processing capabilities and adaptive algorithms that can adjust processing speed and resource allocation based on current workload and urgency, enabling the system to deliver results timely while maintaining high processing capability
3Reliability
If managers and supervisors manually monitor industrial sites, then accountability is maintained, but the ability to observe everything at all times deteriorates
Solution Approach 1:
The patent applies universality by creating a computerized monitoring system that can simultaneously perform multiple functions - tracking persons, physical assets, and deliveries across the entire industrial site at once, thereby maintaining accountability while dramatically improving monitoring coverage beyond what human supervisors can achieve
Data Source
AI summary
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.