Video Audio Analytics for Machine State Detection
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Solution Overview
Problem
Existing methods for determining machine states in large, open worksites such as construction or mine sites are inadequate due to complexity and external variables, making it difficult to analyze images and detect inefficiencies or irregularities in machine operations.
Innovation Solution
A system and method using video and audio analytics that receives sensor data from multiple sources, processes it to determine machine states, and compares these states to modeled states to detect inefficiencies or irregularities, generating responses to address these issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If video analytics are used to monitor machine operations, then detection capability is improved, but the complexity of analyzing images increases due to multiple machine states and external variables
Solution Approach 1:
The patent segments the complex analysis task into multiple specialized models: image processing models for visual data, audio processing models for sound data, and telemetry processing models for operational data. Each model handles a specific type of data and state identification, dividing the overall complex problem into manageable components that can be processed independently and then integrated.
2Measurement precision
If multiple sensor data sources are integrated to determine machine state, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal worksite management system that handles multiple data types (video, audio, telemetry) and multiple machine types through a single integrated platform. The system uses common processing architecture and standardized interfaces to manage diverse sensor inputs, allowing the same system to perform various functions across different machines and worksites without requiring separate specialized systems for each.
Solution Approach 2:
The patent introduces an intermediary processing layer that receives data from multiple sensor sources and translates them into standardized machine state identifiers. This intermediary layer includes specialized processing models that act as mediators between raw sensor data and the final machine state determination, harmonizing different data formats and processing requirements before integration.
3Reliability
If video and audio analytics are used to detect irregularities, then reliability is improved, but loss of time in processing data increases
Solution Approach 1:
The patent employs pre-trained machine learning models and pre-established processing pipelines that are prepared in advance for various machine states and irregularities. The system has pre-defined thresholds, classification rules, and response protocols ready before actual monitoring begins, allowing rapid processing of incoming data without requiring complex real-time decision-making algorithms.
Data Source
AI summary
Systems and methods for analyzing and optimizing worksite operations based on video and or audio data are disclosed. One method includes receiving one or more models relating to a worksite, receiving first sensor data associated with the machine at the worksite, receiving second sensor data associated with an operation of the machine at the worksite, wherein the second sensor data is sourced from a sensor that is different from a sensor sourcing the first sensor data, determining, by the one or more processors, a machine state based at least on the first data and the second data, comparing the determined machine state to a modeled machine state represented by the received one or more models to classify site operations and/or detect an irregularity in site operations or an inefficiency in site operations, and generating a response based at least on the detected irregularity or inefficiency.