Schema Translation via Video Object Detection
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Solution Overview
Problem
Manual data entry for tasks such as estimating costs or planning resources in home services is tedious and imprecise, often requiring repeated consultations due to insufficient skill levels of initial assessors.
Innovation Solution
A system utilizing a machine learning model for real-time object detection and attribute determination from video feeds, allowing automated generation and entry of data into a schema, with simultaneous display and editing capabilities between client and master devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual data entry is used for task assessment, then flexibility in consultation is maintained, but productivity is reduced and precision is compromised
Solution Approach 1:
The system enables self-service by allowing the assessment to be performed autonomously through video feed analysis. The machine learning model automatically identifies objects, determines attributes, and populates the schema without requiring manual intervention, thus maintaining consultation flexibility while dramatically improving productivity.
Solution Approach 2:
The patent replaces the mechanical system of manual data entry with an automated computer vision system. The machine learning model processes video feeds to automatically extract object information and populate task schemas, substituting human manual operations with automated digital processing, thereby increasing both efficiency and precision.
2Device complexity
If manual assessment by less skilled persons is used, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent replaces human manual assessment with an automated machine learning-based computer vision system. This substitution eliminates the precision limitations of human assessors while maintaining relative system simplicity through the use of off-the-shelf video feeds and standardized machine learning models for object detection and attribute determination.
3Measurement precision
If repeated consultations are conducted for clarification, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary action by automatically completing the assessment and populating the schema during the initial consultation. The machine learning model processes the video feed in real-time or near-real-time, providing accurate object identification and attribute determination upfront, thereby eliminating the need for repeated consultations and reducing time loss.
4Productivity
If automated machine learning-based assessment is implemented, then productivity is improved and measurement precision is enhanced, but device complexity increases
Solution Approach 1:
The system achieves universality by using a multi-functional machine learning model that performs both object identification and attribute determination within a single integrated framework. This approach consolidates multiple functions into one system, improving productivity and precision while minimizing the increase in device complexity through efficient resource utilization.
Solution Approach 2:
The patent introduces an intermediary schema translator that bridges the machine learning model output and the task management system. This intermediary component simplifies the overall system architecture by handling the translation and integration tasks, thereby managing device complexity while maintaining the benefits of automated assessment.
Data Source
AI summary
Systems, methods, and computer program products are disclosed that include receiving, at a schema translator in communication with a master device, a video feed from a client device. The video feed may be relayed to the master device to allow a substantially simultaneous display of the video feed at the master device. A snapshot from a frame in the video feed may be acquired. An object in the snapshot may be identified during the video feed by a machine learning model and added to a list.