3D Home Energy Modeling for Self-Service Assessments
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Solution Overview
Problem
Traditional home energy assessments require professional auditors, which are costly and inconvenient for homeowners, necessitating a more accessible and cost-effective solution for accurate and actionable energy performance insights.
Innovation Solution
A machine with network connectivity and sensors collects video, survey data, and sensor data to create a 3D home energy model, using computer vision and machine learning to analyze structural elements, appliances, and energy-related features, providing personalized recommendations for improvement projects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If professional auditors are used for home energy assessments, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a digital 3D copy of the physical home space using video footage and computer vision technology. This digital twin allows for virtual energy assessment without requiring physical presence of professional auditors, thereby maintaining measurement precision while reducing device complexity and cost.
Solution Approach 2:
The patent replaces the mechanical system of manual inspection by professional auditors with an automated computer vision and machine learning system. The machine learning models automatically analyze video data, thermal images, and sensor data to perform energy assessments, eliminating the need for complex human expert systems.
2Reliability
If professional auditors are used for home energy assessments, then reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent enables homeowners to perform energy assessments themselves using the provided system. The machine collects video, thermal images, and sensor data automatically, and the machine learning models automatically process this data to generate energy assessments. This self-service capability maintains reliability through automated quality control while dramatically improving ease of operation for homeowners.
Solution Approach 2:
The system performs preliminary data collection and processing automatically before the final assessment is generated. Video footage, thermal images, and sensor data are captured and pre-processed in advance, allowing the machine learning models to perform reliable analysis without requiring the homeowner to have specialized knowledge or perform complex operations.
3Measurement precision
If comprehensive data collection methods are used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent implements continuous data collection during a single home tour, where video, thermal images, and sensor data are captured simultaneously and continuously as the machine moves through the space. This continuous action allows comprehensive data collection without requiring multiple separate measurement sessions, thereby improving measurement precision while minimizing time loss.
Solution Approach 2:
The patent merges multiple data collection methods into a single integrated process. Video capture, thermal imaging, and sensor data collection are combined and performed simultaneously during one continuous home assessment tour. This merging allows comprehensive data collection for precise energy modeling without the time penalty of sequential separate measurements.
Data Source
AI summary
A machine has a network interface circuit connected to a network with interconnectivity to a user machine and sensors. A processor is connected to the network interface circuit. A memory is connected to the processor. The memory stores instructions executed by the processor to prompt a user for video of a user home, prompt a user for survey data characterizing the user home, collect sensor data from the sensors, analyze the video of the user home, the survey data characterizing the user home, and the sensor data to produce a user home energy model with a three-dimensional (3D) model of the user home including labeled structural elements, construction materials, appliances, and energy-related features and a list of personalized recommendations for home improvement projects.