Waste Scoring System for Resource Usage Benchmarking
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Solution Overview
Problem
Consumers lack a clear means to compare their energy and resource usage to that of comparable households, making it difficult to gauge wastefulness and implement targeted energy-saving measures.
Innovation Solution
A waste scoring system that uses smart home sensor data to calculate a 'waste score' by comparing individual energy and water usage to averages from similar households, providing subcategories for specific usage areas and offering real-time updates and recommendations for improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If smart home sensor systems collect and process detailed usage data from multiple households, then the precision of waste scoring and benchmarking improves, but the complexity of data management and system infrastructure increases
Solution Approach 1:
A central database acts as an intermediary between smart home sensor systems and waste scoring calculations. The database collects, stores, and processes usage data from multiple households, then provides benchmark data to scoring systems. This mediator handles the complexity of data aggregation and management, allowing individual sensor systems to remain relatively simple while achieving precise comparative waste scoring across many households.
2Ease of operation
If waste scores are broken down into detailed subcategories and factors, then the ability to provide targeted energy-saving recommendations improves, but the complexity of data processing and analysis increases
Solution Approach 1:
The waste scoring system segments overall resource usage into distinct subcategories (water consumption, electricity consumption) and further into specific factors (HVAC impact, lights/appliances impact, sprinkler impact). This segmentation allows the system to identify precise areas where energy-saving measures can be targeted. Each factor is calculated separately using specific benchmark data, enabling detailed recommendations while managing processing complexity through modular calculation approaches.
3Speed
If real-time waste score updates are provided to consumers, then the ability to immediately adjust energy consumption habits improves, but the computational resources and data processing requirements increase
Solution Approach 1:
The system provides waste score updates at periodic intervals rather than continuously in real-time. Benchmark data is collected and processed at regular intervals (e.g., hourly, daily), and waste scores are updated and communicated to consumers at these same intervals. This periodic approach provides timely feedback that enables consumers to adjust their energy consumption habits while avoiding the excessive computational burden of continuous real-time processing.
Data Source
AI summary
A method for correlating energy usage data and water usage data to a waste scoring system is described. In one embodiment, the method includes receiving energy usage data and water usage data from a plurality of users, identifying at least one user group from the plurality of users based on predetermined parameters, and calculating average energy usage and average water usage for each of the user groups. The energy usage data and water usage data received for an individual user may then be compared to the calculated average energy usage and calculated average water usage for at least one of the user groups, and a general waste score may be calculated for the individual user. In some cases, a plurality of sub-waste scores may be calculated indicating factors of energy usage and factors of water usage for the individual user.