Recommendation Ranking via User Interaction Scoring
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Solution Overview
Problem
Building management systems (BMS) generate numerous recommendations that are difficult for operators to prioritize effectively due to overwhelming quantities, making it challenging to determine which recommendations should be addressed first.
Innovation Solution
A method and system for ranking recommendations based on context data, including user interest, current space utilization, environmental preferences, and organizational grouping, to calculate a score that determines the priority and display of recommendations, ensuring that the most impactful ones are emphasized.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a BMS generates numerous recommendations to improve building operations, then the comprehensiveness of recommendations is improved, but the difficulty of prioritizing and managing them increases
Solution Approach 1:
The patent segments the large set of recommendations by calculating priority scores for each individual recommendation based on multiple factors (energy impact, cost, implementation complexity, etc.). This divides the overwhelming list into manageable, ranked segments that operators can address systematically, resolving the contradiction between comprehensive coverage and ease of prioritization.
Solution Approach 2:
The patent introduces new parameters (priority scores derived from energy impact, cost, complexity, and other factors) to transform the recommendation management approach. By changing from a simple list to a scored ranking system, operators can easily identify and prioritize high-impact recommendations without being overwhelmed by the total number of suggestions.
2Measurement precision
If a BMS provides detailed context data for each recommendation, then the quality of decision-making is improved, but the complexity of the system increases
Solution Approach 1:
The patent extracts only the most relevant context data needed for priority calculation (energy impact, cost, complexity metrics) from the vast amount of building operation data. This selective extraction provides sufficient decision-making quality without requiring the system to process and display all available data, thus managing complexity while maintaining precision.
Solution Approach 2:
The patent introduces priority scores as an intermediary metric that synthesizes multiple complex factors (energy consumption, cost implications, implementation complexity) into a single manageable value. This intermediary simplifies the decision-making process by translating complex multi-dimensional data into an easily interpretable ranking system.
Data Source
AI summary
A method of ranking recommendations includes receiving a recommendation to improve asset utilization of at least one asset, detecting, via one or more user interfaces, user interaction with one or more other recommendations related to the recommendation, the user interaction indicating user interest in the one or more other recommendations related to the recommendation, calculating a score for the recommendation based on the user interest in the one or more other recommendations related to the recommendation, and performing an action that affects a utilization of the at least one asset based on at least one of the score or the recommendation.