Energy Saving Support System with Consumer Acceptability Level Detection
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Solution Overview
Problem
Existing energy saving action plans do not account for individual consumer interest levels, leading to annoyance and reduced effectiveness in energy saving and cost reduction.
Innovation Solution
A system that includes a data terminal and a data providing apparatus to transmit energy consumption-related data, determining a consumer's acceptability level based on button operations and providing tailored information accordingly, incorporating dweller attributes and AIDAS formula stages to enhance engagement and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If energy saving action plans are transmitted to all consumers uniformly, then the system can provide energy saving information to the maximum number of users, but consumers with low interest in energy saving will feel annoyed and the effectiveness of energy saving advice decreases
Solution Approach 1:
The system applies local quality by customizing energy saving information delivery according to each consumer's individual characteristics. It segments consumers based on their energy saving awareness levels and delivers appropriately tailored information - providing detailed energy saving advice to high-awareness consumers while minimizing or simplifying information for low-awareness consumers, thereby reducing annoyance while maintaining effectiveness.
Solution Approach 2:
The system changes the parameter of information delivery by adjusting the content, frequency, and detail level of energy saving advice based on consumer acceptability levels. It dynamically modifies information parameters (such as the amount of data transmitted, the type of recommendations provided, and the timing of notifications) to match each consumer's demonstrated interest and engagement with energy saving initiatives.
2Loss of information
If detailed energy consumption data and frequent recommendations are provided to all consumers, then comprehensive energy saving guidance is achieved, but consumers may feel overwhelmed and annoyed, reducing engagement
Solution Approach 1:
The system applies partial action by selectively providing energy consumption information and recommendations based on consumer needs and preferences. Rather than transmitting all possible energy saving information to every consumer, it delivers only the portion of information that each consumer is likely to find useful and engaging, determined through monitoring of consumer interactions and acceptability level assessments.
Solution Approach 2:
The system implements dynamics by continuously adapting the level and type of information provided to each consumer based on their demonstrated engagement and acceptability levels. It dynamically adjusts information delivery strategies in response to consumer behavior patterns, increasing detail for engaged consumers and reducing it for those showing signs of overload or disinterest.
3Adaptability or versatility
If the system monitors and analyzes consumer button operations to determine acceptability levels, then personalized energy saving information can be provided, but the system complexity and data processing requirements increase
Solution Approach 1:
The system applies self-service by using consumer interactions with the interface (such as button operations, selections, and responses) to automatically determine their own acceptability levels. The system processes this self-generated data to create personalized information profiles without requiring external intervention or complex external databases, allowing consumers to effectively define their own information preferences through their natural interactions.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring consumer responses to energy saving information and using this feedback to adjust future information delivery. It analyzes button operations and interaction patterns as feedback signals, refining the personalization of information over time based on what the consumer accepts, ignores, or actively engages with, thereby improving personalization while managing system complexity through iterative learning.
Data Source
AI summary
An energy saving support system according to an embodiment is configured to provide a consumer, who has an electric load to which electric energy is supplied from an electric power supply system within a house, with energy consumption-related information through a photo frame or the like. The information providing apparatus is configured to acquire an acceptability level, which stepwise indicates a degree of interest of the consumer in the energy consumption-related information, and to determine the energy consumption-related information to be newly provided to the consumer based on the acceptability level.