Power Management Apparatus Using Sensor Log Data for Predictive State Control
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Solution Overview
Problem
Existing power management systems for electrical devices lack efficient automatic activation and power saving features based on comprehensive sensor data analysis, leading to suboptimal power usage and convenience.
Innovation Solution
A power management apparatus that includes an interface circuit and a processor to generate log data from various sensors, determining expected operational states and controlling power supply accordingly, utilizing a sensor combination table to associate sensor states with usage patterns for optimal power state management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automatic activation and power saving features are implemented based on usage history and human detection sensor output, then user convenience is improved, but prediction accuracy for power state switching remains insufficient leading to suboptimal power usage
Solution Approach 1:
The system segments sensor data into multiple categories (human detection sensor output, operation history, environmental sensor data) and processes each segment separately before integrating them. This segmentation allows for more precise analysis of each data type while maintaining overall system convenience.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring sensor data and adjusting power state predictions based on accumulated usage history. The prediction accuracy improves over time as the system learns from past patterns and adjusts its decision-making process accordingly.
2Measurement precision
If multiple sensors are integrated for comprehensive data analysis, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The power management apparatus is designed with multi-functionality to handle diverse sensor types (human detection sensors, environmental sensors) through a unified processing framework. This universal approach allows the system to manage multiple sensor inputs without proportionally increasing complexity, as the same core processing logic handles different sensor data types.
Solution Approach 2:
The system introduces an intermediary processing layer that standardizes and integrates data from multiple sensor sources before feeding it into the prediction algorithm. This intermediary layer acts as a mediator that simplifies the integration process and reduces the overall system complexity by providing a consistent interface for handling diverse sensor inputs.
3Loss of energy
If power management is optimized based on detailed sensor analysis, then power consumption is reduced, but the device may not be ready when needed due to insufficient prediction accuracy
Solution Approach 1:
The system performs preliminary actions by predicting future power state needs based on analyzed sensor data and usage patterns. It proactively transitions the device to appropriate power states in advance, ensuring the device is ready when needed while optimizing power consumption through informed decision-making.
Solution Approach 2:
The system dynamically changes operational parameters (power states) based on real-time sensor data analysis and predicted usage patterns. By adjusting power consumption parameters according to actual needs rather than fixed schedules, the system reduces energy loss while maintaining device readiness through adaptive parameter optimization.
Data Source
AI summary
A power management apparatus for managing a power supply to an electrical device, includes an interface circuit connectable to a plurality of different types of sensors, and a processor configured to generate first log data of states of each of the sensors in a plurality of periods of a day, acquire from the electrical device second log data of operational states of the electrical device in the periods, generate usage data that associates the operational states of the electrical device with the states of each of the sensors and the periods, using the usage data, determine an expected operational state of the electrical device corresponding to current states of each of the sensors and a current period, and control the power supply based on the expected operational state and a current operational state of the electrical device.