Footstep Pattern Sensor for Automatic Device Control
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Solution Overview
Problem
There is a need for technologies that can automatically control electronic devices based on a user's footstep pattern to minimize user interaction and efficiently manage device settings, while also detecting intruders and managing conflicts in device control preferences.
Innovation Solution
A system that uses sensors to detect footstep patterns and weights, identifying registered users and controlling associated electronic devices based on stored control information, and can detect intruders by comparing sensed footstep information with registered patterns, with priority management for conflict resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If footstep pattern recognition is used to identify users and automatically control devices, then user interaction is minimized and automation is improved, but system complexity increases due to sensor integration and pattern matching requirements
Solution Approach 1:
The sensor system is designed to perform multiple functions: detecting footstep patterns for user identification, measuring weight for authentication, and triggering automated device control. This multi-functionality reduces the need for separate systems while achieving high automation levels.
Solution Approach 2:
The system automatically identifies users based on their footstep patterns and weight, then autonomously controls electronic devices without requiring manual input. The sensor network and control system work together to provide self-service automation throughout the process.
2Reliability
If footstep pattern and weight sensing is implemented for user identification, then security is improved through biometric authentication, but measurement precision requirements increase for accurate pattern recognition
Solution Approach 1:
The sensor system acts as an intermediary that captures footstep patterns and weight data, then processes this information through pattern matching algorithms to identify users. This intermediary layer transforms raw sensor data into reliable identification information.
Solution Approach 2:
The system monitors multiple parameters simultaneously (footstep pattern, weight, timing) and uses their combined analysis to improve identification reliability. By changing and monitoring multiple parameters rather than relying on a single measurement, the system achieves higher accuracy.
3Adaptability or versatility
If multiple registered members are supported with individual control preferences, then adaptability is improved for different users, but device complexity increases for managing multiple control profiles and conflict resolution
Solution Approach 1:
The control system is segmented into separate profiles for different registered members, each with their own control preferences and authorized devices. This segmentation allows the system to adapt to multiple users while managing complexity through modular profile management.
Solution Approach 2:
The system includes feedback mechanisms that monitor which members are present and active, automatically adjusting device control based on the current user context. This feedback loop helps manage multiple profiles by dynamically activating only the relevant control set for the current situation.
4Reliability
If intruder detection is added to the footstep sensing system, then security is improved through intrusion detection, but false detection risk increases that may lead to incorrect intruder identification
Solution Approach 1:
The sensor system serves as an intermediary that collects footstep and weight data, then compares this information against registered member profiles to determine whether an intruder is present. This intermediary comparison process helps distinguish between authorized and unauthorized users.
Solution Approach 2:
The system monitors multiple parameters (footstep pattern, weight, timing) and uses deviations from registered profiles to identify potential intruders. By analyzing multiple parameters simultaneously, the system reduces false detections while maintaining reliable intruder detection capability.
Data Source
AI summary
The disclosure is related to controlling electronic devices in a target control area based on a footstep pattern of a registered member. Such controlling may be performed through identifying a person detected by a sensor based on footstep information received from the sensor, obtaining control information associated with the identified registered member, and controlling target devices in the target control area based on the obtained control information.


