Classifier Configuration for Active Reflected Wave Detection
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Solution Overview
Problem
Existing systems for determining a person's state or activity using active reflected wave detectors, such as radar, suffer from poor detection accuracy, particularly in indoor environments, leading to potential hazards when falls are misclassified.
Innovation Solution
A computer-implemented method that involves obtaining a classification of a monitored region within a building, configuring a classifier based on this classification, measuring wave reflections using an active reflected wave detector, and using the configured classifier to determine the person's state or activity based on the measured data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex classification models are used to improve detection accuracy, then classification accuracy is improved, but memory resource requirements increase significantly
Solution Approach 1:
The patent segments the classification task by creating multiple specialized classifier models, each trained for a specific indoor environment type (e.g., bedroom, living room, bathroom). Instead of using one complex model for all environments, the system divides the problem into smaller specialized models that can be selected based on the detected environment type, reducing the memory footprint of any single model while maintaining high classification accuracy.
Solution Approach 2:
The system performs preliminary classification to identify the type of indoor environment before selecting and applying the appropriate specialized classifier model. This preliminary action allows the system to choose the most suitable model for the specific environment, avoiding the need to load and execute a single large complex model for all possible scenarios.
2Device complexity
If a single classifier model is used for all environments, then device complexity is reduced, but classification accuracy deteriorates due to environment-specific variations
Solution Approach 1:
The patent applies local quality by creating classifier models with properties specifically optimized for particular environment types. Each classifier model is trained on data from its specific environment type (e.g., bedroom-specific patterns, living room-specific patterns), giving each model local expertise for its designated environment rather than using a generic model for all environments.
Solution Approach 2:
The system dynamically selects the appropriate classifier model based on the detected environment type. Rather than using a static single model, the system adapts by choosing the most suitable model for the current environment, making the classification process dynamic and environment-aware while keeping individual model structures relatively simple.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances classification detection accuracy by optimizing the classifier for specific indoor environments, reducing false alarms and unnecessary resource consumption, while ensuring accurate fall detection and minimizing hazards.
Implementation Method 1
controlling the active reflected wave detector to measure wave reflections from the region within the building to receive measured wave reflection data
Data Source
AI summary
Embodiments relate to a device, method and system for determining a state or an activity of a person in an environment. The method comprises: obtaining a classification of a region within a building that is monitored by an active reflected wave detector; configuring a classifier based on the classification; controlling the active reflected wave detector to measure wave reflections from the region within the building to receive measured wave reflection data that is obtained by the active reflected wave detector; and using the classifier, after said configuring, to determine the state or the activity of the person using the measured wave reflection data.