Home Appliance Control Using User Activity Space Heat Maps
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Solution Overview
Problem
Conventional methods for controlling home appliances based on user location are limited by the user's immediate location, failing to account for the user's activity radius and space, leading to inefficient appliance control.
Innovation Solution
An electronic device estimates a user's activity space using location data through a millimeter wave sensor, generating a heat map and clustering map to identify high-density areas, allowing for optimal appliance control based on the user's activity radius.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sensors are used to detect user location, then the user's immediate location can be identified, but the user's activity radius and space cannot be accounted for
Solution Approach 1:
The patent transitions from detecting only the user's immediate location (2D point) to estimating the user's activity space (2D area) by analyzing cumulative location data patterns. This dimensional expansion allows the system to recognize not just where the user is, but also the scope of their activity radius and preferred spaces within the home environment.
Solution Approach 2:
The system performs preliminary data collection and analysis by accumulating user location data over time before actual appliance control decisions are made. This preliminary action of building a heat map and identifying activity spaces in advance enables more accurate and timely appliance control without requiring complex real-time calculations.
2Ease of operation
If home appliances are controlled based on immediate user location only, then control can be implemented, but efficient control considering activity radius and space is limited
Solution Approach 1:
The patent applies different control strategies to different spatial zones within the home environment. By dividing the space into high-density activity areas and low-density areas based on heat map analysis, the system can apply localized control rules - for example, appliances in high-density areas may be activated more proactively or with different parameters compared to those in low-density areas, optimizing overall system efficiency.
Solution Approach 2:
The system dynamically adjusts appliance control parameters based on the user's activity space characteristics. Instead of using fixed control rules, the patent modifies operational parameters (such as activation thresholds, timing, or intensity) according to the analyzed activity patterns and space utilization data, thereby improving control efficiency and user experience.
3Area of stationary object
If sensors are installed in large spaces to collect user data, then location information can be obtained, but the system cannot account for walls and blocked spaces
Solution Approach 1:
The patent introduces an intermediary computational layer (the heat map generation and activity space estimation process) that processes raw location data to infer space topology. Rather than relying on direct sensor detection of physical boundaries, the system uses the user's movement patterns as an intermediary to indirectly map out activity spaces and infer wall locations, effectively recovering topology information that would otherwise be lost.
Data Source
AI summary
An electronic device can include a memory configured to store location data of a user, and at least one processor configured to obtain a cumulative location data set based on the location data, the cumulative location data set including information about a number of times the user is detected at one or more locations within a space, generate a heat map representing a location distribution of the user based on the cumulative location data set, and obtain an activity space of the user based on the heat map, the activity space being a region within the space.