Mobile Device Proximity Sensor Activation for Usage Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing localization technologies lack adaptability and efficiency in managing virtual perimeters for applications like asset tracking and location-based services, as they do not effectively utilize real-time usage data to optimize physical environment maintenance and billing.
Innovation Solution
A system that detects mobile devices in proximity to a physically divided environment, activates sensors to collect usage data, determines usage patterns, and manages interactions or maintenance based on these patterns, allowing for targeted maintenance and billing adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are activated continuously to monitor usage in physical environments, then measurement precision and reliability of usage data are improved, but energy consumption and operational costs increase
Solution Approach 1:
The system activates sensors periodically based on trigger events (mobile device proximity detection) rather than continuously. Sensors remain inactive during non-usage periods, reducing energy consumption while maintaining measurement precision when needed. This periodic activation pattern directly addresses the contradiction by decoupling continuous monitoring requirements from continuous energy consumption.
Solution Approach 2:
The system uses mobile device-based triggers to automatically activate sensors when a user approaches, eliminating the need for continuous sensor operation. The mobile device itself serves as the trigger mechanism, and the system self-regulates sensor activation based on detected proximity events, optimizing the balance between measurement accuracy and energy efficiency.
2Adaptability or versatility
If virtual perimeters are used for location-based services, then adaptability for various applications is improved, but the system complexity increases
Solution Approach 1:
The physical environment is divided into multiple sub-environments with distinct usage patterns and maintenance requirements. This segmentation allows the system to apply different monitoring and management strategies to different areas, increasing adaptability while managing complexity through modular treatment of each sub-environment rather than treating the entire space uniformly.
Solution Approach 2:
The system implements location-specific usage patterns and maintenance strategies for different sub-environments. Each sub-environment has tailored management approaches based on its specific usage characteristics, allowing the overall system to maintain high adaptability across diverse applications while managing complexity through localized optimization rather than global complexity.
3Measurement precision
If comprehensive sensor activation is implemented throughout the physical environment, then usage tracking accuracy is improved, but loss of time for maintenance operations increases
Solution Approach 1:
The system implements real-time feedback loops where sensor data from mobile devices and environmental sensors continuously informs maintenance decisions. When usage patterns indicate potential maintenance needs (e.g., high traffic areas, frequent access points), the system automatically triggers maintenance tasks, reducing the time between detection and action. This feedback mechanism ensures accurate usage tracking while minimizing maintenance response time through proactive rather than reactive maintenance.
Data Source
AI summary
Methods, systems, and apparatuses may provide for the auto-determination of partial usage of a physical environment and use derived intelligence to take various actions. This may allow for partial resulting maintenance of the physical environment based on a single use or use over time.