BLE Beacon Room Tracking via Signal Normalization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for in-home room tracking using Bluetooth Low Energy (BLE) beacons face challenges in dynamic home environments due to varying layouts, materials, and signal interference, requiring calibration and technical assistance, which is impractical for non-technical users.
Innovation Solution
A system utilizing BLE beacons paired with a smartwatch and an algorithm that processes signals without calibration, interpolates missing data, smooths noise, and normalizes signals to accurately track room location without relying on technical assistance or environmental specifics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If calibration and technical assistance are provided for BLE beacon room tracking, then measurement precision is improved, but device complexity and ease of operation worsen
Solution Approach 1:
The system performs automatic environment adaptation where the mobile sensor independently calibrates and adapts to the home environment without external assistance. The device automatically learns signal characteristics from multiple beacons and adapts to environmental conditions, eliminating the need for manual calibration by technical personnel.
Solution Approach 2:
An algorithm acts as an intermediary between the raw beacon signals and the location determination. The algorithm processes and interprets signals from multiple beacons, automatically adapting to environmental variations and translating complex signal patterns into accurate room location identification without requiring user intervention.
2Measurement precision
If calibration data collection is required, then measurement precision is improved, but loss of time and ease of operation worsen
Solution Approach 1:
The system performs preliminary adaptation automatically in the background as users naturally move through their home environment. Instead of requiring dedicated calibration sessions, the system continuously learns and adapts to the environment during normal usage, eliminating time loss while maintaining high precision.
Solution Approach 2:
The environment adaptation process continues continuously in the background during normal system operation. The mobile sensor constantly collects and processes beacon signals, continuously refining its understanding of the environment without interrupting the useful function of location tracking.
3Measurement precision
If multiple RFID or WiFi devices are used to characterize sociability, then measurement precision is improved, but device complexity worsens
Solution Approach 1:
A single mobile sensor device performs multiple functions: it tracks location, characterizes sociability, and adapts to the environment. By consolidating these functions into one device rather than requiring multiple specialized devices, the system reduces overall complexity while maintaining measurement precision through multi-functional integration.
Solution Approach 2:
The system merges location tracking and sociability characterization into a single integrated approach using BLE beacon signals. Instead of separately deploying RFID readers, WiFi access points, and other devices, the mobile sensor combines multiple measurement capabilities into one unified system that reduces complexity while maintaining precision.
Data Source
AI summary
Methods and systems for determining a location of an individual in a home, business, structure, or other finite amount of space using one or more beacons.