IoT Proximity Detection via Audio Chirps and Data Correlation
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Solution Overview
Problem
Existing IoT devices face challenges in determining their physical proximity to each other, as conventional methods like RSSI and NFC are not accurate for distances beyond close range, and ambient noise recognition is unreliable for enclosed environments.
Innovation Solution
Implementing a proximity detection method where one IoT device outputs an audio emission (chirp) and a data packet simultaneously, allowing the other device to calculate distance based on the differential time of detection, with optional correlation information in the data packet or chirp to account for network latency and clock synchronization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods like RSSI and NFC are used for proximity detection, then the detection can be implemented with existing technology, but the accuracy deteriorates for distances beyond close range
Solution Approach 1:
The patent replaces conventional electromagnetic field-based methods (RSSI, NFC) with an acoustic-based proximity detection system. A first IoT device emits an audible chirp sound, and a second IoT device detects this sound through its microphone to calculate proximity. This substitution of detection mechanism enables accurate measurement beyond close range while maintaining implementation feasibility with existing hardware components.
2Reliability
If ambient noise recognition is used for proximity detection, then the system can operate without additional hardware, but the reliability deteriorates in enclosed environments
Solution Approach 1:
The patent uses a controlled acoustic signal (chirp) emitted by the first IoT device as a reference copy against which the detected sound at the second device is compared. By generating a known reference signal and correlating it with the received signal, the system achieves reliable proximity detection in enclosed environments without requiring complex ambient noise analysis or additional specialized hardware.
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
Enables accurate estimation of proximity between IoT devices regardless of intervening obstructions, improving the accuracy of proximity determination beyond close range and enhancing IoT device interactions in various environments.
Implementation Method 1
The first IoT device uses the speed of sound to calculate a distance between the first and second IoT devices based on the differential time
Data Source
AI summary
In an embodiment, a connection is established between first and second Internet of Things (IoT) devices. After a determination is made to execute a proximity detection procedure, the second IoT device outputs an audio emission and a data packet at substantially the same time. The first IoT device detects the audio emission via a microphone and receives the data packet. The first IoT device uses correlation information to correlate the detected audio emission with the data packet, whereby the correlation information is contained in the detected audio emission, the data packet or both. The first IoT device uses the correlation between the detected audio emission and the data packet to calculate a distance estimate between the first and second IoT devices.