Wi-Fi Doppler Gesture Control via Noise-Adaptive Sounding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing human control interface (HCI) systems in wireless networks face limitations due to the need for expensive and complex sensor technologies, which are often limited in range and require direct line-of-sight, making them costly and difficult to integrate with existing Internet of Everything (IoE) infrastructure.
Innovation Solution
A system and method that determines noise levels in a wireless network to select between data-compliant and radar-based sounding techniques for detecting Doppler shifts in wireless signals, allowing for the association of these shifts with user inputs to control devices, thereby enabling efficient HCI operation without the need for direct line-of-sight or extensive hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sophisticated sensor technology (cameras, infrared, touch sensors) is used for HCI, then detection accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces sophisticated sensor technology (cameras, infrared sensors, touch sensors) with a wireless communication-based detection system. The HCI system uses existing Wi-Fi infrastructure to detect Doppler shifts in wireless signals, substituting complex optical and tactile sensing mechanisms with radio frequency signal processing. This maintains detection accuracy while dramatically reducing system complexity and cost.
Solution Approach 2:
The patent makes the wireless communication system multi-functional by enabling it to serve both data transmission and human control interface detection purposes. The same Wi-Fi infrastructure used for communication is also used for gesture detection through Doppler shift analysis, eliminating the need for dedicated sensor hardware and reducing overall system complexity.
2Measurement precision
If sophisticated sensor technology is used for HCI, then detection capability is improved, but cost increases
Solution Approach 1:
The patent replaces expensive sensor hardware (cameras, infrared sensors) with software-based Doppler shift detection using existing Wi-Fi radios. This substitution maintains detection capability while eliminating the need for costly specialized hardware, thereby significantly reducing manufacturing costs.
Solution Approach 2:
The patent enables the wireless communication system to serve itself by using its own transmitted signals for gesture detection. The Wi-Fi signals already present in the environment are repurposed for HCI functionality, eliminating the need for additional dedicated sensing hardware and reducing overall system cost.
3Measurement precision
If camera and infrared sensors are used for HCI, then detection accuracy is improved, but line-of-sight requirement limits versatility
Solution Approach 1:
The patent replaces line-of-sight-dependent optical sensors (cameras, infrared) with radio frequency-based Doppler shift detection. Wi-Fi signals can penetrate obstacles and do not require direct line-of-sight, allowing gesture detection to work in environments where optical sensors would fail, thereby significantly improving adaptability and versatility.
4Measurement precision
If touch sensors are used for HCI, then detection accuracy is improved, but limited range reduces versatility
Solution Approach 1:
The patent replaces contact-based touch sensors with wireless Doppler shift detection. This substitution extends the detection range from requiring physical contact to detecting gestures within wireless signal range, dramatically improving versatility while maintaining detection accuracy through signal processing.
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 allows for effective HCI operation in wireless networks by dynamically adapting to noise levels, enhancing detection accuracy and range while reducing costs and complexity, thus integrating seamlessly with existing IoE infrastructure.
Implementation Method 1
detects a pattern of Doppler shifts in a received set of wireless signals using the selected sounding technique, and identifies a Doppler signature based at least in part on the pattern of Doppler shifts
Data Source
AI summary
A system and method for operating a human control interface (HCI) for one or more devices in a wireless network. A first device in the wireless network determines an amount of noise in the wireless network, and selects one of a plurality of sounding techniques based at least in part on the determined amount of noise. The wireless communications device further detects a pattern of Doppler shifts in a received set of wireless signals using the selected sounding technique, and identifies a Doppler signature based at least in part on the pattern of Doppler shifts. The wireless communications device then associates the Doppler signature with a user input for controlling a second device in the wireless network.