CIR-Based Device-Free People Counting via UWB Signals

Area of Science:

• Engineering
• Computer Science
• Public Health

Background:

• COVID-19 pandemic necessitated strict social distancing measures globally.
• Maintaining social distancing in public areas is challenging.
• Automatic crowd density estimation offers a technological solution to monitor and enforce social distancing.

Purpose of the Study:

• To propose a novel, low-complexity radio frequency (RF) sensing system for automatic people counting.
• To leverage ultra-wideband (UWB) transceivers for crowd density monitoring.
• To develop a system that supports social distancing enforcement.

Main Methods:

• Utilized a low-cost UWB transceiver system.
• Developed an ordinary classifier leveraging features from Channel Impulse Response (CIR).
• Extracted features from singular value decomposition of CIR vector differences.

Main Results:

• The proposed system demonstrated effectiveness in automatic people counting.
• Experimental results were validated in two distinct environments.
• The system shows promise for real-world crowd density monitoring applications.

Conclusions:

• The novel RF sensing system is a viable solution for automatic people counting.
• The system contributes to technological solutions for enforcing social distancing.
• This approach offers a promising direction for future crowd density monitoring systems.