Can WiFi Really Detect Humans? Yes — Here's How

For many, the idea of using a standard home internet router to detect humans, count people, and track their breathing sounds like science fiction. However, the scientific principles behind Radio Frequency (RF) sensing have been understood for over a century. Radar (Radio Detection and Ranging) was developed in the early 20th century to track ships and planes.

Historically, radar required massive, expensive, military-grade transmitters that emitted focused beams of energy. As consumer electronics evolved, Wi-Fi routers became omnipresent, continuously filling our homes with low-power radio waves at 2.4 GHz and 5 GHz.

In the early 2010s, academic researchers realized that we did not need specialized military hardware to perform radar-like sensing. Since the Wi-Fi waves are already bouncing around our living rooms, we could repurpose standard communication signals to sense the physical world. This realization led to the development of WiFi Channel State Information (CSI) sensing—the core technology that powers RuView.

Why does a WiFi signal react so strongly to a human body? The answer lies in the composition of our bodies. Humans are made of roughly 70% water, which is a polar molecule. When electromagnetic waves (like Wi-Fi) strike a human body, they induce tiny electrical currents in our tissues. This causes the body to absorb, scatter, and reflect the incoming radio waves.

Different materials interact with WiFi signals in unique ways:

• **Drywall and Wood**: Low conductivity, allowing Wi-Fi waves to pass through with very little loss.
• **Metal**: Extremely high conductivity, reflecting 100% of Wi-Fi waves and acting as a mirror.
• **Human Bodies**: Intermediate conductivity, absorbing some energy and reflecting the rest in a wide pattern.

As a person moves, they change the path lengths of the reflected signals. By measuring the complex amplitude and phase values of the received signals across multiple subcarriers, RuView captures a detailed signature of these changes.

To understand how raw signals are processed into clean data, see How WiFi CSI Works.

One of the most impressive capabilities of RuView is its ability to monitor human respiration rates without any physical contact. When you breathe, your chest expands and contracts. This movement is tiny—typically between 4 to 12 millimeters.

However, a 12mm chest expansion represents a significant fraction of a 5 GHz WiFi wavelength (which is 60mm). This movement shifts the phase of the reflected wave by a measurable amount. By placing a RuView receiver node near a bed, the system can capture the periodic phase changes caused by breathing.

Our processing engine uses a bandpass filter (0.15 Hz to 0.4 Hz) to isolate respiration frequencies. The resulting time-series wave shows clear peaks and valleys corresponding to inhalations and exhalations.

Under ideal conditions, using high-gain directional antennas, RuView can even detect the sub-millimeter chest vibrations caused by the heart beating. By extracting these micro-movements from the CSI phase stream, we can estimate heart rates (BPM) completely wirelessly.

Capturing the signal is only half the battle. To turn raw waves into actionable events, we need artificial intelligence. Since the human body produces complex, non-linear perturbations, traditional math formulas fall short.

RuView utilizes lightweight deep learning models trained on thousands of hours of CSI recordings. These models run locally on edge gateways and classify human activities into distinct categories:

1. **Static Presence**: Distinguishing between an empty room and a room containing a completely still, sleeping person.
2. **Dynamic Activities**: Classifying walking, standing up, sitting down, and falling.
3. **Fall Detection**: Spotting the rapid, high-amplitude signal drops characteristic of a fall, followed by static low-level breathing signals.

This edge AI processing keeps latency under 5ms, making it suitable for immediate emergency alerts. To see the full range of detection features, visit the Features page.

The implications of WiFi sensing are profound. We are moving toward a future of "ambient intelligence," where our homes and spaces respond to us naturally without requiring us to carry devices, speak to voice assistants, or wear fitness trackers.

RuView is leading this change by building an open-source, affordable platform that anyone can deploy on cheap ESP32 hardware. Whether you want to automate your home, monitor the safety of elderly relatives, or conduct research into RF propagation, RuView provides the tools you need.

To learn how to start building your own setup, check out the Best ESP32 Boards guide or download the code from our GitHub repo.