What is Wi‑Fi Sensing?

Wi‑Fi Sensing is a technology that allows Wi‑Fi devices to detect and interpret changes in the environment using the radio signals they already transmit for communication. Instead of requiring separate sensors or cameras, Wi‑Fi devices use existing radio measurements like channel frequency response or received signal strength (RSSI), to sense motion, presence, or activity in a space.

In essence, Wi‑Fi Sensing leverages the Wi‑Fi infrastructure itself (routers, access points, or client devices) to act like a radar system, providing environmental awareness for applications such as:

• Motion detection (humans, pets, or objects)
• Gesture recognition
• Vital signs monitoring (breathing, heart rate)
• Occupancy analytics
• Smart building automation and security

Wi‑Fi Sensing can be used by network providers, device OEMs, and chipset vendors to create new services or differentiate products, and as the technology matures, it enables more complex and valuable use cases.

How Does Wi-Fi Sensing Work?

Wi-Fi Sensing transforms ordinary Wi-Fi networks into an environmental awareness system. It leverages the radio signals that devices already transmit for communication to also detect changes in the surrounding environment, such as motion of people, pets, or objects. Essentially, every Wi-Fi device can act like a radar, analyzing how signals interact with the space around them.

The sensing process begins with radio signal transmission. Every Wi-Fi device emits signals to communicate, and Wi-Fi Sensing uses these transmissions to “illuminate” the environment. Depending on the setup, sensing can occur in different configurations:

• Monostatic: A single device both transmits and receives signals.
• Bistatic: Separate devices act as transmitter and receiver.
• Multistatic: Multiple devices collaborate, providing a more accurate, comprehensive view of the environment.
  
  

These signals are measured in either passive or triggered modes. In passive sensing, devices rely on normal Wi-Fi communication packets, which avoids extra network traffic but provides limited control. Triggered sensing actively generates transmissions for measurement and can be:

• Invoked: A response to a received signal triggers a measurement.
• Pushed: The transmitting device intentionally sends signals to be analyzed by one or more receivers.

Triggered sensing allows precise control over timing, frequency, and coordination, enabling more accurate and complex applications.

Once measurements are collected, the Wi-Fi Sensing agent - a software component running on an Access Point (AP) or client device analyzes the data. It uses advanced signal processing algorithms to detect changes in the channel, such as variations in signal strength or frequency response, which correspond to motion or gestures. Agents can also collaborate across devices to generate a more robust and precise understanding of the environment.

Key roles of the Wi-Fi Sensing agent:

• Configuration & Control: Manages sensing capabilities, coordinates triggered transmissions, and interacts with the radio through standardized APIs.
• Signal Processing: Extracts meaningful features from raw radio data to identify motion, gestures, or occupancy patterns.
• Network Feedback: Integrates with Wi-Fi services to optimize radio resource management, like AP selection or band steering.

Finally, the application layer converts this processed data into actionable services. For example:

• Home Security: Motion detection and real-time alerts sent to mobile devices.
• Smart Spaces: Occupancy tracking and automation in offices or industrial settings.
• Gesture Control: Interaction with smart devices through detected movements.

By combining radios, sensing agents, and applications, Wi-Fi Sensing provides an unobtrusive, scalable, and intelligent mechanism to monitor environments without additional hardware. The technology is continuously evolving, with standardized APIs and multi-device coordination enhancing its accuracy and enabling more advanced use cases over time.

Why is Wi-Fi Sensing Emerging Now?

Several forces are converging to make Wi-Fi sensing practical and valuable:

• Existing Infrastructure: There are already millions of Wi-Fi APs and Wi-Fi–capable devices. Using them for sensing means lower incremental hardware cost.
• Improved Processing & AI: ML and signal processing advances (including self-supervised learning) allow extracting more from noisy RF data. Features like Channel State Information (CSI) allow fine-grained measurement.
• Standards Progress (IEEE 802.11bf): The IEEE is standardizing WLAN sensing via the 802.11bf amendment (SG / Task Group) to provide interoperable, reliable mechanisms for measurement and reporting.
• Privacy & Non-Visual Sensing Demand: Some use-cases (elder care, in-home monitoring) need sensing without cameras or intrusive sensors; Wi-Fi sensing offers privacy advantages. 

What Are the Real World Applications of Wi-Fi Sensing?

Wi-Fi Sensing leverages existing Wi-Fi networks to detect motion, presence, gestures, and biometric signals, enabling a wide variety of applications across home, enterprise, and personal network environments. Key use cases include:

1. Home Monitoring

• Purpose: Detects motion in a home to provide security and situational awareness.
• Examples: Alerts sent to homeowners when motion is detected in specific rooms.
• Participants: End consumers (DIY home security), hardware OEMs, security providers, network providers.
• Requirements: Detect large-scale motion (~1m), differentiate human vs non-human motion, localize motion to specific areas.

2. Energy Management

• Purpose: Uses Wi-Fi Sensing to provide environmental control and optimize energy usage without installing dedicated sensors.
• Examples: Tracking occupancy in rooms or buildings to manage lighting, heating, and cooling efficiently.
• Participants: Home automation users, enterprise building automation systems, OEMs, network providers.
• Requirements: Detect large-scale motion, count number of people, localize activity in a defined area.

3. Elder Care

• Purpose: Monitors elderly individuals to ensure safety and independent living, while preserving privacy.
• Examples: Detecting falls or unusual motion patterns and notifying caregivers.
• Participants: DIY elder care system users, elder care providers, OEMs, network providers.
• Requirements: Detect specific motion patterns (~1m), localize motion to a room or area.

4. Remote Operator Troubleshooting

• Purpose: Helps network operators identify and troubleshoot Wi-Fi issues by combining sensing data with network KPIs.
• Examples: Detecting localized presence to pinpoint areas with poor coverage or roaming issues.
• Participants: Network providers managing APs, customers with managed Wi-Fi services.
• Requirements: Localize motion/activity to specific rooms or areas.
  

5. Wake-On-Approach / Lock-On-Walk-Away

• Purpose: Enhances device energy efficiency and security by detecting user proximity.
• Examples: Devices such as computers, smart TVs, and monitors switch on when a user approaches and enter power-save mode when the user leaves.
• Participants: Consumer electronics OEMs, network providers offering smart device features.
• Requirements: Detect proximity of a human to a device.

6. Gesture Recognition

• Purpose: Enables hands-free interaction with devices via detection of gestures.
• Examples: Detect small-scale hand/finger gestures, facial gestures, or whole-body poses to control devices.
• Participants: Users, consumer electronics OEMs providing enhanced interaction features.
• Requirements: Detect small and large-scale gestures accurately.
  

7. Biometric Monitoring

• Purpose: Measures physiological and behavioral data for health monitoring or security applications.
• Examples: Passive monitoring of heartbeat, respiration, or body movement; security applications such as polygraphs.
• Participants: Patients, healthcare providers, security agencies, device manufacturers.
• Requirements: High-resolution detection of subtle body movements.
  

What factors impact Wi-Fi Sensing performance, and how is its performance measured?

Wi-Fi Sensing leverages existing Wi-Fi networks to detect motion, gestures, and other events in various environments. Its performance depends on several interrelated factors, many of which also affect the underlying Wi-Fi network. Understanding these factors helps in designing robust and reliable Wi-Fi Sensing applications.

Key Factors Affecting Wi-Fi Sensing Performance

Interference

Wireless interference is one of the primary challenges for Wi-Fi Sensing. It can arise from other Wi-Fi devices operating on the same or adjacent channels, causing co-channel and adjacent channel interference, or from non-Wi-Fi devices producing electromagnetic noise. Interference impacts sensing in two ways: it can reduce the number of measurements captured within a given interval, introducing timing jitter, and it may create false readings where transient interference is mistaken for motion.

Mitigation techniques include:

• Dynamic Channel Allocation (DCA) and Auto Channel Selection (ACS)
• Optimized RF planning using non-overlapping channels
• Power control to minimize interference with nearby networks
  

Coverage and Signal Strength

Just as strong and consistent Wi-Fi coverage is critical for connectivity, it is essential for sensing accuracy. Weak signal strength can degrade channel-state measurements, leading to reduced reliability in detecting motion or gestures. For applications covering large areas, such as home monitoring or enterprise spaces, adequate coverage across the entire target environment is vital.

Channel Bandwidth

The bandwidth of the Wi-Fi channel directly impacts the spatial resolution of sensing. Wider channels provide higher resolution, enabling the detection of finer movements:

• 2.4 GHz and 5 GHz networks (20–160 MHz) are suitable for general motion detection.
• 60 GHz networks with bandwidths exceeding 2 GHz enable high-resolution detection for precise applications like gesture recognition and biometric monitoring.
  

Resource Availability

Wi-Fi Sensing requires network resources to perform measurements reliably. Heavy network load or limited device processing power can reduce measurement rates, potentially causing missed events or false detections.

Number of Sensing Illuminators

Using multiple Wi-Fi transmitters or access points improves sensing performance. More illuminators allow for:

• Detection across larger areas
• Enhanced localization of motion
• Improved measurement accuracy through multiple perspectives