What is Wi-Fi Sensing?

Wi-Fi Sensing is a technology that uses Wi-Fi signals to operate like a short-range passive radar by measuring how they interact with movement and the environment. By pinging the environment, Wi-Fi sensing systems can easily track locations and movement based on how the signals are reflected and deflected. By analyzing these disturbances using AI trained models, this disturbance data of the Wi-Fi signals can be given meaning and classified to create smart solutions. 

Wi-Fi sensing has been deemed surprisingly accurate and the information collected is from the normal packets and signals used for transmitting and receiving information from regular devices connected via a Wi-Fi network. This technology does not require any additional specialized signals nor does it degrade network performance or the user experience when using Wi-Fi. 

Preliminary testing shows that Wi-Fi sensing performance is correlated to channel bandwidth. The larger the bandwidth, the higher the resolution. Currently, Wi-Fi works in 2.4 GHz, 5 GHz and 6 GHz bands. Channel bandwidth in the 2.4 GHz spectrum is 20 MHz and 5 GHz is 160 MHz and 6 GHz band can be up to 1200 MHz (Wi-Fi 6E). The wavelengths of the Wi-Fi signal in these bands spans from 4.2 cm (6 GHz band) to 12.4 cm (2.4 GHz band).

Such signals are well suited for motion detection, activity detection and recognition for human bodies as well as the breathing rate and even heartbeat detection through a more sophisticated antenna, DSP (digital signal processing), machine learning algorithms and techniques. Wi-Fi sensing technology enables security, safety, and family care services in smart home and IoT applications. It supports a variety of features and applications such as motion detection, human activity detection and recognition and vital signs detection.

Wi-Fi, one of the most commonly used wireless network protocols, is typically associated with wireless internet access and local area networking of devices. It may have seemed that this would be the sole purpose of Wi-Fi until a few years ago, but now, the growth in number of Wi-Fi enabled networks around the world to comprise of tens of billions of connected devices, has opened up a new range of possibilities for application of Wi-Fi technology other than providing wireless internet access and communication. Some research even shows how Wi-Fi signals can be used to transfer power as well as data. But perhaps the most promising and tangible application of Wi-Fi signals is that of using it for motion sensing.

The technology behind Wi-Fi sensing is relatively new, and there aren’t any standards governing its implementation. While some applications can be enabled using existing standards, there are technology gaps that limit the range of applications. Some of these gaps may be addressed via proprietary means, however, such an approach would inhibit interoperability, integration, and deployment. Alternatively, there could be opportunities for the introduction of new capabilities into the Wi-Fi standards. Standard support would allow for more efficient handling of existing use-cases and enable new use-cases previously not possible. 

Advantages

Currently, motion sensing can be achieved using infrared and radar sensors, or a combination of cameras, AI and time of flight (ToF) sensors. These existing solutions naturally raise the question: Where does Wi-Fi sensing fit into all this?

Wi-Fi Sensing has an advantage over existing solutions in this regard as it does not need any extra hardware. For example, active radar systems require dedicated antennas and transceivers that are complex and costly. On the other hand, Wi-Fi sensing uses existing devices like cell phones, PCs, and mesh Wi-Fi systems. The user would only need to install the required software to transform their setup into a Wi-Fi sensing solution.

There are about 15 billion Wi-Fi client devices out there. With Wi-Fi sensing, all these devices, which were never meant to be motion sensors can be enabled to be motion sensors. And that can then provide the user with other capabilities going forward, whether that’s home monitoring or IoT integration for smart homes. All this can be done simply by software.

Wi-Fi also penetrates through walls, enabling out of line-of-sight (LOS) operation, an important consideration for security monitoring applications. And because it doesn’t rely on image data, it retains a degree of privacy.

Wi-Fi sensing is innately cost-effective due the near-ubiquitous nature of Wi-Fi. Wi-Fi is now virtually everywhere, so the infrastructure is already all around us. There is no need to build a new ecosystem because the IoT (Internet of Things) provides the perfect ecosystem for using data like motion sensing in more useful ways.

Since the Wi-Fi standard was developed with interoperability and backward compatibility in mind, it makes it easier to layer extra functionalities on top. With that said, Wi-Fi equipment manufacturers need to enable lower-level access and chipset firmware access to control data flow. Similarly, the operating system may also need lower-level access to network gear to allow a standardized application interaction.

Some Applications of Wi-Fi Sensing

All the above advantages enable motion-sensing using Wi-Fi to be applied to a wide range of new and existing use-cases. These include conventional residential monitoring, to detect an intrusion or scheduled maintenance in and around homes. This can easily be extended to smart buildings, using motion and occupancy detection as part of a building management system for HVAC and lighting control. 

The wake-on-approach and lock-on-walk-away use cases are similar in concept. Consumer electronics with Wi-Fi radios might detect a user in proximity and switch on from standby mode. The same mechanism could lock a device when a logged-in user saunters off. Enabling both features would be a great for the battery life and security of mobile devices.

For large events, a sensor could be placed at the entrance to count visitors.

Perhaps even more impactful, it can be used to help monitor the elderly and vulnerable people in their homes for peace-of-mind. Hospitals and elderly care facilities can use Wi-Fi sensors to monitor patient movement and biometric data like heartbeats, breathing, and limb movements.

Wi-Fi Sensing may even be used for gesture recognition, displacing many of today’s touch controls, particularly in public places. As COVID-19 has everyone acutely aware of shared surfaces, there’s an immediate need for touchless alternatives to turnstiles, elevator buttons, and airport kiosks.

When predictive analytics are applied to Wi-Fi sensing technology, it can learn users’ behavior patterns. Over time, as a consumer incorporates more IoT devices into the home, the data from each device is added to the motion algorithms, resulting in more precise motion information. For instance, the Wi-Fi network will be able to sense when someone comes home and adjust the smart thermostat and smart lighting based on habitual behavior rather than requiring users to set manual preferences in an app or through verbal commands.

Challenges

The most important indicators for performance in Wi-Fi-based motion sensing are the same for other methods of motion detection, specifically accuracy, precision and latency. Accuracy relates to detecting motion when someone is moving or present while minimizing the number of false positives the system may generate. This emphasizes the need for total Wi-Fi coverage in the home, buildings or other areas being monitored. Precision, in this context, relates to how the system differentiates between types of movement being detected, including the speed and direction. This is important if the system is being used to monitor an elderly or vulnerable person in the event of a fall, for example. Latency, as it is generally understood, is the delay between detecting a movement and reporting the event. In any motion detection solution, this needs to be measured in milliseconds, rather than minutes.

Wi-Fi signals, like any wireless transmission, are vulnerable to interference that decreases their accuracy. And if the Wi-Fi equipment acting as sensors come under heavy traffic, the depleted resources could reduce service quality.

Coverage and signal strength is another consideration for out of LOS applications. Wi-Fi sensing works best with high-frequency, high-bandwidth transmission. But high frequencies have trouble penetrating walls. Thus, solution designers need to balance bandwidth and accuracy, rely on more sense nodes, or consider the sensor’s proximity to the target.

In enterprise scenarios like healthcare, the high resolution demands set more stringent hardware requirements. In addition to frequency and bandwidth criteria, the devices need higher processing power for active systems with large performance overheads.

Wi-Fi’s physical layer (PHY) protocols already perform certain measurements for sensing the surrounding environment. But those measurements weren’t exactly designed for the applications targeted by Wi-Fi sensing. In the future if a standard could specify additional measurement data, sensing accuracy would improve. Meanwhile, the technology’s efficiency stands to benefit by exposing each device’s sensing capabilities at the medium access control (MAC) layer. 

Right now, a limited number of use cases are possible with commercially available hardware based on existing wireless standards. But there are gaps in the technology when it comes to testing Wi-Fi sensing features, in terms of knowledge, procedures, and tools which needs to be bridged by a broader industry-wide effort. Which is why standardization is key to Wi-Fi sensing’s future.