Guest blog by embedUR
Wi-Fi continues to be the leading choice for wireless connectivity, with no signs of slowing down. Today, over 19.5 billion Wi-Fi-enabled devices are in use including smartphones, laptops, security cameras, smart plugs, and nearly every kind of IoT device. But connectivity is no longer the only useful application for Wi-Fi signals. Here’s some of what is happening at the forefront of Wi-Fi innovation.
Many people associate Wi-Fi primarily with activities like streaming videos, browsing the web, or transferring files. However, Wi-Fi technology is now being adapted in many ways for applications beyond data transmission. Although some of these advancements may not be widely publicised, they have the potential to transform our understanding and utilisation of this technology. To explore this innovation, we’ve curated five lesser known non-data transmission uses of Wi-Fi.
1 – Wi-Fi sensing
Wi-Fi sensing uses tiny changes Wi-Fi signals to detect changes in the physical environment. Initially, Wi-Fi was created for communication purposes—transmitting data between devices—but researchers soon discovered that the same signals could do more.
As Wi-Fi signals travel through space, they reflect off objects, walls, and people, creating subtle distortions in the signal patterns. These distortions can be analysed to detect motion, gestures, and even biological functions like breathing or heart rate.
The origins of Wi-Fi sensing trace back to academic research with early breakthroughs at institutions like MIT. Research teams at these institutions explored how radio frequency (RF) signals, such as those used in Wi-Fi, could provide non-intrusive environmental awareness without requiring cameras or physical sensors. By analysing signal disruptions, it became possible to identify human activities like walking, sitting, or even waving hands, making Wi-Fi sensing an alternative for monitoring and control in homes, offices, and public spaces.
Companies like Origin Wireless and Cognitive Systems use this technology in home security systems. For example, Origin Wireless’s Hex Home system uses Wi-Fi to provide motion detection without cameras. Wi-Fi sensing is easily adaptable and cost-efficient because most environments already have Wi-Fi infrastructure. This means sensing capability can be leveraged without major investments in new hardware.
2 – Gesture recognition
Gesture recognition is an innovative non-data transmission use case of Wi-Fi that applies the same principles as Wi-Fi sensing. This technology interprets movements by analysing how Wi-Fi signals bounce off and reflect off people and objects in the environment.
Specifically it measures changes in signal strength and phase caused by movements. When a person makes a gesture, such as waving a hand or pointing, the Wi-Fi signals emitted by routers and access points interact with the person’s body, creating unique patterns of reflection and diffraction.
Advanced algorithms process these patterns to identify specific hand or body movements and then translate them into commands or actions. For instance, as Wi-Fi sensing can detect motion or monitor heart rates by analysing signal variations, Wi-Fi gesture recognition discerns distinct gestures from the modulation of Wi-Fi signals.
In addition to Wi-Fi, other wireless technologies are being explored for gesture recognition. For example: Google’s Pixel 4 device integrates a radar-based technology called Soli to detect fine hand gestures, allowing users to skip songs, snooze alarms, and even silence phone calls just by waving their hands.
This technology operates on principles similar to Wi-Fi gesture recognition. However, Wi-Fi’s widespread presence in most environments gives it a significant advantage for broader applications, as it can utilise existing infrastructure without the need for specialized hardware.
Commercial applications of Wi-Fi-based gesture recognition are already emerging. Some forms of this technology can be integrated into routers to enable gesture-based control for smart home devices. This application demonstrates how Wi-Fi gesture recognition can provide seamless user experiences, allowing individuals to control their smart home environments with simple gestures, using the ubiquity of Wi-Fi signals already present in homes and businesses.
3 – Power-over-Wi-Fi & ambient power harvesting
Power-over-Wi-Fi uses the energy from radio frequency (RF) signals emitted by Wi-Fi routers. Researchers at the National University of Singapore (NUS) have made some advancements in this area by developing a new rectifier that converts these ambient RF signals into usable direct current (DC) power. Their innovative approach demonstrates the ability to capture RF energy at low power levels below -20 dBm, where many current technologies fall short.
This technology has major implications for powering small, low-energy devices such as sensors in IoT ecosystems. For instance, energy harvesting could support environmental monitoring sensors in rural areas and even wireless devices in smart homes, such as connected light bulbs and smart thermostats and reduce the need for regular battery replacements.
Power-over-Wi-Fi (PoWi) is still being developed and is not widely available yet. However, similar wireless power solutions are already in use. A perfect example is the Ossia Cota Power system. This system operates like Wi-Fi, where a Cota Power Receiver sends out a beacon signal to locate a Cota Power Transmitter in devices. The transmitter then sends power back through the same paths. This exchange happens 100 times per second, allowing power to be delivered safely to devices, even when they are in motion.
Ambient power is now also being studied for standardisation by an IEEE 802.11 topic interest group. The chipset company Haila is an example of a startup working on developing battery-free IoT sensors using the principle of RF energy harvesting.
4 – Asset tracking
Wi-Fi-based location tracking systems use existing Wi-Fi networks to detect the location of devices without requiring them to connect to the network. Instead of establishing a connectivity session, the system listens to signals that devices naturally emit – such as beaconing – at the link level. This means the network “listens” to nearby devices without needing them to join the network (e.g., without needing passwords or login).
The key advantage of Wi-Fi-based location is that it uses existing Wi-Fi infrastructure. Most buildings already have Wi-Fi networks, so no new hardware installations are required, unlike other technologies such as BLE (Bluetooth Low Energy) beacons or RFID.
BLE (Bluetooth Low Energy) beacons require numerous dedicated devices to be placed throughout a building to achieve accurate indoor localization. Each beacon transmits a signal to track devices, and the need for multiple units, along with maintenance and battery replacements, increases costs.
RFID (Radio Frequency Identification), which has historically been widely used in industries like retail and healthcare, requires dedicated readers and tags. While effective for tracking items or patients in hospitals, RFID systems often involve considerable investment in hardware, such as antennas and readers, especially for large-scale operations.
With Wi-Fi-based localization, simple calibration or additional access points can enhance positioning accuracy without requiring entirely new technologies. This makes it easier and cheaper to scale tracking across multiple facilities, such as warehouses or large office spaces, where indoor tracking is crucial.
Companies like Cisco offer solutions such as Cisco Spaces, a cloud-based platform that captures real-time data from Wi-Fi signals. This allows businesses to track assets, people, and even sensors to gain insights about space utilisation, occupancy, and asset management without additional hardware.
New and standardised Wi-Fi technology dubbed IEEE 802.11az or ‘Fine Timing Measurement’ (not yet supported by all devices and networks) now allows highly accurate tracking down to less than a meter of accuracy. Applications such as indoor wayfinding, geofencing, and using location to support AR & VR use cases are now being developed using 802.11az. For more details also read here.
5 – Sleep monitoring with Wi-Fi
Sleep monitoring is another innovative application of Wi-Fi technology that extends beyond data transmission. Traditional sleep assessment methods – such as Polysomnography (PSG) – require multiple sensors to measure brain activity, heart rate, and other physiological signals. While PSG is highly accurate, it is uncomfortable and typically confined to clinical settings.
Wrist-based Fitbit devices and the Google Pixel Watch series, on the other hand, offer a more convenient alternative by tracking sleep through heart rate and movement, but they often compromise comfort. Wearing the device all night can disrupt natural sleep, limiting the practicality of long-term use.
Researchers have now discovered that Wi-Fi signals can be harnessed to monitor sleep stages non-intrusively. As Wi-Fi signals pass through a room, they reflect off walls, objects, and the sleeper’s body, capturing subtle changes in the environment. By analysing the distortions in these signals, it is possible to detect respiration rates, body movements, and other physiological activities associated with different sleep stages.
Building on this idea, a research team developed Wi-Fi-Sleep. This system uses Channel State Information (CSI) from Wi-Fi devices to monitor sleep without physical contact or wearable sensors. The system relies on a pair of Wi-Fi transceivers positioned with the sleeper in the middle.
As Wi-Fi signals pass through, changes in the signals caused by breathing patterns and body movements are recorded. To improve the accuracy of these measurements, the system uses algorithms to filter out noise and correct signal distortions.
The researchers designed this system to identify four distinct sleep stages (wakefulness, light sleep, deep sleep, and REM) based on variations in respiration rate, depth of breathing, and movement.
This Wi-Fi-based approach offers a low-cost, non-invasive alternative to traditional sleep monitoring methods, providing long-term sleep analysis without the need for wearable devices or clinical equipment. Though still in the research phase, this innovation points to a future where sleep can be monitored effortlessly in both home and hospital settings and make us better understand and manage our sleep.
Wi-Fi is more than a simple data conduit. It’s an intelligent network that can sense, interact, and power the world around us in ways we never thought possible. Much of this innovation is made possible by the expertise of embedded systems engineers involved in the evolution of Wi-Fi and intelligent edge technologies. embedUR is one of the key players in this innovation.
/embedUR
