Trends in Sensing System Innovations

Someone just open-sourced a system that can detect human movement, presence, and even some vital signals using WiFi. The project is called RuView / WiFi DensePose. It builds on earlier academic research, including work like Carnegie Mellon’s “DensePose from WiFi” papers, which showed that detailed WiFi signal data can be used to estimate human pose and motion. This project takes that research idea and turns it into an open-source system that developers can actually experiment with. The system reads Channel State Information (CSI) from WiFi hardware and uses signal processing and machine learning to infer things like movement, body position, breathing patterns, and presence. In controlled setups with the right hardware, systems like this can detect whether someone is in a room, track how people move, estimate rough body pose, and sometimes even pick up breathing patterns. (Full capability requires CSI-capable hardware such as ESP32 boards or specialized WiFi cards. It is not something that works with a normal phone or laptop WiFi chip.) Capabilities once limited to research labs are now becoming accessible to builders everywhere. Open source accelerates experimentation across healthcare monitoring, smart environments, robotics, and search and rescue. At the same time, technology that can sense people without cameras raises obvious questions. In the right hands, it could help catch criminals, detect intruders, or locate survivors when cameras cannot see through debris. Used responsibly, those are powerful and important applications. But the same capabilities could also be misused for covert surveillance, tracking, or stalking. As sensing technologies like this spread beyond research labs, the conversation around safeguards, responsible deployment, and misuse prevention needs to move just as fast as the innovation itself. https://lnkd.in/eTWQVnVQ

Wireless #sensing is one of my picks for 2026 interest, acceleration & maybe hype. It is one of the few possible "new cool features" for #6G, and also has an existing role in enabling new #WiFi services such as smart-home functions. I recently met with ETSI, which has just approved its 2nd package of #ISAC (Integrated Sensing and Communications) work items. This includes new efforts around: - What else is needed around RAN & core architecture to make sensing work - Privacy and security (I recently wrote about some possible challenges) - Integration of compute with ISAC and also governance of sensing data - Demonstrability and business/economic value Based on my meeting and other discussions, I've picked up a few other relevant things about this domain: - ETSI is trying to act as a bridge between academia / industrial R&D and the standards process. It intends to be "2-3 years ahead" of the main 3GPP process on specifications - It's not just about 6G, but also #5GAdvanced, aligning with IEEE / Wi-Fi efforts such as 802.11bf and future #WiFi9. (There's also a ton of sensing work done with fibre and subsea cables, but I think they're pretty separate) - A lot of the early use-cases are from #automotive and #drone / UAV sectors, plus also I know there's deep interest from defence and public safety - Some interesting discussions about hybrid sensing combining infrastructure and end-devices (eg a radar "ping" from a base station, picked up on a phone) - Sensing *probably* won't need dedicated spectrum, but it's a bit unclear how existing bands get reused and the impact on interference / capacity - We'll definitely need sensor fusion and multimodal efforts including cameras and other sensing inputs - it won't just be RF on its own - There's a huge AI/ML surface here - both using sensing as a data input for AI models, and using AI to interpret sensing data, including with realtime inferencing. I'm going to stick my neck out and suggest #neuromorphic and #analog computing as maybe having a role here too. - The ETSI "interest group" now has over 110 members, including some from the device side such as Apple and Xiaomi Technology (the latter now makes EVs and well as phones). Thanks to InterDigital, Inc. too for the invite - Alain Mourad is the ISG Chair But there's one really big issue nobody is yet thinking properly about, as far as I know: #regulation of sensing. It's not obvious there's a read-across from normal #mobile or #spectrum regulation & policy. For instance, do we need 3-4 competing national sensor grids? What does wholesale or a "sensing MVNO" looking like? How does sensing interact with other regulatory domains like privacy, cybersecurity, planning, public safety, AI etc? As far as I know, no regulator has yet developed a full strategy. That needs to start ASAP; otherwise it will become a bottleneck for deployment and commercialisation. (Please get in touch if you'd like me to facilitate a workshop or do a research project here).

Quantum Sensing Breakthrough Sets New Standard for Light Displacement Detection Unprecedented Precision Through Photon Interference Physicists at the University of Portsmouth have made a landmark advancement in quantum sensing, achieving a new level of precision in detecting ultra-tiny spatial shifts in light—down to the nanoscale. Published in Physical Review A, the study leverages quantum interference between entangled photons to surpass the limits of classical measurement tools, marking a potential turning point for fields requiring extreme sensitivity, such as advanced materials science, metrology, and navigation. How It Works: Entangled Photons and Beam-Splitters • Photon Entanglement and Interference: The research team used pairs of entangled photons—light particles whose properties remain linked even when separated. These photons were sent through a beam-splitter that directs them along different paths. • Interference-Based Detection: The entangled photons interact in predictable but highly sensitive interference patterns. By analyzing even minute changes in these patterns, researchers can detect spatial displacements at an extraordinarily fine scale. • Beyond Classical Limits: Traditional methods struggle to maintain accuracy when displacements become extremely small or large. This quantum approach, however, maintains its precision regardless of the scale of the displacement. Applications and Scientific Impact • Characterizing Birefringent Materials: The technique has direct applications in analyzing materials that change the direction of light based on polarization—useful in optics, telecommunications, and medical imaging. • Precision Rotation Sensing: This level of displacement detection opens new doors for extremely accurate gyroscopes and navigation systems, particularly in environments where GPS isn’t available, such as deep space or underwater. • Industrial and Daily Impacts: Ultra-precise measurements are essential in semiconductor manufacturing, nanofabrication, and high-resolution imaging. This breakthrough could significantly enhance those processes, improving both product performance and measurement reliability. Why It Matters: Quantum Precision Moves Closer to Real-World Deployment This achievement demonstrates the practical power of quantum physics to revolutionize measurement science. With its ability to detect infinitesimal spatial changes using entangled photons, the Portsmouth team has brought quantum sensing closer to mainstream industrial and scientific applications. In a world increasingly defined by nanoscale engineering and quantum technologies, the ability to “see” with such clarity is more than academic—it’s foundational for future innovation. This work not only reinforces the value of quantum research but also brings us one step closer to a future where quantum sensing reshapes how we measure, navigate, and understand the physical world.

7 wearable and sensor innovations pushing health beyond “wellness” tracking this month: 🔘 Sibel Health is developing an AI-enabled wearable that tracks scratching behaviour in people with atopic dermatitis, turning something usually seen as a subjective symptom into a measurable clinical signal that could also support drug development. 🔘 CranioSense is working on a non-invasive approach to measuring intracranial pressure, which today often requires invasive procedures, and if validated could make brain pressure monitoring safer and more continuous in routine clinical care. 🔘 University of Technology Sydney researchers are developing AI-powered sweat sensors that can decode body chemistry in real time, tracking hormones, medication levels and potential early warning signs of disease, potentially offering a non-invasive alternative to some forms of blood testing 🔘 ŌURA rings are being used within Medicare Advantage Plans, with around one-third of eligible members opting in and sharing biometric data, which is already leading to improvements in sleep and light activity and is paving the way for deeper clinical use cases such as hypertension monitoring 🔘 Samsung Electronics is preparing to launch an AI Brain Health tool that uses data from smartphones and wearables, including speech, movement and sleep behaviour, to help detect early signs of dementia while aiming to keep the experience privacy-aware and clinically relevant 🔘 Researchers at the University of Arizona have created a wearable mesh sleeve that monitors gait and subtle movement patterns to identify early signs of frailty in older adults, with the goal of shifting care from reacting after a fall to proactively supporting prevention through continuous remote monitoring 🔘 And China is testing “smart urinals” that analyse urine in real time for markers like glucose and protein, which opens up interesting conversations about passive health screening, consent, and how health data might be gathered in everyday environments. 💬We are steadily moving from episodic health snapshots to passive, continuous and contextual signals across movement, sleep, behaviour and even body chemistry. The technology is getting closer. Now the real work is around validation, governance, reimbursement and making sure the data actually makes a difference in peoples lives 👇 Links to articles in comments #DigitalHealth #Wearables #AI

Revolutionizing Geospatial Data: The Evolution of Aerial Photogrammetry Over the past 25 years, aerial photogrammetry has transformed into a fully digital technology, providing highly precise spatial data essential for creating digital twins and making informed decisions in urbanization, climate change, and energy production. 🔍 Key Developments: 🔹 Digital Transformation: The 1990s saw the digitization of analog aerial images using high-precision scanners, leading to the first digital photogrammetric workstations. 🔹 Introduction of Laser Scanning: The late 1990s brought laser scanning technology, enabling direct capture of elevation data over large areas. 🔹 Advancements in GPS Technology: Integrating GPS allowed near real-time positioning and direct orientation of aerial images, enhancing spatial data precision. 🔹 First Digital Aerial Cameras: In 2000, Leica and Zeiss-Intergraph introduced the first digital aerial cameras, replacing traditional film with digital sensors. 🔹 Drones and Computer Vision: The 2010s democratized aerial photogrammetry with affordable drones and advancements in computer vision algorithms, enabling efficient data capture for smaller areas. 🔹 Semi-Global Matching (SGM): Introduced in 2005, SGM revolutionized 3D point cloud generation from image data, achieving near-laser scanning quality for surface models. 🔹 Hybrid Sensor Systems: The development of hybrid sensors combining imaging and laser scanning technologies in 2016. 🚀 Trends Shaping the Future: 🔹 Higher Resolutions: Achieving resolutions of 10 cm or better for large areas and 5 cm for urban regions. 🔹 Frequent Updates: Annual or bi-annual flights for cities and large-scale areas to ensure up-to-date data. 🔹 Larger Project Areas: Expanding project sizes to cover entire countries efficiently. 🔹 Multisensor Integration: Simultaneous capture of complementary image and LiDAR data, providing comprehensive geospatial information. 🔹 Artificial Intelligence: Enhanced data analysis, flight planning, and quality control through AI, leading to more efficient and accurate results. 🔹 End-to-End Solutions: Providing complete solutions from data capture to final presentation, meeting the growing demand for ready-to-use information. 🌟 Impact on Industries: Aerial photogrammetry is crucial for creating spatial digital twins, foundational for urban planning, environmental monitoring, and disaster management. AI and hybrid sensors enhance geospatial data accuracy and usability, driving innovation across sectors. 📈 Looking Ahead: The future of aerial photogrammetry lies in sensor advancements, increased automation, and AI integration. These developments will lead to higher quality data, faster processing times, and more comprehensive solutions, making geospatial data more accessible and valuable than ever before. 💡 Comment | Like | Share 👉 Follow me (Dr. Uwe Bacher) for more geospatial insights #Photogrammetry #DigitalTwins #AerialMapping

The most important wearable of the next decade won’t be something you show. It won’t sit on your wrist. It won’t light up. You may even forget it’s there. Health technology is shifting from devices we notice to systems that quietly work in the background. Lumia™ Health is a strong signal of that shift. They didn’t choose the wrist. They chose the ear. They didn’t optimize battery life. They removed charging altogether. A solar-powered earable, under one gram, always on, fueled by ambient light as life unfolds. No habits to build. No charging reminders. No data gaps because the device died. But the real innovation isn’t convenience. It’s what becomes measurable. The wrist captures movement. Steps. Heart rate. Activity trends. The ear opens access to cephalic blood flow and that’s how blood reaches the brain in real time. That matters for symptoms people experience daily: brain fog, dizziness, fatigue, head pressure. Not acute illness. Not “nothing” either. These signals live between annual checkups and lived experience that quietly shaping focus, energy, and performance. With continuous sensing, context appears: during work, under stress, in recovery. Health stops being episodic. It becomes adaptive. Instead of reviewing data after the fact, the system responds as conditions change by detecting early shifts, linking them to behavior and environment, and guiding action before symptoms escalate. This is the next phase of wearables: less attention, more intelligence. From a health futurist’s lens, three forces are converging: • Invisible design over visible tech • Deep physiology over surface metrics • Continuous guidance over periodic insight Lumia™ Health sits right at that intersection. We’re moving beyond the wrist. Beyond dashboards. Beyond once-a-year health. Toward silent, solar, brain-aware systems that work with us, not on us. #wearabletech #thewearablesexpert How do you see earables and invisible wearables redefining health products?

This week's defining shift for me is that sensing is being designed as a complete system. The center of gravity has shifted from tuning individual cameras or lidar units to making sure the whole stack works together in real conditions. You can see it in the hardware choices and how these products are being packaged and sold. This week’s news surfaced signals like these: 🚘 Waymo introduced its 6th-generation Driver with a redesigned sensing suite that balances cameras, lidar, radar, and audio around cost, weather performance, and multi-vehicle deployment. 📸 Ouster acquired StereoLabs, bringing stereo vision hardware and perception software into its lidar business and repositioning itself around an integrated sensing and perception platform. Why this matters: Perception is being thought of beyond parts to consider what it needs to act as a system. Where and how these sensing systems run is shaping how these stacks are designed. #sensors #radar #lidar #computervision #spatialcomputing

A breakthrough in quantum sensing—measuring more with less. Researchers at Massachusetts Institute of Technology have developed a new type of diamond-based quantum sensor capable of measuring multiple signal parameters simultaneously. Traditionally, solid-state quantum sensors capture one parameter at a time—such as magnetic fields, temperature, or mechanical strain. This sequential approach increases experiment time and the risk of measurement errors. The new system leverages entangled qubits within a diamond defect known as a Nitrogen-Vacancy Center. In this structure, a nitrogen atom sits next to a missing carbon atom, forming a highly sensitive quantum system. By exploiting Quantum Entanglement, researchers can extract multiple signal characteristics—amplitude, phase, and frequency deviation—from a single measurement. One of the most compelling advantages: 👉 The sensor operates at room temperature, eliminating the need for extreme cooling required by many quantum systems. Why this matters: This innovation could significantly accelerate research in advanced materials, biological systems, and nanoscale magnetic fields, where fast and precise multi-parameter sensing is critical. 🤯 Quantum sensing is moving from complexity to practicality faster than expected. #QuantumTechnology #QuantumSensing #DeepTech #Innovation #MIT #FutureTech #Science #EmergingTech #Foresight #QuantumPhysics

Wi-Fi is no longer waiting for you to carry a WiFi-enabled device to interact with it .. no phone, no laptop, no wearable, nothing at all. Last September, the IEEE - the global body responsible for defining Wi-Fi standards - officially published the (IEEE 802.11bf) amendment, widely known as "Wi-Fi Sensing", after years of drafts and development. This amendment will take Wi-Fi technology into a completely new dimension, expanding its role far beyond indoor wireless connectivity. A few examples of what's now possible: ✨ Wi-Fi can replace surveillance cameras. This is a massive industry, especially that Wi-Fi will offer higher privacy. Cameras, for example, cannot be installed inside hotel rooms, but Wi-Fi can. It can associate you with an identity without recording any video, and without invading personal privacy. ✨ Wi-Fi can precisely count people anywhere, whether a person has WiFi-enabled devices or not. It can detect motion, identify intrusions and determine which rooms are truly occupied or under-utilized. This is a game-changer for enterprises, malls, hotels, and museums. ✨ Wi-Fi can monitor the wellbeing of seniors and children. It can detect movement, falls, sleep patterns, breathing, and even heart rate .. all without wearables. Time to rethink the traditional health bands. ✨ Wi-Fi can enable intelligent energy management. Lighting, air conditioning, and other systems can operate automatically based on real human presence .. replacing traditional sensors whose readings were often inaccurate and costly. Wi-Fi, on the other hand, already exists everywhere. These use cases are just the tip of the iceberg… and what’s coming next is even more transformative.

One of the most important lessons from Ukraine is this: sensing must scale economically. Ukraine has developed acoustic sensors capable of detecting FPV drones by their sound signature including fiber-optic drones that are invisible to RF detection and resistant to electronic warfare. The range per node is modest. But that’s not the point. The point is architecture. Each acoustic station costs roughly $500. For the price of a single radar system, you can deploy thousands of acoustic nodes, creating dense distributed sensing networks across frontlines, infrastructure, and logistics routes. This fundamentally changes the cost equation. Radar remains critical but radar alone is not enough. Low-altitude drones, terrain masking, clutter, and fiber-optic control create sensing gaps. Acoustic sensors fill those gaps by providing passive, resilient detection that cannot be jammed or easily targeted. They do not replace radar but complement it. Modern defence sensing is no longer about single exquisite sensors. It is about layered, distributed, economically scalable detection architectures. In a world where drones costing hundreds of dollars can threaten billion-euro infrastructure, cost-effective sensing is not optional. It is foundational. #DefenceInnovation #Drones #AirDefence #Ukraine #DefenceTech https://lnkd.in/dBC7RppV