Integrating AI With IoT Devices

Brainwaves are the next big biometric. A recent report by Neurable highlights the multibillion-dollar opportunity for wearables that track brain activity and improve cognitive health. 40% of Americans suspect they have an undiagnosed brain condition, but only 25% have sought functional solutions. Growing at a 33% CAGR, AI-powered devices are outpacing adjacent categories, moving from niche hardware to maximizing ROI for patients and everyday users. Beyond diagnosis, DTC neurotech now decodes neural signals, pairing continuous tracking with targeted stimulation to enhance energy, focus, and mental resilience. Integrating inputs, Muse® by Interaxon Inc. headband combines brain and oxygen signals for deeper cognitive insight, while Neurable’s headphones train reaction time. Behind-the-ear devices from Atlas and AWEAR combat distraction and stress. Sleep therapies, Somnee’s headband uses low-frequency currents, while NextSense, Inc’s earbuds adapt “pink noise” to brainwaves. Tracking cerebral blood flow, Lumia™’s earrings and Temple’s face-affixed device pioneer new form factors. Using headset-based electrical stimulation, Flow Neuroscience secured FDA approval for at-home depression treatment, Samphire Neuroscience and OhmBody remedy PMS/endometriosis pain, and Mave targets mental performance. Unlocking brain insights for consumers opens new frontiers for prevention, treatment, and optimization — with neurofeedback loops validating exercise, nutrition, and recovery inputs. 📩 Subscribe to Fitt Insider for more health & wellness headlines. → https://lnkd.in/erFVbn5Z

Walking the floors at HLTH Europe, I came across some impressive startups tackling everything from menopause to mouthguards, hormone tracking to hydration. Here are 10 that caught my eye: 🇬🇧 JawSense tackles bruxism with a smart headband that detects clenching and delivers gentle feedback. It offers a non-invasive alternative to mouthguards, with early trials showing up to 80% reduction in grinding 🇫🇷 Theremia uses AI to optimize CNS treatments by identifying how patient subgroups respond to drugs. Combining clinical and real-world data with pharmacology insights, they refine dosing, formulations, and trial design 🇬🇧 TidalSense built a handheld device that analyzes exhaled CO₂ for faster COPD and asthma diagnosis. It uses AI to interpret breathing patterns and delivers point-of-care results in minutes for early detection and monitoring 🇳🇴 Mode Sensors 'Re:Balans' is a wearable patch that tracks hydration via bioimpedance. It monitors shifts over several days and sends data to clinicians, offering a non-invasive alternative to manual fluid tracking 🇰🇪 Xaidi from iZola.life is a free AI app that supports caregivers of neurodivergent children with symptom tracking, therapy tips, and local-language resources. It connects families to vetted therapists and eases day-to-day care 🇳🇱 WSK Medical uses AI for early cancer detection via real-time endoscopy and pathology analysis. Their tools highlight and classify lesions or automate slide review to help clinicians diagnose more quickly and consistently 🇩🇪 Dx365 built a portable device that reads rapid tests, from hormones to infections, via color or fluorescent signals. Results sync to the cloud, enabling consistent point-of-care testing across health and care settings 🇮🇪 Whyze Health offers an AI platform that unifies health records and shares data securely across patients, providers, and pharma. It supports care coordination, trial matching, and real-world research insights 🇦🇹 Menotracker GmbH is an AI app that helps users track menopause-related changes like symptoms, sleep, and mood. It offers personalized insights and education, while ensuring privacy and multi-language access 🇬🇧 Impli is developing a subdermal sensor to track fertility hormones in real time via NFC. Aimed at IVF, it replaces frequent blood tests by enabling continuous, at-home monitoring and clinician alerts. They partnered with Bayer last year #HLTHEurope #DigitalHealth #AI

Many factories lose money on problems they can't even see. Tiny defects, machine breakdowns, and small inefficiencies add up quietly. Regular robots and machines can't spot these issues. But AI can see them. The groundbreaking partnership between Intel and LG Innotek tackles this challenge head-on. We are building a smart factory where AI acts as a "superhuman eye" for real-time visual quality control. This system is powered by a suite of Intel technologies, including Intel® Xeon® processors, the OpenVINO toolkit, and Intel® Arc™ Graphics. This is a leap beyond simple robotics. We're now moving into the era of the self-optimizing production line. What does this look like in practice?  - AI vision systems can detect defects invisible to the human eye. Micro-fractures, subtle color variations, minute misalignments prevent flawed products from reaching the next stage. - As the AI analyzes thousands of units, it learns. It begins to identify patterns that predict a future failure, allowing for preemptive adjustments to the manufacturing process itself. - This creates a continuous feedback cycle. The line doesn't just produce widgets; it produces data. That data fuels the AI, which in turn makes the line smarter, more efficient, and more resilient with every shift. I see this as the fundamental shift from automated manufacturing to cognitive manufacturing. The goal is no longer just speed but intelligent adaptation.  Read more here: https://lnkd.in/gz6tURZz #IntelAI #SmartFactories #IntelXeon #IntelArc #AIInManufacturing

Smart Consumer Health - What’s New? From smart rings that detect atrial fibrillation to devices that enable showering in bed, and even cutlery that reduces sodium intake—CES 2025 showcased health tech innovations that are redefining personal wellness and self-care. For me CES is always a good indicator, where personal and preventive health is heading, that’s why I am tracking the show every year. Here are my top 6 picks: 1. Kirin International Holding, Inc. Electric Salt Spoon: This innovative spoon uses electrical currents to enhance the perception of saltiness, helping those on low-sodium diets enjoy flavorful meals without added salt. 2. Eli Health Hormometer: An at-home saliva test for instant cortisol and progesterone readings, empowering users to monitor stress and hormone health from the comfort of home. 3. Circular Ring 2: With AI-enabled features, FDA clearance for ECG and AFib detection, and an 8-day battery life, this $380 smart ring sets new standards in wearable health monitoring. Launching in March, it surpasses its competitors in functionality. 4. Ozlo Inc. Sleep Earbuds agains snoring: Designed by ex-Bose Corporation engineers, these ultra-comfortable earbuds combine noise cancellation with sleep tracking, pausing audio playback when you fall asleep for uninterrupted rest. 5. Switle Body: A game-changer for elder care, this lightweight device cleans individuals in bed with minimal water and no mess. Adjustable temperature controls add comfort to its practical design. 6. FaceHeart Cardio Mirror: The FaceHeart Cardio Mirror measures blood pressure, heart rate, variability, respiration, oxygen saturation, stress, atrial fibrillation, and heart failure in 45 seconds going beyond other smart mirrors. Pricing and release are pending. Beyond these highlights, CES introduced a wave of innovations: • Smart Rings monitoring ECGs and sleep cycles, and other vitals even one out of 18k gold. • Interactive Wellness Mirrors acting as virtual fitness trainers eg. from FaceHeart and Withings. • Pain-Relief Wearables using microcurrent therapy for drug-free relief. What excites me most is how these technologies shift healthcare toward preventative care, empowering individuals to take control of their well-being before problems arise. I’d love to hear your thoughts—would you adopt any of these devices? How do you see them shaping the future of healthcare? #futureofhealthcare #ces2025

I believe AI creates real value when it tackles hard, physical problems — the kind that live in factories, warehouses, and service tasks. Recently, I learned the attached from a plastics machine manufacturer and logistics provider struggling with unpredictable production schedules, warehouse congestion, and reactive maintenance routines. When a structured AI implementation approach was brought into the equation the following outcome was achieved 👇 🔹 Smart Production Planning – Machine learning models forecasted demand and optimized resin batch production, cutting material waste by 18%. 🔹 AI-Driven Warehouse Logistics – Intelligent slotting and routing algorithms boosted order fulfillment rates by 25%, reducing forklift travel time and idle inventory. 🔹 Predictive Maintenance for Service Teams – Sensor data and pattern recognition flagged early signs of machine wear, reducing unplanned downtime by 30%. The result wasn’t automation replacing people — it was augmentation empowering people. Operators, warehouse managers, and service engineers gained real-time insights to make faster, better decisions. 💡 Takeaway: AI success in industrial environments isn’t about technology first — it’s about aligning data, people, and process to create measurable operational impact. #AI #IndustrialServices #SmartManufacturing #WarehouseOptimization #PredictiveMaintenance #DigitalTransformation #OperationalExcellence

Small Language Models + Edge Technology = A New Era in #Healthcare AI is revolutionizing healthcare, but it’s not just about large-scale systems. Small Language Models (#SLMs) on edge devices—like smartphones, wearables, and IoT sensors—are creating real-time, cost-effective solutions that transform patient care. These lightweight, localized AI models operate independently of the cloud, ensuring speed, affordability, and security—even in areas with limited connectivity. Here are four powerful ways SLMs on edge devices are already shaping the future of healthcare: 1️⃣ MedAide: Real-Time Diagnostics on Edge Devices Built for low-latency performance, MedAide delivers diagnostic support in remote areas or during emergencies. Think high-quality healthcare anywhere—without relying on robust infrastructure. 2️⃣ CLAID: Unlocking Digital Biomarkers CLAID processes sensor data from wearables and smartphones, enabling real-time monitoring of health metrics (heart rate, oxygen levels, movement). It empowers precision medicine and early condition detection like never before. 3️⃣ Abridge: AI-Powered Medical Transcriptions By summarizing patient-doctor interactions in real time, Abridge saves doctors hours on documentation. Less admin work, more patient care. 4️⃣ AliveCor: AI-Driven Cardiac Monitoring Portable ECG devices that track and analyze heart health in real time. FDA-approved and built for proactive care—whether at home or on the go. Why SLMs on Edge Devices Matter • Speed: No cloud dependency = faster processing. • Cost-Effective: Affordable solutions for wide-scale deployment. • Privacy-First: Localized data processing enhances security. The Future is Now From rural clinics to urban hospitals, SLMs are bridging healthcare gaps, driving efficiency, and saving lives. 💡 Are you ready to integrate AI into your practice? Let’s discuss how small language models and edge tech can enhance workflows, improve care, and shape the future of medicine. #HealthcareInnovation #ArtificialIntelligence #EdgeComputing #HealthTech #DigitalTransformation #DrGPT

𝗗𝗼 𝘆𝗼𝘂 𝗳𝗲𝗲𝗹 𝗪𝗲𝗮𝗿𝗮𝗯𝗹𝗲𝘀 𝗮𝗿𝗲 𝗹𝗶𝘃𝗶𝗻𝗴 𝘂𝗽 𝘁𝗼 𝘁𝗵𝗲𝗶𝗿 𝗲𝘅𝗽𝗲𝗰𝘁𝗮𝘁𝗶𝗼𝗻𝘀? Because this breakthrough just raised the bar significantly. Researchers have developed a wearable device that monitors glucose levels through sweat – and it doesn't stop there. This disposable patch integrates real-time glucose monitoring with automated transdermal drug delivery for diabetes management. 𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: ✅ 𝗡𝗼𝗻-𝗶𝗻𝘃𝗮𝘀𝗶𝘃𝗲 𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 – No more painful finger pricks ✅ 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 – Real-time glucose data from sweat analysis ✅ 𝗦𝗺𝗮𝗿𝘁 𝗱𝗿𝘂𝗴 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 – Automated treatment response when glucose levels spike ✅ 𝗪𝗲𝗮𝗿𝗮𝗯𝗹𝗲 & 𝗱𝗶𝘀𝗽𝗼𝘀𝗮𝗯𝗹𝗲 – Practical for everyday use This isn't science fiction. It's soft bioelectronics on human skin, creating a closed-loop system that monitors AND treats diabetes simultaneously. 𝗧𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝗿 𝗽𝗶𝗰𝘁𝘂𝗿𝗲? This technology represents the convergence of AI, wearables, and connected care – three pillars transforming healthcare delivery. We're moving from reactive treatment to proactive, personalized health management. For healthcare organizations exploring digital transformation, innovations like this answer the question: wearables aren't just living up to expectations – they're exceeding them by becoming active treatment devices, not just passive monitors. 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻: 𝗛𝗼𝘄 𝗾𝘂𝗶𝗰𝗸𝗹𝘆 𝗰𝗮𝗻 𝘄𝗲 𝘀𝗰𝗮𝗹𝗲 𝘁𝗵𝗶𝘀 𝗳𝗿𝗼𝗺 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝘁𝗼 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗰𝗮𝗿𝗲? What's your take? Are non-invasive biosensors the next frontier in chronic disease management? 📖 Research: Science Advances (DOI: 10.1126/sciadv.1601314) For more Wearables News and Expertise follow João Bocas #DigitalHealth #AIinHealthcare #Wearables #DiabetesCare #HealthTech #ConnectedCare #Innovation #HealthcareTransformation

𝗦𝘄𝗮𝗿𝗺-𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗘𝗺𝗯𝗼𝗱𝗶𝗲𝗱 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗔𝗜: 𝗙𝗿𝗼𝗺 𝗦𝗺𝗮𝗿𝘁 𝗠𝗮𝗰𝗵𝗶𝗻𝗲𝘀 𝘁𝗼 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝘃𝗲𝘀 Most factories today still operate with highly capable but largely independent systems i.e robots, machines, sensors, and planning engines working in silos. The next step in industrial intelligence is coordinated intelligence across many agents. Imagine a warehouse where AGVs negotiate routes in real time like ant colonies optimizing food paths, or assembly lines that reorganize themselves as soon as a machine fails — no emergency meetings required. Swarm-intelligent embodied Industrial AI applies the principles observed in nature i.e ants, bees, and bird flocks — where simple entities collaborate to solve complex problems through collective behavior. This enables: • Self-organizing production flows • Real-time adaptive logistics and scheduling • Distributed resource allocation without heavy central control • Resilient operations where performance continues even if individual    nodes fail 𝗥𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝘁𝗲𝘀𝘁 𝗰𝗮𝘀𝗲: Amazon Robotics fulfillment centers already operate thousands of mobile robots coordinating inventory movement, routing, and task allocation in real time. These systems combine shared robotic autonomy with centralized orchestration, demonstrating how collective robotic intelligence can complement central planning to achieve highly scalable automation. Similar swarm-based fleet orchestration pilots are now expanding into manufacturing logistics and intra-plant material movement. The enabling foundation is the Cloud–Edge–Terminal architecture, where machines, robots, and sensors act as embodied agents, edge systems coordinate real-time decisions, and cloud platforms provide learning and long-horizon optimization. The real shift underway is powerful: Factories are moving from automation of machines to orchestration of intelligent agent ecosystems. Organizations that design systems for collective intelligence, rather than isolated AI deployments, will unlock the next wave of operational performance. #IndustrialAI #SwarmIntelligence #SmartManufacturing #EdgeAI #DigitalFactories

🏥 Two #wearable companies. Combined valuation: over $20 billion. And we're just getting started. WHOOP has just raised $575 million in a Series G round at a $10.1 billion valuation. What is especially notable is not only the size of the round, but the signal behind it: investors include Abbott and Mayo Clinic. That suggests wearables are increasingly being seen not merely as consumer wellness products, but as strategically relevant assets in the future of healthcare. Meanwhile, ŌURA has been reported at roughly an $11 billion valuation, reinforcing the scale of market confidence in continuous, consumer-facing health monitoring. What makes this shift important is not just the hardware. It is the growing clinical relevance of continuous, real-world data. Recent literature shows that wearable technologies are moving beyond lifestyle tracking into more serious remote monitoring use cases. A new Nature Portfolio study demonstrated that #smartwatch-based monitoring can support the remote assessment of heart failure patients using continuous physiologic and behavioral data. A JMIR mHealth and uHealth systematic review further showed that wearables are increasingly used for chronic disease monitoring, especially in cardiovascular and neurological applications. At the same time, the real acceleration comes from analytics. As #AI-enabled interpretation improves, wearable data is becoming more actionable: not just raw signals, but contextualized information about recovery, stress, rhythm, activity, and deterioration risk. A JMIR systematic review on AI-enabled medical devices highlights wearable monitoring as one of the domains where AI is enabling more continuous, #personalized health management. This is why wearables are becoming strategically relevant beyond consumer tech. They are helping to push healthcare away from a model that mainly reacts to illness, and toward one that increasingly supports prevention, early detection, and continuous management. A recent European Heart Journal – Digital Health review describes wearable technologies as part of a transformation in cardiovascular care through continuous monitoring outside traditional clinical settings, while also making clear that large-scale impact still depends on validation, workflow integration, and governance. For those of us working in healthcare IT, the key question is no longer whether wearable-generated data will matter. The real question is: Are our health IT systems ready to receive, contextualize, and operationalize this data? #DigitalHealth #Wearables #RemotePatientMonitoring #PreventiveCare #AIinHealthcare #HealthcareIT #Interoperability #DigitalTransformation #Virgobit

Manufacturing innovation used to follow a predictable pattern. Build a prototype. Test it. Adjust it. Repeat. Trial and error. But AI is quietly replacing that process with something new. Simulation first manufacturing. One of the most powerful tools enabling this shift is the digital twin. A digital twin is a virtual model of a real world system. Factories, machines, production lines, even entire supply chains can now be simulated digitally before anything is built or changed. Physics informed AI models allow manufacturers to test: • equipment stress • production flow • failure scenarios • maintenance schedules inside simulations. Instead of experimenting on real machines, companies experiment in virtual environments first. The second big shift is happening in quality control. Computer vision systems are now inspecting products with precision that often exceeds human inspection. These systems can detect microscopic defects in: • electronics • automotive components • pharmaceuticals • consumer products Industry reports suggest AI vision adoption for quality inspection has already crossed 40% in some sectors. The third shift is about knowledge. Factories often rely on experienced technicians who carry years of institutional knowledge. But when those experts retire, knowledge can disappear with them. Large language models are now being used to build technical knowledge assistants for manufacturing teams. Technicians can ask systems questions like: “Why does this machine vibrate under load?” “What troubleshooting steps were used last time this fault occurred?” Instead of digging through manuals or calling senior staff, answers appear instantly. And finally, we’re seeing the rise of agentic AI in operations. These systems don’t just analyze information. They execute workflows. For example: • automatically triggering procure to pay cycles • coordinating maintenance scheduling • monitoring supply chain disruptions and recommending actions All with governance and human oversight. Manufacturing has always been about precision. What AI is doing now is extending that precision beyond machines to decisions, operations, and planning. The factories of the future won’t just be automated. They’ll be predictive. #Manufacturing #AI #ArtificialIntelligence #SmartManufacturing #DigitalTransformation #DigitalTwin #Simulation #ComputerVision #QualityControl #PredictiveMaintenance #AgenticAI #DeepTech