IoT Innovation Applications

China just bent the rules of electronics — literally. Facinating? Chinese and global researchers are advancing Metal-Polymer Conductors (MPCs) — circuits made from liquid metals like gallium–indium embedded in elastic polymers — that defy traditional rigid wiring by remaining conductive even when stretched up to 500% or more. Why this is a big deal: 🔹 High Stretchability: Certain liquid-metal conductors maintain electrical conductivity even when stretched 5× their original length. 🔹 Durability: Printable metal-polymer conductors can withstand over 10,000 cycles of stretching with minimal resistance change (<3%). 🔹 Conductivity: Hybrid conductors based on indium alloys can achieve extremely high conductivity (~2.98 × 10⁶ S/m) with minimal resistance change under extreme strain. 🔹 Fine Feature Sizes: Advanced techniques can pattern circuits as small as 5 micrometers, rivaling conventional PCBs. Market Insight: The global market for wearable and flexible devices is expected to surge into the hundreds of billions of dollars, with advanced stretchable materials at the core of the next wave of innovation. (Wearable tech projected >US$150B by 2026 in soft electronics growth — wearable industry data) Where AI Fits In: AI is not just hype — it’s accelerating how we design and discover materials like MPCs. AI/ML models help predict material properties — like conductivity and mechanical resilience — before physical prototypes are made. Computational simulations can evaluate thousands of polymer + metal combinations far faster than physical testing alone. AI-assisted optimization reduces lab iterations, cutting time and cost in early-stage development. In other words: AI + materials science = faster discovery of smarter, stretchable electronics. Potential Applications: Soft robotics that mimic human motion Wearables that feel like fabric Artificial skin with embedded sensing Health monitoring devices that conform to the body On-skin motion recognition and bioelectronics. The era of electronics you can twist, stretch, and wear is here — and AI is helping make it a reality. #FlexibleElectronics #MaterialsScience #AIinInnovation #SoftRobotics #WearableTech #DeepTech #FutureOfElectronics #Innovation

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

My 8 #observations from the top industrial expo HANNOVER MESSE last week, by talking with #AWS customers, partners, the industrial community, walking around some halls and from my LinkedIn network. What are yours? 1️⃣ Industrial Edge is growing in terms of adoption, customer interest and vendor maturity. In addition, #IndustrialEdge is taking the role of simplifying and accelerating the path to industrial cloud where industrial companies can leverage #MachineLearning and #GenerativeAI. Great example is the work of Siemens, Eurotech, Belden Inc. with pre-integrated edge offerings with AWS (incl. AWS IoT SiteWise). 2️⃣ Better and broader #Collaboration among multiple vendors for end to end #IIoT solutions. You can read here one of my favorite #examples with 5 vendors: Vodafone, Amazon Web Services (AWS), Treedis, Matterport and ifm with several system integrators supporting this offering. https://lnkd.in/ewSdVRSD 3️⃣ While projects and customers are becoming more mature, Industrial #DataOps (or similar names) is becoming a big theme for 2024. And these data ops are required to be managed locally per site, not only centrally from HQ etc. The collaborations here will make a big difference, like #AWS with HighByte, Litmus, Cognite and Edge2Web, Inc. 4️⃣ #GenerativeAI was in most of the booths and in almost a 'humble way'. I say humble because I was afraid I will see many exhibitors talking only about this, forgetting about other industrial tech and use cases. The use case of the industrial virtual assistant in factories/operations was the main use case. 5️⃣ All #telecom booths that I came across (Telefónica, Vodafone, Ericsson and I think GSMA) promoted their #5G #PrivateNetworks offering. Is there enough market demand though? 6️⃣ Manufacturers are trying hard to find the balance between: A. Scaling their 'connected factory' concept to more factories and B. Adding more use cases in their existing connected factories. Both paths A and B require lots of time, energy, resources (people and money) and top down, bottom up ambition. Some new ideas were shared from #AWSIoT customers, like Siemens Energy, Gousto and Klöckner Pentaplast during their presentations. What are your best practices? 7️⃣ #Sustainability combined with #regulations, cost reductions, data integration and #traceability. This time customers and vendors tried to capture all these themes and benefits together. #Circulareconomy was maybe the best example of how these concepts come together. It is still early days though.. 8️⃣ #Hydrogen energy solutions were the top energy topic in couple of energy related booths. #Norway (the partner country #HM24) led the way with the message: “Norway 2024: Pioneering the Green Industrial Transition”. #EuropeanUnion, #Turkey and few other countries were present with big energy booths as well. What are your key observations or #surprises from #HM24? #HannoverMesse #trends #IndustrialIoT #SmartManufacturing #Industry4 #DimitriosIoT

Are we doing enough to make energy affordable and sustainable? As we tackle the demand for energy in a growing world, there’s a pressing question we can’t ignore: How do we ensure that everyone has access to clean, affordable energy without compromising the environment? Sustainable Development Goal #7 is all about addressing this need—ensuring reliable, sustainable, and modern energy for everyone. Take a closer look at how smart technology is transforming the energy landscape. The rise of IoT in renewable energy, for example, has been nothing short of remarkable. Through IoT sensors, we’re not just generating solar or wind power—we’re monitoring, optimizing, and even predicting energy use in real-time. These sensors allow businesses to adjust based on demand, helping to make renewable energy sources more resilient and cost-effective. Consider a business using solar panels or wind turbines to generate its own electricity. With smart grid tech, they can manage power locally, rather than depending solely on a centralized grid. The result? Reduced costs and improved energy efficiency. And it’s not just about generating power; AI and machine learning models help organizations identify peak hours to tap into energy sources efficiently, saving both money and resources. Measuring impact is essential. For many companies, tracking the real-time effects of their energy choices is critical. IoT sensors can monitor energy usage continuously, allowing organizations to prove their progress toward sustainability. By using data instead of manual reports, they can also show customers and employees that they’re taking meaningful action. And then there’s the financial side: How to allocate resources effectively. Data from these smart systems enables leaders to make thoughtful decisions about where to focus their budget. If a particular renewable project shows a greater impact, they can prioritize that effort, optimizing both sustainability and cost efficiency. It’s easy to talk about sustainability, but taking measurable steps—and having the data to back it up—makes a difference. As more organizations embrace these tools, we’re seeing a shift in how companies approach energy, balancing their environmental responsibilities with practical, business-focused strategies. Where do you see your organization on this journey?

🚀 #𝑰𝒐𝑻 𝒂𝒏𝒅 #5𝑮 𝑹𝒆𝒅𝑪𝒂𝒑: 𝑼𝒔𝒆 𝑪𝒂𝒔𝒆𝒔 𝒂𝒏𝒅 𝑶𝒑𝒑𝒐𝒓𝒕𝒖𝒏𝒊𝒕𝒊𝒆𝒔! 🌐 The evolution of the Internet of Things based on the new 5G RedCap (Reduced Capability) evolution, which is included as part of the #5GAdvanced already available by companies such as Huawei, enables new use-cases as presented by the GSMA - Internet of Thing #RedCap is a game-changer for connecting devices across industries with moderate data rates, low power, and cost efficiency. Based on my experiences during the MWC Shanghai, it has very clear applications and benefits for industry, smart grids, and smart cities. The report from the GSMA presents an analysis of the most relevant and impactful use cases: 🔋 𝐒𝐦𝐚𝐫𝐭 𝐆𝐫𝐢𝐝𝐬 #Grid360: 5G RedCap revolutionises power systems by enabling real-time monitoring and remote control of grid equipment and network. This enhances grid reliability and energy distribution and supports green energy initiatives. Large-scale deployment has already reduced terminal costs by 50% and energy consumption by 32%. Libelium is working with Red Eléctrica, Telefónica and AWS Public Sector on #Grid360 to monitor environmental parameters for #DLR algorithms to optimize the network maintenance and performance in isolated areas: https://lnkd.in/dvtEth9a José Antonio Cabo Alejandro Pujante 🏙️ 𝐒𝐦𝐚𝐫𝐭 𝐂𝐢𝐭𝐢𝐞𝐬 #Envair360: From environmental monitoring to smart parking solutions the technology facilitates real-time data collection, enhances traffic management, and supports sustainable urban development. Libelium is extending the current Parking solution with the emerging Parking V3 that extends the support from Sigfox 0G technology UnaBiz and LoRa Alliance to new Radios such as #NBIoT and soon #RedCap. Yuri Javier We are supporting the Internet of Video Things #IoVT with the extension of our solutions for Low Emission Zones, Environmental Monitoring and Traffic Optimization in #Envair360, extending with #RedCap the inclusion of Radar, Cameras, complementing our capabilities of people counting, air quality and noise monitoring: https://lnkd.in/dcfF-6zS Andrea John David Noel Claudia Africa Jesús 🏭 𝐒𝐦𝐚𝐫𝐭 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 #LibeliumOne: Manufacturing processes are becoming more intelligent and safer. 5G RedCap is a catalyst for digital transformation across industries, offering scalable, low-cost, and energy-efficient solutions. The key benefits of 5G RedCap are the convergence of Artificial Intelligence, #EdgeComputing, and IoT. For that purpose, we are enabling, together with SECO and Red Hat in AI REDGIO 5.0, the capabilities of merging 𝔼𝕕𝕘𝕖 𝕩 𝕀𝕠𝕋 𝕩 𝔸𝕀 Libelium has launched a game changer for IoT, AI and edge computing integration called #LibeliumOne: https://lnkd.in/dkbKcyx7 Eduardo Pedro Aya Javier and Ángel. #IoT #5GRedCap #SmartGrid #SmartCity #SmartManufacturing #Innovation #DigitalTransformation #5G

What connects Industrial IoT, Application and Data Integration, and Process Intelligence? During my time at Software AG, my attention has shifted in line with the company's strategic priorities and the changing needs of the market. My focus on Industrial IoT, moved into Application and Data Integration, and now I specialise on Business Process Management and Process Intelligence through ARIS. While these areas may appear to address different challenges, a common thread runs through them. Take a typical production process as an example. From raw material intake to finished goods delivery, there are countless interdependencies, processes and workflows, and just as many data sources. Industrial IoT plays a key role by capturing real-time data from machines and sensors on the shop floor. This data provides visibility into equipment performance, production rates, energy usage, and more. It enables predictive maintenance, reduces downtime, and supports continuous improvement through real-time monitoring and analytics. Application and Data Integration brings together data from across the value chain, including sensor data, manufacturing execution systems, ERP platforms, quality management systems, logistics, and supply chain management. Synchronising these systems with integration creates a unified, reliable view of production operations. This cohesion is essential for automation, traceability, quality management and responsive decision-making across departments and geographies. Process Management, including modelling, and governance, risk, and controls, takes a different yet equally critical perspective. Modelling helps design optimal process flows, while governance frameworks ensure controls are in place to manage quality, risk, and enforce conformance for standardisation. Process mining uncovers bottlenecks, rework loops, and compliance deviations. It focuses on how the production process actually runs, rather than how it was designed to operate. Despite their different vantage points, each of these domains works toward the same goal: aggregating, normalising, and structuring data to transform it into information that can be easily consumed to create meaningful, actionable insights. If your organisation is capturing process-related data through isolated tools, such as diagramming or collaboration platforms, quality management systems, risk registers, or role-based work instructions, it is likely you are only seeing part of the picture. Without a unified approach to integrating and analysing this data, the deeper insights remain fragmented or out of reach. By aligning physical operations, applications & systems, and business processes, organisations can move beyond surface-level visibility to uncover the root causes of inefficiency, unlock hidden potential, and govern change with clarity and confidence. #Process #Intelligence #OperationalExcellence #QualityManagement #Risk #Compliance

🚀 AI-Powered Industrial Revolution: How Rockwell Automation is Shaping the Future of Smart Manufacturing Artificial Intelligence and Generative AI are transforming industrial automation, and Rockwell Automation is at the forefront of this revolution. By embedding AI into manufacturing execution systems (MES), digital twins, industrial IoT, and supply chain optimization, Rockwell is unlocking new levels of efficiency, productivity, and resilience in industrial operations. 💡 Key AI Innovations by Rockwell Automation: ✅ Predictive Maintenance – AI-driven analytics reduce machine downtime and optimize performance. ✅ Generative AI for Industrial Design – AI automates engineering workflows, system design, and PLC programming. ✅ AI-Powered Industrial IoT (IIoT) – FactoryTalk InnovationSuite provides real-time monitoring and predictive insights. ✅ AI in Supply Chain Management – Intelligent forecasting, risk assessment, and logistics optimization. 🌍 The Bigger Picture: AI is driving autonomous manufacturing, edge computing, and human-machine collaboration, making industrial automation smarter, faster, and more resilient. Competitors like Siemens, ABB, Schneider Electric, and Honeywell are also investing in AI, but Rockwell’s integrated approach to AI-powered automation gives it a competitive edge. ⚠️ Challenges & Considerations: 🔹 AI model accuracy and reliability in critical industrial processes. 🔹 Cybersecurity risks in AI-driven industrial control systems. 🔹 Regulatory compliance with NIST, ISO, and the EU AI Act for AI governance. The future of industrial automation is AI-driven, autonomous, and adaptive. Rockwell Automation is shaping that future by blending AI, IoT, and automation to build the factories of tomorrow. 💬 What do you think about AI’s role in industrial automation? How do you see AI transforming manufacturing in the next decade? Drop your thoughts below! ⬇️ #AI #Automation #Industry40 #SmartManufacturing #RockwellAutomation #IndustrialAI

Implementing IoT solutions for monitoring and managing energy consumption requires an integrated vision combining technology, data analysis, security, and sustainability to achieve significant efficiency and cost savings. Internet of Things (IoT) IoT refers to a network of physical devices that communicate via the Internet. These include sensors, smart meters, thermostats, and HVAC systems, all of which work together to collect and share real-time energy consumption data. Energy Consumption Monitoring Using smart sensors and meters allows real-time tracking of energy use, enabling the identification of inefficiencies and the implementation of immediate corrective measures to reduce unnecessary energy expenditure. Energy Management Automation systems in IoT can control lighting, heating, and cooling based on environmental data and occupancy. This optimization reduces energy waste without compromising comfort and operational needs. Data Analysis Advanced data analysis techniques, including big data and machine learning, help identify trends and consumption patterns. These insights drive long-term energy-saving strategies and continuous improvement in energy performance. Integration with Existing Systems Ensuring compatibility and seamless integration of new IoT devices with existing systems is crucial. Interoperability allows for smooth data exchange and functionality, enhancing overall system efficiency. Data Security Protecting the data collected by IoT devices is essential. Implement robust security measures, including encryption and access control, to safeguard sensitive energy data and ensure only authorized personnel have access. Economic and Environmental Benefits Efficient energy management leads to substantial operational cost savings, and reducing energy consumption supports corporate sustainability goals by lowering the organization’s carbon footprint. Implementation and Maintenance The implementation process includes planning, device installation, system integration, and staff training. Ongoing maintenance and regular updates ensure the IoT systems remain efficient and effective over time. Regulations and Standards Compliance with local and international energy management and IoT standards is vital. Certifications ensure the quality and security of the IoT solutions, meeting regulatory requirements and industry best practices. Staff Training Training staff on the use and maintenance of IoT systems is essential. Building an energy-conscious culture within the organization promotes efficient energy use and maximizes the benefits of IoT solutions. #IoT #EnergyManagement #BusinessEfficiency Ring the bell to get notifications 🔔

Companies often start their IIoT journey by connecting machines and installing sensors. But real industrial value comes when those connected systems improve operations, reduce downtime, and optimize production. Industrial IoT (IIoT) is not just about collecting machine data — it’s about turning operational data into measurable improvements across manufacturing systems. From monitoring equipment health to optimizing supply chains and simulating digital twins, IIoT enables factories to become data-driven and intelligent. This framework shows six key areas where IIoT delivers the most operational impact. ➞ Asset Monitoring Track machine performance in real time using connected sensors and centralized dashboards. ➞ Predictive Maintenance Use IoT data and analytics to predict failures and schedule maintenance before breakdowns occur. ➞ Quality Optimization Monitor production processes continuously to detect defects and improve product consistency. ➞ Energy Management Analyze energy consumption across machines and facilities to optimize efficiency and reduce costs. ➞ Supply Chain Integration Connect production systems with logistics and enterprise platforms for end-to-end operational visibility. ➞ Digital Twin Integration Create virtual replicas of machines and processes to simulate scenarios and optimize performance. Industrial IoT turns factories into connected, intelligent production systems. 🔁 Repost if you’re building the future of smart manufacturing. ➕ Follow Nick Tudor for more insights on AI + IoT systems that actually ship.

🏥 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