IoT Innovation Applications

Let's take a look at Bielefeld’s Obersee in Germany where we can learn more about effective environmental monitoring using a smart IoT system. From this lake, data like water quality, air conditions, and CO2 levels are being measured. This data is now captured and analyzed 24/7 via LoRaWAN technology, ensuring real-time monitoring. Doing that, one particular challenge is to prevent the risk of the shallow (2.50 meters deep) lake tipping over, especially during hot periods. Exactly this is happening right now at Paris Summer Olympic Games. The river Seine is too polluted and thus, prevents Triathlon and long distance swimming competitions to take place as planned. Was that predictable? Hard to say from a distance. But this is the intention of collecting all relevant data from Bielfeld's Obersee. The collected measurements from the lake and its surroundings serve to regulate artificial aeration. When negative values are detected in the lake, the aeration system activates at specific points to supply oxygen to the fish and therefor stabalize delicate balances in that ecosystem. To realize this application, we used a Smart City Box which includes: • PLCnext Control: Enables sensor diagnostics and in future ventilation control.   • LoRaWAN Gateway: Facilitates wireless transmission of sensor data around the Obersee.   • grovez.io: A web-based IoT platform making real-time and historical data visualization available for all stakeholders   • Cloud-to-Cloud Integration: Data accessible from the central MQTT broker.  This means the Smart City Box powered by PLCnext Technology ensures effective measures for sustainable environmental protection through the integration of decentralized sensors with various interfaces. These sensors provide real-time transparency into environmental data, including water turbidity and oxygen levels. Open interfaces, accessible even at the cloud level, allow data provision to all stakeholders. Additionally, automated and demand-oriented aeration control eliminates the need for manual measurements, resulting in energy, cost, and resource savings. Please let me know if you have any questions about this application. Can you imagine other applications for the IoT technologies used at the Obersee in different environmental conservation scenarios?  #lorawan #internetofthings #iiot #plcnext #cleantech #sustainability #smartcities

Real-time data analytics is transforming businesses across industries. From predicting equipment failures in manufacturing to detecting fraud in financial transactions, the ability to analyze data as it's generated is opening new frontiers of efficiency and innovation. But how exactly does a real-time analytics system work? Let's break down a typical architecture: 1. Data Sources: Everything starts with data. This could be from sensors, user interactions on websites, financial transactions, or any other real-time source. 2. Streaming: As data flows in, it's immediately captured by streaming platforms like Apache Kafka or Amazon Kinesis. Think of these as high-speed conveyor belts for data. 3. Processing: The streaming data is then analyzed on-the-fly by real-time processing engines such as Apache Flink or Spark Streaming. These can detect patterns, anomalies, or trigger alerts within milliseconds. 4. Storage: While some data is processed immediately, it's also stored for later analysis. Data lakes (like Hadoop) store raw data, while data warehouses (like Snowflake) store processed, queryable data. 5. Analytics & ML: Here's where the magic happens. Advanced analytics tools and machine learning models extract insights and make predictions based on both real-time and historical data. 6. Visualization: Finally, the insights are presented in real-time dashboards (using tools like Grafana or Tableau), allowing decision-makers to see what's happening right now. This architecture balances real-time processing capabilities with batch processing functionalities, enabling both immediate operational intelligence and strategic analytical insights. The design accommodates scalability, fault-tolerance, and low-latency processing - crucial factors in today's data-intensive environments. I'm interested in hearing about your experiences with similar architectures. What challenges have you encountered in implementing real-time analytics at scale?

How do you build the "digital brain" of a city? It rests on four essential platforms: 1️⃣ The Sensory & Video Platform This is your city's nervous system. It taps into a vast network of IoT sensors to gather real-time dynamic data on everything—water, traffic, public security... This gives administrators the rich data they need- 2️⃣ The Twin City Model Visualization Platform Imagine a detailed, interactive 3D model of your entire city—every building, road, bridge, and even underground pipe. This isn't just a static map. It's a dynamic virtual environment you can edit, analyze, and simulate on. 3️⃣ The Data Integration & Service Platform Here's where the intelligence comes in. This platform integrates all your city's data into one place, allowing you to analyze the status of any element in real-time. Over time, it learns to predict patterns in human flow, traffic, and other high-value information. 4️⃣ The Open-Source Application Platform Innovation shouldn't happen in a silo. By opening up data access, you empower businesses, developers, and the public to build diverse applications that improve urban governance for everyone. Cities like Helsinki did this, using 3D modeling for complex tasks like solar feasibility analysis. At a cost of €1 million (Source: World Economic Forum), the City of Helsinki has also used innovative modelling techniques to build two state-of-the-art 3D city models, a live-view Mesh model based on 50,000 tilted photographs and 11 terabytes of data ...and a CityGML model with rich semantic information based on the live-view Mesh model. Exciting times ahead...💰 --------- Follow me for #digitaltwins Links in my profile Florian Huemer

Smart cities: Essential elements for success In today's dynamic environment, we see technology all around us. This is especially true when it comes to smart cities. Smart cities use a variety of software, user interfaces, and communication networks alongside IoT to deliver connected solutions for the public that are citizen centric. What else is required for a city to become smart and function smoothly? Apart from fundamental components like people, commerce, and traditional urban infrastructure, four critical elements must be present for thriving smart cities: Extensive wireless connectivity: Smart cities are built on being able to share data between a vast array of interconnected devices. This would be rendered useless without a reliable wireless network. Open data: A key feature of a smart city is that all participants share information so that informed decisions can be made in real time which requires easy accessibility and availability of data. Security you can trust: With a wide array of devices in use and data being easily available, the threat of a cyberattack becomes very real. Thus, a smart city must have a reliable and trustworthy security system in place to protect the data and infrastructure from potential cyber-attacks. Flexible monetization: In the age of IoT and smart cities, data is key. For smart cities to thrive, we need to establish sustainable commercial operations that ensure all within the ecosystem are rewarded. A smart city must offer a monetization model that enables businesses to profit from the data generated while also ensuring that the city’s residents benefit from the services offered. Citizen centricity: citizen should be at the center of smart cities design. citizen/visitors journey should be very well crafted to around citizen and not technologies; as well around quality of live and not control. As we continue to innovate and develop smart cities, let's keep these elements in mind to ensure we build cities that benefit and prioritize the needs of their citizens. #SmartCities #Technology #Innovation #iot

Researchers have designed a game-changing, ring-like biosensor that monitors the hormone oestradiol in human sweat. This represents a leap in personalized healthcare, moving away from traditional, invasive methods to a non-invasive, real-time monitoring approach. Integrating aptamers with advanced microfluidics, this not only tracks fertility and menstrual cycles but also has potential applications in hormone therapy monitoring. Its ability to provide immediate health insights through a simple wearable device is nothing short of a marvel in biotechnology. What makes this technology so transformative is its potential to be adapted for various hormonal measurements, paving the way for a new era in personalized healthcare. Imagine having real-time data about your body's hormonal balance at your fingertips, revolutionizing how we approach health and wellness. The fusion of biotechnology with user-friendly devices opens a new frontier in healthcare, one that empowers individuals with unprecedented control over their health. How do you envision wearable technology evolving in the healthcare sector? Join the conversation below! #BuildWithBiology #Biosensor

What themes will keep #IoT vendors and adopters busy in 2025? 🤔 Here are my quick thoughts for 2025 based on recent signals and growing trends: 1️⃣ Edge Computing 🌍 The need to run IoT workloads locally—where data is produced—will grow. Drivers like cost efficiencies, regulations, privacy concerns, unstable connectivity, and latency will push this demand. While the cloud remains critical, cloud-to-edge flows and requests for cloud-like capabilities at the edge will dominate discussions across industries. 2️⃣ Generative AI + IoT (#GenAIoT) 🤖 Combination of #GENAI with IoT will become a thing, in three key areas: • Optimizing #Maintenance: Real-time IoT data + manuals/SOPs = standardized processes, improved worker productivity, faster onboarding, and reduced costs. • New Data #Insights for connected products: Unlock patterns in product usage, user habits, and market trends to drive new revenues. • GENAI at the #Edge: A growing exploration area as businesses seek to understand the what, how, and why. 3️⃣ Data #Foundations 📊 Prioritization to build a proper data foundation , either by modernizing tech stacks or starting fresh, for scalable AI deployments, Digital Twins, data sharing, and simplifying IoT ecosystem collaboration. 4️⃣ Security as #Differentiation 🔒 IoT vendors will invest more in security (a must!) while proactively promoting security features as a competitive advantage. 5️⃣ #Regulation, #Cost Optimization & #Sustainability 🌱 These drivers will fuel IoT adoption in energy, manufacturing, logistics, and the public sector. Expect growing momentum in healthcare, tourism, well-being, and aerospace/defense. 6️⃣ Tech #Synergies & Interoperability 🤝 Combining successfully IoT with Edge, #AI, GENAI, and #Spatial tech can define success. Open ecosystems and interoperability across machines, vendors, and protocols will be critical—especially with AI #Agents needing diverse IoT data inputs. 💬 Do these resonate with your view of IoT themes for 2025? What would you add— #eSIMs, #5G, hardware cost reductions? Let’s discuss! 🚀 One thing is clear: It’s still Day 1 for IoT, with plenty of scaling, but also with exploration ahead. 🥂Cheers to an exciting year for #IoT! #IoT2025 #IoTPredictions #InternetofThings #EdgeComputing #GenerativeAI #iotforall #IoTCouncil IoT For All #DimitriosIoT

Is the future of wearable technology more than just fitness?   I felt like posting about wearable technology today. I’ve always been fascinated by wearables. I’ve tried numerous devices through the years with various form factors. Sadly, I haven’t really stuck with any for more than a few months. In my opinion, many of the devices are good if you’re a first-time fitness enthusiast and if you care about sleep measurements. Both very important of course. That said, I feel that the future of wearables is much more revolutionary. I think whilst current wearables offer useful metrics, this only scratches the surface of their potential.    I believe we are approaching a time where wearables will be more about health than wellness. We are moving well beyond simple step counts and heart rate monitors. Advancements in biosensors, nanotechnology and AI will make this achievable. In one of my previous roles some years ago, we experimented with wearable technology, and even then, I always felt the future would be about medical-grade wearables.   Next-gen wearables will not only monitor your heart rate but also track blood glucose levels, hydration, and even biomarkers for early disease detection. AI-driven medical diagnostics is a game changer. Quite apart from physiology, future wearables will have the potential to analyse brain wave patterns and stress indicators. Wow, that would open a whole new use case for mental health management.    One of the pain points with wearables is battery life. We would love for these devices to last weeks on a single charge. Well, that might be possible with the utilisation of solar, kinetic energy or who knows, even body heat to extend battery life. And then there’s the potential for flexible electronics to turn clothing into interactive health systems. A good percentage of wearables in the not too distant future will be embedded into everyday clothing. How’s that for always-on health monitoring!   The possibilities are massive. With the cost of healthcare around the world, we need more systems that focus on preventive healthcare. If we can do that, catching illnesses before they occur will mean we are in the realm of extending lifespans and enhancing well-being.    #WearableTech #HealthTech #PreventiveHealthcare 

"Industrial IoT Middleware for Edge and Cloud: The OT/IT Bridge with Apache Kafka and Flink" => Modernization of industrial IoT integration and the shift toward cloud-native architectures. As industries embrace digital transformation, bridging Operational Technology (OT) and Information Technology (IT) has become crucial. The OT/IT Bridge plays a vital role in industrial automation by ensuring seamless data flowbetween real-time operational processes and enterprise IT systems. This integration is fundamental to the Industrial Internet of Things (#IIoT), enabling industries to monitor, control, and optimize their operations through real-time data synchronization while improving Overall Equipment Effectiveness (#OEE). By leveraging Industrial IoT middleware and data streaming technologies like #ApacheKafka and #ApacheFlink, businesses can establish a unified data infrastructure, enabling predictive maintenance, operational efficiency, and smarter decision-making. Explore a real-world implementation showcasing how an edge-to-cloud OT/IT bridge can be successfully deployed: https://lnkd.in/eGKgPrMe

𝐁𝐫𝐢𝐝𝐠𝐢𝐧𝐠 𝐭𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠: 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐈𝐨𝐓 𝐆𝐚𝐭𝐞𝐰𝐚𝐲𝐬 🌐 The boundary between Information Technology (IT) and Operational Technology (OT) has long hindered holistic industry operations. Industrial IoT gateways are the champions heralding change. ✨ 𝐒𝐧𝐚𝐩𝐬𝐡𝐨𝐭 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬: - The IIoT gateway market surged ~14.7% within a year, nearing the $860 million mark, and this trajectory is predicted to continue through 2027. - Major players in this shift are Cisco, Siemens, Advantech, and MOXA. 🏭 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 𝐄𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧: IIoT gateways are pivotal in reshaping the manufacturing landscape. By retrofitting even older systems, they facilitate real-time data exchange between operations and IT/cloud realms. This harmonization yields key outcomes: reduced downtimes (as illustrated by Vitesco's preemptive malfunction detection), significant labor cost reductions, and optimized energy use. The result? Streamlined operations, significant savings, and enhanced productivity. 🚀 🛠️ 𝐃𝐞𝐞𝐩 𝐃𝐢𝐯𝐞: 1) 𝑰𝑻/𝑶𝑻 𝑺𝒚𝒏𝒄𝒉𝒓𝒐𝒏𝒊𝒛𝒂𝒕𝒊𝒐𝒏: Legacy equipment, often disconnected, is now plugged into the digital grid. IIoT gateways serve as conduits, ensuring swift, seamless data transitions to IT platforms. 2) 𝑮𝒂𝒕𝒆𝒘𝒂𝒚 𝑭𝒓𝒂𝒎𝒆𝒘𝒐𝒓𝒌𝒔: They're not one-size-fits-all. Four distinct architectures accommodate diverse enterprise needs, ensuring smooth data flows and heightened efficiency. 3) 𝑽𝒆𝒓𝒔𝒂𝒕𝒊𝒍𝒊𝒕𝒚: Modern IIoT gateways juggle multiple roles - from protocol translation to security management, making them indispensable in a robust IIoT ecosystem. 💼 𝐅𝐮𝐫𝐭𝐡𝐞𝐫 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬: 1) 𝑺𝒐𝒇𝒕𝒘𝒂𝒓𝒆 𝑴𝒊𝒈𝒓𝒂𝒕𝒊𝒐𝒏: Companies are transitioning key applications to the cloud, elevating IIoT gateways as primary data traffic controllers. 2) 𝑯𝒂𝒓𝒅𝒘𝒂𝒓𝒆 𝑬𝒗𝒐𝒍𝒖𝒕𝒊𝒐𝒏: Gateways now sport multi-core processors, AI chipsets, and enhanced security elements, ensuring swifter and safer data processing. 3) 𝑩𝒆𝒏𝒆𝒇𝒊𝒕: IIoT gateways have led to profound IT/OT integrations. Examples include Vitesco Technologies Italy's advanced malfunction prediction and Corpacero's reduced repair costs thanks to predictive maintenance. The once aspirational fusion of IT and OT is now tangible, courtesy of IIoT gateways. The forthcoming industrial epoch? Seamlessly integrated, vastly efficient, and pioneering. 🔍 Source: IoT Analytics (https://lnkd.in/euj3wiUD)

Personalised risk assessment leveraging IoT sensor technology and machine learning... These researchers developed an integrated monitoring system including sensors that measure potentially harmful agents like dust, noise, ultraviolet radiation, illuminance, temperature, humidity, and flammable gases. The data collected by these sensors was then processed using machine learning algorithms to provide real-time, personalised safety recommendations. The system tested comprised wearable monitoring devices, a server-based web application for employers, and a mobile application for workers. By integrating health histories of workers, such as common diseases and symptoms related to the monitored agents, the system generates actionable alerts. These alerts are suggested to help companies make informed decisions to protect their employees from environmental hazards, both in immediate situations and for long-term safety planning - ideally improving work design. The research was conducted in lab conditions but proved which type of machine learning can be applied to different hazardous agents and the researchers determined that models can be applied to other agents not tested. So what? My thoughts are that it is likely we will see more hyper-personalised risk assessments leveraging IoT sensors in the future; either wearable or strategically located in workplaces. We've been observing this trend for some time, but with the advancements in machine learning, we now have the opportunity to understand much better how several different hazardous agents interact with each other and therefore, ideally, we have the intelligence needed redesign workplaces for the better; and we can also support individuals who have pre-existing exposures or vulnerabilities to thrive in the workplace. You can access this open source research here: https://lnkd.in/ggZpGRFS Follow my profile and these hashtags for more: #SafetyTechResearch #SafetyInnovation #SafetyTech and #SafetyTechNews