The Internet of Things (IoT) Explained: How It Works and Why It Matters

By J. Philippe Blankert, 22 February 2025

Imagine your alarm clock not only wakes you up, but also signals your coffee maker to start brewing. This is not sci-fi – it’s part of the Internet of Things (IoT), a rapidly growing web of interconnected devices. In simple terms, IoT refers to everyday objects and machines that are connected to the internet so they can collect and share data – all with minimal human input. In fact, estimates suggest there will be over 75 billion such connected devices in use by 2025(nccoe.nist.gov). This article breaks down what IoT is in plain language, how it works, and how it’s used in the real world – from smart cities and hospitals to farms and factories. We’ll also see how businesses use IoT for efficiency, and how Artificial Intelligence (AI) makes IoT even smarter.

What is the Internet of Things?

The Internet of Things (IoT) broadly encompasses all physical objects – or “things” – that are connected to the internet and able to communicate with each other (fm-house.com). These can range from simple sensors and household appliances to industrial machines and city infrastructure. What makes an object part of the IoT is connectivity (it can send/receive data) and often some level of “smart” functionality. IoT devices are typically equipped with sensors or actuators and software that let them gather information about their environment, share that data with other devices or cloud systems, and sometimes act on it. Ultimately, the goal is to help us – the users – gain useful information, solve problems, or automate tasks (fm-house.com) without needing constant human intervention.

In essence, IoT turns stand-alone things into part of a connected network. For example, a light bulb in a smart home can “talk” to the internet – allowing you to control it with your phone or voice assistant. A weather sensor might send temperature readings to an online database. Even a cow in a field can be part of IoT if it’s fitted with a tracker that reports its location and vital signs to a farm’s monitoring system. All of these are IoT devices or nodes on the network of things.

How Does IoT Work?

While IoT can sound abstract, the way it works is straightforward. Every complete IoT system has a few key components working together (leverege.com).

Sensors/Devices: First, the device itself collects data from its environment. It may have built-in sensors to measure things like location, temperature, motion, light, or vital signs. For instance, a thermostat senses the temperature, and a fitness wearable might detect your heart rate. The data collected can be very simple (e.g. a single temperature reading) or more complex (a video feed from a security camera) (com).
Connectivity: The gathered data is then sent somewhere to be processed. This requires a network connection. IoT devices may connect to the internet or a local hub via various methods: Wi-Fi in your home, cellular 4G/5G networks, Bluetooth, satellite links, or low-power long-range networks (LPWAN) for remote sensors. In some setups, devices talk to a nearby gateway (like a home router or an on-site hub) that aggregates data and sends it to the cloud. The common goal is to transmit the device’s data to a server or cloud platform where it can be analyzed and stored.
Data Processing: Once the data reaches the cloud or a central server, software takes over. Here the system can process and analyze the data. This could be as simple as checking if a reading falls within an acceptable range, or as complex as running advanced analytics or AI algorithms on streams of data. For example, a sensor might send an alert if temperature readings are too high, or a security camera system might use computer vision (AI) to recognize a person in its video feed. This is where raw data turns into meaningful information.
User Interface & Action: Finally, the system delivers useful output to end-users – or even directly back to devices. The processed data might trigger a notification or alert (e.g. an app notification that your front door camera detected movement, or a text that a machine in the factory needs maintenance). Often, there’s a user interface (like a mobile app or web dashboard) where people can monitor conditions or make adjustments. In many cases, the IoT system can also take automatic action based on the data, without waiting for a user. For instance, a smart thermostat can automatically turn the heat down if it detects no one is home, or a sprinkler system can switch off when soil moisture is adequate. These automated actions follow predefined rules or intelligent algorithms, making the “things” respond in real time to the information they receive.

To put it simply, IoT works like a feedback loop: devices collect data, send it through a network for processing, and then either a person or the system itself acts on the results. This cycle can run continuously and often invisibly in the background. The end result is smarter systems that can adapt and respond, creating convenience and efficiency.

Now that we know what IoT is and how it functions, let’s explore some real-world applications. While many people think of consumer gadgets (like smart TVs or fitness trackers) when they hear IoT, its impact goes far beyond the home. Below we look at how IoT is being used in smart cities, healthcare, agriculture, and various industries.

IoT in Smart Cities

Modern cities are using IoT technology to become “smart cities” – more efficient, sustainable, and livable. This involves placing sensors and connected devices throughout the urban infrastructure, from roadways to power lines, and using the data they generate to improve city services. Here are a few key smart city applications of IoT:

Traffic Management: Cities are installing IoT sensors to monitor traffic flow, congestion, and public transit usage in real time. Traffic lights can adjust their timing based on sensor data to optimize traffic flow, and transit agencies can reroute buses or trains according to live conditions. By analyzing data from cameras, GPS devices, and road sensors, city operators can identify patterns and reduce bottlenecks. In short, IoT helps optimize transportation networks, cutting down on commute times and traffic jams (com). For example, London has unified data from CCTV, sensors, and ticketing to predict passenger loads on trains and help distribute crowds evenly (rishabhsoft.com). Such measures improve travel efficiency and reduce frustration for commuters.
Energy Efficiency: A smart city leverages IoT to better manage energy use in buildings, streetlights, and the power grid. Sensors can monitor how much electricity is being used in real time and adjust lighting or thermostat settings automatically to avoid waste. For instance, smart streetlights can dim or brighten based on the time of day or presence of people, saving electricity. IoT devices can also coordinate with smart grids – electrical grids that adjust distribution based on demand – to distribute power more evenly and incorporate renewable sources. By monitoring energy consumption patterns, cities can identify where to conserve energy, leading to lower costs and emissions (com). Copenhagen, for example, deployed smart heating grids and integrated electric transport to reduce carbon emissions, illustrating IoT’s role in urban sustainability (rishabhsoft.com).
Waste Management: Even garbage collection gets smarter with IoT. Cities are placing sensors in trash bins and dumpsters that measure fill levels. This data is sent to waste management centers so that garbage trucks can be dispatched only when needed and via optimal routes. The result is fewer unnecessary collection trips, saving fuel and labor, and ensuring that bins don’t overflow. By routing garbage trucks based on real-time data, cities reduce traffic from waste collection and cut operational costs. These IoT-enabled trash systems help minimize waste overflow and fuel consumption, making garbage collection more efficient and eco-friendly (com). For instance, in some cities a sensor notifies the collection team when a specific dumpster is almost full, so they can adjust the pickup schedule rather than sticking to a fixed routine.

Smart city IoT solutions aren’t limited to these areas; they also include environmental monitoring (air quality sensors), public safety (connected cameras and gunshot detectors), and city services (smart parking apps, water leak detection, etc.). Altogether, IoT technologies can significantly improve a city’s functionality – reducing congestion, cutting energy waste, optimizing public services, and improving quality of life for residents (rishabhsoft.com).

IoT in Healthcare

In healthcare, IoT is enabling a new era of connected medical devices and proactive patient care. The Internet of Medical Things (IoMT) refers to networks of wearables, sensors, and smart medical equipment that monitor patient health and streamline hospital operations. These devices can collect vital health data in real time and share it with doctors or cloud databases. Several important applications include:

Remote Patient Monitoring: This is one of the most widespread IoT applications in healthcare. Remote patient monitoring means using connected health devices to track patients’ vital signs and symptoms when they’re outside the hospital – often at home (net). For example, wearable ECG monitors, blood pressure cuffs, or blood glucose sensors can automatically measure a patient’s stats throughout the day and send those readings to their healthcare provider. If something is out of the ordinary – say, a heartbeat becoming irregular – the system can alert doctors or caregivers immediately. This IoT-driven approach eliminates the need for frequent in-person checkups just to gather routine data. Patients with chronic conditions can be watched over in real time without leaving their homes, which is especially valuable for the elderly or those in remote areas. Overall, remote monitoring through IoT leads to faster intervention when issues arise and has been shown to improve patient outcomes (binariks.com).
Smart Medical Devices and Wearables: Beyond dedicated remote monitoring tools, many other medical devices are IoT-enabled. Smart infusion pumps, for instance, can automatically regulate and log medication dosages and send alerts if something needs attention. Wearable fitness and health trackers (like smartwatches or chest straps) record exercise, sleep, heart rate, and other metrics, helping individuals and doctors track wellness continuously. In hospitals, connected equipment like smart beds can detect if a patient has moved or fallen, and ingestible sensors can transmit data from within a patient’s body (such as confirming if a patient has taken their medication). These IoT devices gather a wealth of health data seamlessly. Healthcare professionals can access this data on dashboards that give a holistic view of a patient’s condition, allowing for more informed and timely decisions. The continuous stream of data means doctors get an ongoing picture of patient health rather than a snapshot only during visits.
Predictive Diagnostics and Maintenance: IoT in healthcare isn’t just about patient monitoring – it’s also about maintaining the equipment and predicting health issues before they escalate. Smart sensors on medical equipment (like MRI or X-ray machines) can monitor performance and predict maintenance needs, alerting technicians to service a device before it breaks down. This reduces equipment downtime at hospitals. More ambitiously, when IoT-collected patient data is paired with AI (see next section), healthcare providers can use predictive analytics to spot patterns that might indicate a health risk. For example, an AI system might analyze data from hundreds of patients’ IoT heart monitors to learn the early warning signs of a stroke or heart attack, enabling doctors to take preventive action. Such predictive diagnostics, powered by IoT data and AI, help shift healthcare from reactive to proactive. Early studies suggest that using connected devices for real-time monitoring and analysis can reduce hospital readmission rates and catch warning signs earlier. IoT is fundamentally changing healthcare by providing continuous, real-time data and automating certain care processes. It improves the quality of care and patient safety – doctors can make decisions with up-to-the-minute information, and patients receive attention faster when something is wrong. Additionally, it increases efficiency: for example, smart inventory systems in hospitals track supplies and equipment automatically, and connected wheelchairs or beds can be located via the hospital’s network. While IoT in healthcare brings challenges (such as data privacy and security concerns), its benefits in patient monitoring, chronic disease management, and operational efficiency are driving rapid adoption of these technologies in the medical field.

IoT in Agriculture

Agriculture might not be the first thing that comes to mind for high-tech innovation, but IoT is revolutionizing farming. With the global demand for food rising, farmers are turning to IoT (often called “smart farming” or “precision agriculture”) to increase yields, use resources more efficiently, and reduce waste. By putting sensors in fields and barns and using satellite connectivity or long-range radio networks, even remote farms can benefit from IoT data. Key applications of IoT in agriculture include:

Precision Farming and Crop Monitoring: IoT sensors can be deployed throughout crop fields to monitor conditions like soil moisture, soil nutrient levels, temperature, humidity, and light. This granular data allows farmers to understand exactly what different parts of a field need, rather than treating an entire field uniformly. For instance, moisture sensors might show that one section of a field is dry while another has ample water. Farmers (or automated irrigation systems) can then water only where needed, conserving water. Drones or stationary sensors can monitor crop health indicators (like leaf color or pest presence) and send alerts for any issues. By collecting and analyzing all this data, IoT-driven precision farming helps optimize planting, watering, and fertilization The result is often higher crop yields with less waste of resources (agritechtomorrow.com). In fact, IoT-driven analysis provides a multifaceted view of farming operations – covering crop conditions, weather data, and even equipment performance – to support data-driven decisions on the farm.
Automated Irrigation: Water is a precious resource in agriculture, and IoT makes irrigation much smarter. Instead of watering on a fixed schedule, farms use soil moisture sensors and weather data to determine when and how much to irrigate. IoT systems can automatically turn valves and control irrigation equipment to water plants at the optimal time. This prevents both under-watering and over-watering. For example, if the soil moisture sensors detect that the ground is dry and weather forecasts (fed through the IoT system) indicate no rain, the system can trigger irrigation in that specific zone. Conversely, if rain has just happened, the system skips a cycle. Such intelligent water management ensures crops get the right amount of water at the right time, improving growth while saving huge amounts of water (com). Farms that have adopted IoT-based irrigation have reported substantive water savings and better crop consistency, demonstrating the environmental and economic benefits of this technology.
Livestock Tracking and Health Monitoring: IoT isn’t just for crops – it’s also transforming animal husbandry. Farmers are using IoT collars, tags, and implants to continuously monitor livestock location, activity, and vital signs. For example, a rancher can place GPS-enabled tags on cattle to track their grazing patterns and find them easily across large pastures. Sensors can also monitor an animal’s body temperature, heart rate, or behavior, which helps in early detection of illness or distress. If a cow’s activity drops or its temperature rises (potential signs of sickness), the system can alert the farmer via phone. IoT sensors in barns monitor conditions like temperature, humidity, and air quality to ensure healthy environments for poultry or pigs (com). By collecting all this data, farmers gain insights into herd health and can improve animal welfare and productivity. IoT-driven livestock management thus leads to healthier animals and can increase yields like milk production, while also reducing labor (since much of the monitoring is automated). As an example, IoT-enabled livestock systems allow precise feeding – silo sensors and smart feeders ensure each animal gets the right amount of food, and water trough sensors verify water supply, with any anomalies reported instantly (intuz.com).

Overall, IoT in agriculture helps farmers make better, data-driven decisions. It minimizes guesswork by providing real-time visibility into farm conditions. According to industry reports, by using IoT, farming businesses can significantly enhance productivity and sustainability – global IoT in agriculture was a $11.4 billion market in 2022 and is projected to keep growing as farms seek higher efficiency (agritechtomorrow.com). From soil to satellite, IoT technology is enabling more food to be produced with fewer resources, which is crucial for future food security.

IoT for Businesses and Industrial Automation

Beyond specific sectors like health or farming, IoT is broadly transforming industries and businesses of all kinds. The ability to monitor equipment, assets, and environments in real time – and to automate processes based on data – is driving major gains in efficiency and productivity. This industrial side of IoT is often called the Industrial Internet of Things (IIoT). Businesses are leveraging IoT for everything from factory automation to supply chain optimization. Here are some ways IoT is used at the industry level:

Manufacturing and Industry 4.0: Factories are increasingly filled with IoT-enabled machines and tools. Sensors attached to production equipment track metrics like temperature, vibration, speed, or output quality continuously. This allows for real-time monitoring of the production line and equipment health. If a machine shows signs of a problem (e.g. abnormal vibrations), managers can intervene or schedule maintenance before a breakdown halts production. IoT data also helps automate manufacturing processes – robots and machines can adjust their operations on the fly coordinated by central systems. These improvements translate to huge efficiency gains. For example, Harley-Davidson implemented IoT sensors and automation in one of its motorcycle plants, and the results were dramatic. The production cycle for a customized bike dropped from 21 days to just 6 hours, and operating costs fell significantly, yielding about $200 million in savings (tsl.io). This stunning improvement was achieved by using IoT to streamline workflows, reduce downtime, and optimize supply of parts. Many manufacturers are pursuing similar “smart factory” initiatives. The Industry 4.0 movement refers to this next industrial revolution, where IoT, robotics, and data analytics combine to drive automation and better decision-making on the factory floor.
Energy and Utilities: Companies in oil & gas, electricity, and water management use IoT to monitor and maintain critical infrastructure. In the oil industry, for instance, IoT sensors on remote oil wells and pipelines continuously measure pressure, flow rates, and equipment status. Instead of dispatching technicians for routine checks, companies like Royal Dutch Shell have used remote IoT monitoring to keep an eye on operations from afar. This reduces the need for on-site visits (which can be dangerous and costly in remote areas) and catches anomalies early. Shell’s deployment of off-site IoT monitoring in difficult-to-access oil fields led to significant cost savings by cutting down manual maintenance trips and minimizing downtime from unexpected issues (tsl.io). In the electric utility sector, smart grids employ IoT devices across the network – smart meters at homes, sensors on transformers and power lines – to detect outages or inefficiencies and balance load distribution. This makes the power supply more reliable and efficient. Water utilities use IoT sensors to detect leaks in pipelines and monitor water quality in real time, helping to quickly address issues and conserve water. Across energy sectors, IoT provides better visibility into infrastructure and helps prevent failures, thus improving service reliability and safety.
Retail and Supply Chain: Businesses that deal with physical goods are using IoT to track inventory and shipments with greater accuracy. In retail stores, smart shelves equipped with weight sensors or RFID readers can tell when stock is running low or if items are misplaced. This automates inventory management and can even alert staff to restock before shelves go empty. For example, the grocery chain Giant Eagle piloted “smart shelves” that monitor product inventory in real time and can even send product information to shoppers’ smartphones when they are nearby (tsl.io). The system helps avoid stockouts (which can cost retailers lost sales) and improves the shopping experience by guiding customers to products. In warehouses and logistics, IoT tracking devices on packages or pallets report their location and condition throughout the shipping process. This means a company can have a live map of all shipments and get alerts if, say, a container experiences a temperature spike (important for cold-chain goods like pharmaceuticals or food) or if a delivery is delayed. Fleet management is another area – trucking companies use IoT to monitor truck locations, driver behavior, and vehicle health. This data helps optimize delivery routes and schedules, saving fuel and ensuring timely deliveries. Overall, IoT in retail and supply chain leads to leaner operations: warehouses that restock efficiently, fewer lost items, and more responsive logistics. These examples barely scratch the surface. Virtually every industry is finding value in IoT. Construction firms deploy sensors on job sites and equipment to improve safety and project management. The automotive industry uses IoT both inside factories and in the vehicles themselves (connected cars that report maintenance needs or receive software updates). Agriculture companies we discussed earlier use industrial IoT for food processing and distribution. According to research, organizations adopt IIoT solutions to increase efficiency, reduce costs, and gain data-driven insights across their operations(nix-united.com). Another big advantage is improved safety: IoT can take over monitoring of hazardous conditions (like gas leaks or machine overheating), reducing the risk to human workers and providing early warnings. Traditional manual processes that were time-consuming and error-prone can be automated with IoT – for example, counting inventory or logging machine readings can happen automatically and accurately. This frees up employees to focus on higher-level tasks and cuts down on human error.

In short, businesses are leveraging IoT to create smarter, more automated industries. The data collected by IoT devices becomes a strategic asset for companies – they can analyze it to find inefficiencies, predict problems, and make better decisions. The result is often a boost in productivity and a competitive edge in the market for those who use IoT effectively.

The Intersection of IoT and AI: Making IoT Smarter

IoT devices generate massive amounts of data. On its own, this data is valuable, but when combined with Artificial Intelligence (AI) and machine learning, the true power of IoT is unleashed. AI can rapidly analyze IoT data, detect complex patterns, and make intelligent decisions, effectively giving “brains” to the network of connected “things.” This synergy between IoT and AI is sometimes called AIoT. Let’s look at a few key ways AI enhances IoT capabilities:

AI-Driven Predictive Maintenance

One of the most impactful combinations of IoT and AI is in predictive maintenance for machines and infrastructure. As IoT sensors collect data on equipment performance (temperature, vibration, noise, etc.), AI algorithms can continuously analyze this data to detect signs of wear or failure before a breakdown happens. Traditional maintenance might be reactive (fix things after they fail) or scheduled at set intervals. Predictive maintenance, by contrast, uses data to predict when a machine will need service, so maintenance can be performed just in time to prevent unplanned downtime.

For example, consider a factory with IoT sensors on its motors and conveyor systems. AI software learns the normal vibration patterns of each motor. If the pattern starts to deviate in a way that in the past signaled an impending bearing failure, the system can flag it and generate a maintenance ticket days or weeks in advance of a potential breakdown. This saves the company from a sudden production halt. Studies show that moving from reactive to AI-powered predictive maintenance can reduce overall maintenance costs significantly (estimates range from an 18–25% reduction) and cut unexpected equipment downtime by up to 50% (iiot-world.com). In real terms, that means fewer expensive repairs and less time where machines sit idle. Industries like manufacturing, aviation, and utilities are embracing this approach. For instance, jet engine makers use IoT sensors on engines and AI analysis to predict when parts will need replacing, rather than fixing them after a failure. This data-driven foresight is only possible through AI’s pattern recognition abilities applied to the constant stream of IoT data. In short, IoT provides the raw data (the “ears and eyes” on the equipment), and AI is the “brain” that figures out what that data means for future performance. The combination leads to safer, more reliable operations and big cost savings from avoiding major failures (iiot-world.com).

Intelligent Automation in IoT Systems

AI doesn’t just predict problems – it can also enable IoT systems to act autonomously and optimize processes in real time. This is often referred to as intelligent automation or closed-loop automation. In an AI-enhanced IoT network, decisions that used to require human input can be made by AI algorithms almost instantaneously, based on sensor data. This makes the whole system more responsive and efficient.

Consider a smart home scenario: IoT devices like thermostats, lights, and appliances are all connected, but adding AI allows them to adapt to your lifestyle automatically. An AI system can learn your daily routine and preferences by analyzing data from motion sensors, temperature sensors, smart plugs, and more. Over time, it might notice that you usually return home at 6 pm and prefer the living room at 22°C. Using that insight, the AI could set the thermostat to warm up the house shortly before you arrive and turn on lights in the hallway. It may also learn your entertainment habits – for example, dimming the lights and turning on the TV for your favorite show on Tuesday nights. In essence, the home begins to “learn” and anticipate needs, rather than waiting for manual commands. One description put it well: AI systems in a smart home can observe your interactions and mood, then adjust lighting, temperature, music, and more to suit your preferences – for instance, watering the garden when soil sensors detect dryness or starting the vacuum robot every Saturday at 1 PM automatically (pwrteams.com). This kind of seamless automation makes technology truly fade into the background of daily life, providing comfort and efficiency effortlessly.

On the industrial side, intelligent automation means AI can control IoT-connected machinery and processes for optimal performance. In a smart factory, an AI might dynamically adjust the speed of an assembly line based on sensor feedback about product quality, or reroute power in an electrical grid by analyzing usage patterns in real time. AI algorithms can juggle many more inputs and constraints than a human operator can, finding the best configuration to, say, minimize energy consumption while maintaining output. Another emerging area is autonomous vehicles and drones – essentially IoT devices that move. Self-driving cars gather input from many sensors (cameras, radar, LiDAR) and use AI to make driving decisions. They can even communicate with each other (vehicle-to-vehicle IoT communication) to, for example, form an optimal traffic flow. All these are examples where IoT provides the interconnected hardware, and AI provides the decision-making software that makes the system intelligent and automated.

Data Analytics and Pattern Recognition for Better Decision-Making

IoT leads to big data. A city with thousands of sensors or a company with IoT devices on every asset will end up with a flood of data points. Simply connecting devices doesn’t automatically create insight – this is where data analytics and AI-based pattern recognition come in. AI tools (particularly machine learning) are exceptionally good at sifting through large datasets, finding correlations and trends, and even making predictions. By applying these tools to IoT data, organizations can unlock valuable knowledge and guide better decision-making.

For example, consider environmental data from IoT sensors spread across a region: they measure rainfall, river levels, soil moisture, and more. An AI system can analyze all these streams together to detect subtle patterns that humans might miss – perhaps identifying that certain sensor readings, when combined, are an early indicator of a flood. This could enable authorities to issue warnings or take action before a disaster strikes. Indeed, pairing AI with IoT sensors allows us to identify patterns and predict outcomes such as natural disasters or pollution events, which helps in taking preventive measures (tektelic.com). Another scenario is using AI on city IoT data (traffic, weather, events) to predict where congestion will occur and proactively manage it, or analyzing building sensor data to recognize when a building is occupied and adjust lighting/heating accordingly without manual input.

In business, analytics on IoT data can illuminate inefficiencies – for instance, a delivery company might find through AI analysis that certain delivery routes consistently cause delays due to traffic at a specific time, and then change routes or timing accordingly. Retailers might analyze foot traffic data from IoT-enabled cameras and combine it with sales data to optimize store layouts or staffing. Patterns that lead to energy waste can be spotted by analyzing months of IoT meter readings, suggesting new energy-saving policies. And as mentioned, patterns in healthcare data can hint at medical conditions or treatment outcomes, improving clinical decision-making.

In summary, AI turns IoT data into actionable intelligence. It can recognize complex patterns across numerous sensors and data points, something that would overwhelm manual analysis. By doing so, AI helps humans make better decisions – often giving recommendations or automating the decision entirely. The marriage of IoT and AI thus results in systems that are not only connected and automated, but also continually learning and improving their operations based on data.

Conclusion

The Internet of Things is all about connectivity – bringing the physical objects around us into the digital fold so they can work in unison to improve our lives and businesses. We started with a simple idea: everyday “things” like thermostats, cars, or farm soil can communicate useful information. From that idea has grown a vast ecosystem of applications: smart cities that adapt to citizens’ needs, healthcare systems that watch over patients 24/7, farms that produce more food with less waste, and industries that run more safely and efficiently.

For the layperson, IoT means more convenience – devices that anticipate what you need and routines that are automated for you. For professionals and businesses, IoT provides unprecedented visibility into operations and opens the door to automation and optimization at scale. When we add Artificial Intelligence into the mix, IoT systems become even more powerful: they not only collect data, but also understand and react to it in intelligent ways, from predicting equipment failures before they happen to learning our personal preferences at home.

It’s an exciting time where the physical world and digital intelligence are merging. While there are challenges (like ensuring security and privacy, and managing all this data), the IoT revolution is clearly underway. In making this complex technology accessible and useful, we stand to create smarter cities, healthier lives, and more productive industries. The Internet of Things is ultimately about unlocking potential – the potential of objects to serve us better, and the potential of data to inform better decisions. And as IoT continues to expand with the help of AI, its impact will only grow, in ways we are just beginning to imagine.