The Internet of Things (IoT) is a multifaceted industry that bridges the gap between physical objects and information technology. When we digitize the physical world with the help of sensors, mapping and systems to parse the data we collect on these objects, it helps businesses monitor products, objects or services and manage response machines, all from convenient and remote locations.
Remote management of oil wells is a great example of the IoT stack at work. Companies can now monitor and manage their machines using vibration sensors to detect potential well leaks, in turn preventing time consuming and costly repairs and reducing the labor costs to maintain the infrastructure.
Companies gather the data and digitize it using IoT endpoints or sensors, which connect to the machines and deliver vital operations and environmental information to a software platform. When this data is parsed by and integrated into business applications, it becomes invaluable information to business users, customers and partners.
Endpoints can include machines like, sensors, actuators, gateways, compute devices and communications devices. These components have standardized and evolved over the years to be cheaper, faster, more connected and easier to deploy, fueling the appetite to transform physical information into data.
Today, more machines are designed or retrofitted to communicate openly with secured sensors. Sensors are cheaper and require little or no power to operate for years, which makes it easier to deploy the sensors in remote locations. Gateways are made to withstand weather and elements, and low energy communications devices like low power wide area network (LPWA) make it possible for thousands of sensors to connect to gateways.
Smaller and cheaper computing devices manage the machines and analyze the data for immediate actions. These devices are even now programmed to only transmit valuable data to the IoT software platform, reducing the amount of unusable or non-valuable data collected.
Thanks to the ubiquitous availability of IoT software platforms like ThingWorks, Telit, AWS, and Azure have emerged. These typically run in the cloud and provide connectivity to endpoints and manage data on the edge and in the cloud. These platforms rely on machine learning to profile “normal” operating procedures and detect anomalies. They also manage the endpoints devices and communications, and provide a security layer to protect both the devices and the data.
The evolution of endpoints and the emergence of software platforms make it possible to transform the physical world into digital information. Digital transformation became possible with the evolution of the IoT endpoints and the emergence of the IoT software platforms, but the true business transformation is occurring with each new class of IoT applications and IoT enterprise integrations. New IoT applications use the data to make real time decisions in supply chain, manufacturing, transportation, and collaborations with customers and partners. Data is now integrated with existing business applications to provide deeper insights, automated actions, and enterprise collaborations.
Later on, I will explore the IoT stack layers in greater detail.