The Internet of Things (IoT) is big and getting bigger by the day, as organizations deploy Internet-connected devices that can collect and send data, receive instructions and perform tasks. These devices run the gamut from smart cars to building automation systems to medical equipment. Manufacturers, retailers, healthcare providers, government agencies and organizations in many other industry sectors stand to benefit from the IoT.
Imagine a “lights out” factory in which sensors and cloud-based software manage the robotics systems without human intervention. Or vehicles that detect when they need maintenance and automatically schedule service. The IoT allows oil and gas companies to monitor and manage far-flung infrastructure, and cities to reduce costs and increase safety through smart lighting and traffic controls.
But the IoT isn’t just about remotely operating equipment. In fact, the real value of the IoT lies in the data the devices collect. Organizations are hoping to capitalize on this data to gain new insights into their operations, their customers and their competitors. These insights can help them improve their business processes, launch new products and develop new business models.
The problem is that you can’t extract value from IoT data without sophisticated analytics tools. Typically, these tools would be implemented in a centralized data center or the cloud, and all the data would have to be transported there for processing. Giving the sheer volume of information generated by the IoT, moving it across the network creates bottlenecks and delays that make real-time analysis difficult.
A better approach is to process the data closer to the devices themselves — a concept known as “fog computing.” Fog computing refers to a distributed infrastructure that brings data analytics functionality to the network edge. It provides mobile devices, sensors and other smart technology with local compute and storage resources, so data can be processed before it is sent to the data center. This makes it possible to convert data into actionable insights more quickly. It also makes better use of available resources. Only intelligent information, not an endless stream of raw data, is pushed to the cloud for storage and more advanced analytics.
As a result, fog computing delivers a number of business benefits. Thanks to a geographically distributed infrastructure that is integrated with cloud services, fog computing delivers on the promise of real-time data analytics with minimal latency. Users can make faster, more-informed decisions based upon the most recent data. At the same time, organizations can make more efficient use of available bandwidth because only high-value data is sent to the cloud. This also makes it possible to enhance performance, improve security and overcome privacy issues.
As the IoT expands, the number of mobile devices increases, adoption of cloud services grows, and data centers become more distributed, organizations need to figure out how to efficiently leverage all of the data that’s being generated. By bringing processing power to the network edge, closer to IoT devices, fog computing makes IoT data easier to access, manage and analyze while improving performance and conserving bandwidth.