Issue link: https://www.e-digitaleditions.com/i/1081695
30 I ICT TODAY FIGURE 1: Oil and gas companies are using edge computing to predict and alert on malfunctions and failures before they happen, saving millions in lost production yearly. use sensors ensuring that if a pump is about to have enough of a problem that it shuts down the system, and it warns someone first (Figure 1). Pumps that are not running cost oil companies on average $40 million per year with some estimates pegged at $80 million. Then there is the question of the data. It used to be common to install these little sensors, which are basically faucets that spew out terabytes of data every single day, but a lot of important information just gets thrown away. Now organizations are beginning to realize the tremendous unlocked value of this data through machine learning. Machine learning, once rooted in science fiction and thought to always be just out of grasp, has started doing things that people once thought were impossible for computers to do. The intelligent building is turning into an artificial intelligence building. Edge compute is the practice of running servers closer to where they are needed and closer to where the gushers of data are produced. These sources of data are not in the public cloud or some centralized data center. They are attached to light fixtures throughout a corporate office. They are attached to the pumps on massive oil rigs off the coast of Africa. They are sitting next to a jet engine on a 747. They are even in a local supermarket ensuring applications as mundane as a refrigerator not breaking down, but if it does someone is notified before the produce goes bad and must be thrown out. Grocery stores lose millions of dollars a year on spoilage; some chains estimate it to be 20-30 percent of sales! Companies are not just installing sensors on these devices because it is technically interesting. There is real business value that is being created and captured. Oil companies