Caterpillar's marine business has integrated a suite of machine learning software from OSIsoft that should help its clients save millions in fuel costs while improving the safety and reliability of equipment on the high seas. OSIsoft announced today that Caterpillar is OEMing some of its technology, including the Connected Services and PI Systems offerings, as part of Cat Asset Intelligence, which is a suite of machine learning-based services that Caterpillar offers to clients in various industries. The complexity and scale of today's ships make them good candidates for optimization through big data. According to Matt Miller, OSIsoft's transportation industry principal, the two most immediate areas for savings are energy consumption and maintenance costs. "Ships use tremendous amounts of fuel," Miller tells Datanami.

Organizations have been tracking and reporting on their assets – including people, processes, and physical things such as computers – for years. Companies use the information they get to help lower operating costs, reduce risk and outages, improve regulatory compliance and take control of capital expenditure planning. But, like other fields, the rapid advance of technology is disrupting enterprise asset intelligence. Artificial intelligence technology like machine learning has been particularly influential. In this post, we'll review what asset intelligence is today and how machine learning will impact it going forward.