One must be able to walk into a room, including those in data centers, and not only access information about every facet of it, but also importantly, have it automatically solve all of its problems on its own.\nSite 1001, which specializes in artificial intelligence-run facilities management systems,\u00a0says the problem\u00a0should be achieved through neural networks that copy how humans and animals think.\nThe company, a spin-off of JE Dunn Construction Co., demonstrated its all-listening,\u00a0predictive building maintenance at CES 2018 last week. It says its big data, AI-driven system will ultimately produce smarter and healthier buildings.\n\nOne example demonstrated in mock-up form at the conference was an apparatus that could automatically determine when bacteria conditions in water systems were ripe for producing Legionnaires' Disease. The IoT-driven infrastructure autonomously flushes the building's plumbing system with pathogen-killing hot water, reporting back to the facilities manager that the relatively simple-to-perform \u2014 but hard to know when to do \u2014 job had been accomplished. It uses heat data from sensors to figure out when pathogens might form.\nIn traditional systems, water samples would have to be taken manually. And if they weren\u2019t, then reports of illness in building occupants would be the impetus for corrective measures.\nBuildings as living structures\n\u201cWhen we look at buildings as living structures, we can understand how various systems are connected and operate together,\u201d says Dr. Filip Ponulak, principal data scientist at Site 1001, in a press release.\nPonulak says all buildings should now be listening for issues. He says it\u2019s an innovative way of managing new buildings. Site 1001 believes its system would also work in older buildings.\nChief Innovation Officer Eric Hall told me one could draw an analogy with an aging car, except that unlike cars, buildings don\u2019t have odometers to help identify failing parts.\nIn other words, by collecting data on failings, for example, predicting upkeep becomes possible \u2014 you know when things are likely to fail and can pre-empt them, like a flexible car service schedule. That lets facilities management \u201cmove to an entirely conditional and proactive maintenance schedule,\u201d says Hall on the company\u2019s website.\nData centers fit into this platform, too, the company says. Indeed, I\u2019ve written before about folks who think AI will ultimately self-manage the data center:\nRobots are going to be running the show, I wrote in a recent blog post. In that case, robots are making physical cabling connections. But a facet of that article was a company that said it would be cloning employees\u2019 intimate knowledge of their workspace soon.\nIn addition, HPE says predictive troubleshooting from AI will be used to unravel bottlenecks between applications and data within the data center.\n\u201cA building can be compared easily to our own body and working systems,\u201d Ponulak told Builtworlds in an interview this month. He says HVAC is like the respiratory system, the electrics are like the \u201cbody\u2019s circulatory system, which supplies energy to the body,\u201d and the musculoskeletal is the building structure. Communication with the original architectural plans, live sensor data, and AI create the brain.\nIt\u2019s the coordination of IoT that gives \u201cthe building the ability to heal itself,\u201d Site 1001 says.