During this year’s CES conference, Site 1001, a company which specializes in artificial intelligence-run facilities management systems and previously spun off of JE Dunn Construction Co. showcased its artificial intelligence driven predictive maintenance system. Essentially, with any artificial intelligence driven facility, not only should the program be able to access information about every aspect of the building, but also be able to have the program automatically solve any problem which may arise on its own. The way to do this, according to Site 1001, is through neural networks that copy how sentient creatures think. As such, one prominent example of this kind of predictive thinking in action was with Legionnaires’ disease. This example, shown at the conference, highlighted a devise that could not only automatically determine when conditions in water systems were conducive for legionella bacteria to form, but could also flush the building’s plumbing system with hot water to kill the bacteria. This IoT-driven infrastructure then would not only detect and clear legionella bacteria and others, but could also report back to the facilities manager everything that had just been done in order to keep individuals readily informed. This kind of system would clearly be far better than traditional systems, whereby water samples would be taken manually and if not done, then reports of illnesses would be the only catalyst for responding. Yet it also serves to highlight how artificial intelligence can serve practical functions which would otherwise involve far more intensive responses to address, particularly with something like legionella bacteria and Legionnaires’ disease. Jules Zacher is an attorney in Philadelphia who has tried Legionnaires’ disease cases across the U.S. Please visit LegionnaireLawyer.com again for updates.
Artificial Intelligence and Detecting Legionnaires’ Disease was last modified: January 22nd, 2018 by