Using artificial intelligence and "big data", New York City has increased locating illegal building alterations by 500%. It looks for increased utility and sanitation demand. Is fire prevention next? Or incident prediction?
Truck tire manufacturers are rolling out an artificial intelligence enabled tire. Designed for delivery vehicles with high start/stop use (like fire equipment?), sensors provide data such as temperature, pressure, tire wear, acceleration, and vibration. This information is sent to machine learning algorithms. Testing has shown up to 90% of problems can be predicted. Further, stopping distances can be reduced, and more tires can be retreaded, decreasing air pollution and operating costs.
In the past, tire maintenance meant checking the tire pressure and putting a copper penny between the treads. When you could see the top of Abe's head it was time to replace the tire.
Herb Simon (one of the fathers of artificial intelligence) won the Turing Award in 1975 and the Nobel Prize in Economics in 1978 for research done years earlier. The first computer program for machine learning algorithms (ALGOL) was published in 1960 (I took the ALGOL class in 1967. Now, I can turn on my laptop). These achievements, plus better sensors, computers, and megadata are finally being put to use by tire manufacturers (including Michelin) for commercial purposes. Twenty five years ago is now the stone age.
Incidentally, Herb Simon published the book " Fire Losses and Fire Risks" in 1943. It was used by the Rand Fire Project in New York City in 1968.