CAN A.I. detect fires faster than humans. Yes, very much so. A software is being trained to look for smoke, and the early results are very, very promising.

Let's take the case of California : For years, firefighters in California have relied on a vast network of more than 1,000 mountaintop cameras to detect wildfires. Operators have stared into computer screens around the clock, looking for wisps of smoke.

This summer, with wildfire season well underway, California's main firefighting agency is trying a new approach : training an artificial intelligence to do the work.

THE IDEA is to harness one of the state's great strengths - expertise in A.I.  - and deploy it to prevent small fires from becoming the kinds of conflagrations that have killed scores of residents and destroyed thousands of homes in California over the past decade.

Officials involved in the pilot program say they are happy with early results. Around 40 percent of the time, the artificial intelligence software was able to alert firefighters to the presence of smoke before dispatch center's received emergency calls.

'' It has absolutely improved response time,'' said Philip SeLegue, the staff chief of intelligence for the California Department of Forestry and Fire Protection, the state's main firefighting agency, better known as Cal Fire.

In about two dozen cases, Mr. SelLegue said, the A.I. identified fires which the agency never received emergency calls. The fires were extinguished when they were still small and manageable.

The A.I. pilot program, which began in late June and covered six of Cal Fire's command centers, will start rolling out to all  21 command centers in September.

But the program's apparent success comes with caveats. The system can detect only fires visible to the cameras.

And at this stage, humans are still needed to make sure  the A.I. program is properly identifying smoke. 

Engineers for the company that created the software, DigitalPath, based in Chico, Calif, are monitoring the system day and night and manually vetting every incident that the A.I. identifies as fire.

EVEN what seems like a straightforward task - teaching a computer to recognize smoke - has been a painstaking process that is far from complete, engineers say. There are many false positives.

'' You wouldn't believe how many things like smoke,'' said Ethan Higgins, chief architect of the software.

Fog. A little haze in front of a mountain. Dust kicked up from a farmer's tractor. Steam rising from geothermal plants. Camera flare from a rising sun. All of these have tricked the computer into thinking there was fire. 

ENGINEERS and firefighters are spending their training the A.I. program to understand what is - and what is not - fire.

I don't think this robot is ever going to take my job,'' said Andrew Emerick, the duty chief for Cal Fire's [ California ] northern region. Mr. Emerick, an experimental operator of cameras, gives the example of the deliberately set fires in agricultural areas : vintners burning branches after an autumn pruning or rice farmers burning stalks after harvest.

Mr. Emerick knows the area and understands the context - these are not fires that he needs to dispatch engines and aircraft to snuff out. But he is not sure the A.I.program will ever fully understand those nuances.

'' What we do is going to require some sort of human intervention, someone with experience to say, '' Hey, do something about this,'' or ' No, don't do something about it,'' he said.

The Publishing on A.I. Solutions and  Future continues.The World Students Society thanks author Thomas Fuller.


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