Bringing Artificial Intelligence To Parking Guidance

By Chris Scheppmann

When we visualize artificial intelligence (AI), we often think of robots learning how to think, so they can perform human tasks. And of course, those of us who are science fiction fans probably envision apocalyptic acts committed by hordes of out-of-control robots. Thankfully, the reality is much safer and more useful than robots learning how to kick a soccer ball. This is particularly true when it comes to parking.

One of the most important recent breakthroughs in parking guidance technology is Machine Learning. Through Machine Learning, parking guidance has become highly accurate and useful, both for helping manage parking inventory and when it comes to providing parking operations with business intelligence to make better informed decisions. But, to understand the role that Machine Learning is playing in parking guidance, it is first necessary to understanding what Machine Learning is.

What is Machine Learning?

Machine Learning is a type of AI. Equipment paired with Machine Learning is able to modify itself when exposed to more data. It is dynamic and does not require human programmers or designers to manually make changes and the Machine Learning models can continually  improve its understanding of an environment where it is being used. 

As Arthur Samuel, a pioneer of the field stated in 1959, Machine Learning “gives computers the ability to learn without being explicitly programmed.” As an example, Machine Learning is like a child who is born without having any knowledge and adjusts (knowledge improves) its understanding of the world in response to experience (receives new data). As that baby continues to be exposed to similar and new experiences, its ability to make connections and decisions improves. Over time, a child can differentiate between a spotted dog and a cow or a brown-haired dog and a…

Continue reading →