Some of the estimates going around are that 1 to 2 million people attended today's championship parade. But 2 million seems like a lot, even though today was frenetic (see above photo, again). I mean, that's 1/3 of the population of the Greater Toronto Area.

The fact that some of the "official" estimates also have a 1 million person spread tells me that, as of right now, we actually have no idea how many people were at today's parade.

So that got me thinking: How do people count crowds? And are we using drones to do it, yet? Subway and rail ridership for the day -- which surely spiked -- will give us some indication. But definitely not the full picture.

It turns out that the typical approach to counting crowds is known as Jacobs' Method. It was invented in the 1960s by a professor at UC, Berkeley, named Herbert Jacobs. He came up with the method while trying to count the number of students protesting the Vietnam War.

The concept is simple: It's area x density. And permutations of his method usually use this same principle. What you do is take the area filled with people, break it up into a smaller grid, and then come up with a population density estimate for each square.

He had some rules of thumb for that. A light crowd was about 1 person per 10 square feet. And a dense crowd (such as a mosh pit or an NBA championship parade in Toronto) was about 1 person per 2.5 square feet.

Using this method and aerial photos of today's parade, I would imagine that we could eventually get to a more precise estimate than 1 to 2 million people. But surely somebody has figured out how to program a drone (or other UAV) and do this even more accurately.

Crowd data is valuable information, particularly for political rallies and protests (I would imagine). If you know of a company doing this, please leave it in the comment section below. And if it doesn't yet exist, well then, now you have a new business idea.

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