Traffic Count and Statistics.

Cute little garbage truck captured in the fog, one of 8 passings of garbage trucks that day.

Our Neighborhood Security Surveillance Camera records a lot of traffic but how many passers-by do we really record:

I decided to pick 1 day and do a detailed count, this happened to coincide with a theft from a car that night which allowed me to combine the work.

in 24 hours, the motion detector recorded 491 sequences of events on 1 camera covering an entrance to our neighborhood.
The count below records objects passing the camera, not unique cars passing, e.g. the same car coming and going will be counted as 2.
1 Bicycle
2 Motorcycles
3 Utility trucks
7 Delivery vans
8 Contractors
8 Garbage Trucks (garbage day, but I was surprised it was that many)
14 Pedestrians (with 6 dogs)
238 Passenger Cars
1 Suspicious Person (Photo and license plate submitted to Oakland Police)

Total of 281 relevant events.

The rest was false alarms on the motion sensor, e.g.  moving shadows from clouds, fog, changing light. (it was a foggy day)  e.g.

License plate readability
Of the 266 vehicles, 7 did not have a License plate. (2.6%)
Out of 259 vehicles with License plates 255 could be read by human(*) (98.5%)

(8) The human is me, method included selecting the best photo for each vehicle and using different zoom levels, sometimes part of the license plate could be read in one photo and the rest of the plate in another photo. No image manipulation was needed (such as Photoshop)

Room for Improvement
A motion detector False Positive rate of 42% – is too much.

While I would rather have too many recordings than missing 1 critical, here is room for improvements.
I am currently adjusting the sensitivity levels in order to try reduce the number of false recordings.


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