This is less a specific question, and more... "what is this called" and "where can I read more about it"?
Several times in my career, I've had to work with datasets with "discrete events". Lets say customers passing an infrared sensor at a store front.
Normally, signal processing would be concerned with a continuous time signal, like the voltage on the IR receiver... but my question pertains to the event of someone walking through the door. The "signal" (in this case) is more a list of times when someone walked through the gate.
# Unix Timestamps entry_times = [1490648032, 1490648102, 1490648591, ..., ...]
The "crude" way to treat this signal is to bin the entry times to hours of the day and interpolate that dataset for a rough idea of customers vs time. However, I think that there's more to this problem.
- Entry and exit are the same type of signal, but could DSP help differentiate? (I think not, but I don't know!)
- Perhaps we want to count a mother and her two children as a single "customer". Assuming we get three events in a five second window, can we somehow group that together?
If we count the number of entries and exit per hour, this gets us a rough graph of customer throughput, and we can interpolate that to get more resolution... but how could we create that on the fly?
What is the name of this type of signal? Are there any signal processing algorithms or techniques that would help answer my questions?