The above image is a profile of scanner module hit density over a week. The x-axis is time, and the y-axis is hit density (hits per time period). The time is in UTC. The semi-periodic waveforms you see are an EKG-like graph of our city’s heartbeat! (Right click->View Image to see a larger version)
The bottom graph measures hits on KCMARRS – a network that handles much of our law enforcement, emergency services, and government communications. The top graph measures scanner hits on local pager networks. Pagers are used for industrial control systems, and most of all doctors.
The periodicity of both graphs is striking. KCMARRS peaks around 1600-1800 UTC (2200-0000 local). It troughs around 1000 UTC. The pagers tend to lag government communications by a small amount.
What amount of the fluctuation is due to time-dependent changes in RF propagation? The graph below shows one of the pagers frequencies over the time period in question. The x-axis is time, the y-axis is power. The gap and slight shifting of signal level after the gap are due to a service interruption.
At this frequency, and presumably the others (which are close by in frequency), the power stays relatively constant over time. So we can safely conclude that the change in hits is due to activity on the frequency.
There are likely larger wave-form periodicities that can be extracted from multi-weekly and seasonal-scale data. Are police and doctors busier on the weekends? Are summers much busier than winters?
An interesting application would be to hook the data up to an alarm – so that any sudden rise in the government net alerts an analyst. Terrorist attacks and large disasters will likely trigger a sharp rise on the graphs.