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Dumb Sensors (aka Inductive Loops) vs. Smart Swarm Sensors

We often think of students counting traffic as (until very recently) the old-school way of doing traffic counts (aka Students-as-a-Sensor (SaaS)). We think of Inductive Loops as the modern traffic counting sensor.

But when was the first real traffic counting sensor? The 1980s? 1970s? Try 1937! In an early project...traffic recorders….operated off a strip laid across the street, and used a six volt battery. Each hour it printed off a paper strip with the total for that hour…” (source)

In fact, current Inductive Loops are a slightly updated version of the same 1935 sensor. They may lie beneath the asphalt, but they are fundamentally the same sensor technology (minus the paper printer!).

Inductive Loops are:

  • Expensive and disruptive to deploy
  • Are prone to hardware failure
  • When they fail are expensive to replace and redeploy
  • Are not updatable
  • Cannot handle slow or stationary traffic
  • Are Inaccurate

“Dumb sensors, always remain dumb” (Wieland Alge)

People are often skeptical that a video-based sensor, using standard IP cameras and Dynamic Perception Technology, can be as accurate as ‘tried-and-tested’ Inductive Loops. This is in fact not the case, as two recent independent tests (by a globally active corporation with more than 50 years of experience in traffic management) have shown.

Parking Area Entry/Exit Test

Swarm Perception was deployed for one camera overlooking an entry-exit area to an outdoor UK parking area, where there were exiting Inductive Loops to count entries and exits. The Hikvision camera used costs just under €200.Over a period of a few weeks, the organization ran a live test comparing the accuracy of Inductive Loop, Swarm Perception, and Manual entry/exit counts of vehicles (day and night). Swarm Perception delivered significantly more accurate counts than the Inductive Loops. Induction Loops missed some vehicles (especially on entry) and also over-counted vehicles (especially on exit).

 

Why? Well, one example shows this. A car broke down at the exit, causing traffic chaos around it, this made a mess of the inductive loop counts (as cars were either stationary, drove too slowly, or drove around the Inductive Loops) while Swarm Perception continued to count as accurately as ever (without even breaking into sweat!).

Fast Highway Test

In a different test, by the same organization, Swarm Perception was deployed for one exiting standard IP camera overlooking a fast highway in Denmark, where there were exiting Inductive Loops.

Over a period of weeks, the organization compared traffic counts between the Inductive Loops, Swarm Perception, and Manual Counting over 15 minute periods. To make it more fun, the camera with the worst resolution and worst night vision configuration was chosen for the test. About 7500 vehicles pass the test location on a usual working day.

Yet again, Dynamic Perception Technology was shown to be more accurate than the Inductive Loops, even at night-time! This was despite having fast-moving vehicles further away from the camera.

Innsbruck, AustriaDumb Sensors (aka Inductive Loops) vs. Smart Swarm Sensors