Project:Spacensus: Difference between revisions

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==Overview==
==Overview==
I have located two Laser Diode Retroreflective Sensors in our stores which I intend to use to monitor space occupancy by having the beams cross the main doorway. The beams will be staggered so that direction (arriving, leaving) can be determined by the order in which the beams are broken. I was thinking of mounting them at waist height.
I have located two Laser Diode Retroreflective Sensors in our stores which I intend to use to monitor space occupancy by having the beams cross the main doorway. The beams will be staggered so that direction (arriving, leaving) can be determined by the order in which the beams are broken. I was thinking of mounting them at waist height.


The occupancy level is [http://hack.rs/cacti/graph.php?action=view&local_graph_id=35&rra_id=all charted on cacti].
The occupancy level is [http://hack.rs/cacti/graph.php?action=view&local_graph_id=35&rra_id=all charted on cacti].

Revision as of 13:50, 31 March 2011

Spacensus


Members Elliot
QR code
In situe
Prototype

Part of the London Hackspace graphs and visualisations project.


Overview

I have located two Laser Diode Retroreflective Sensors in our stores which I intend to use to monitor space occupancy by having the beams cross the main doorway. The beams will be staggered so that direction (arriving, leaving) can be determined by the order in which the beams are broken. I was thinking of mounting them at waist height.

The occupancy level is charted on cacti.

Status

Recent modifications:

  • Milled new bracket for sensors.
  • Graphical display with graph showing the days occupancy
  • Detection code now completely interrupt driven
  • Beams are now polarized
  • Beams are now very close together
  • Temporary prism reflector being used (permanent replacement on order)

What next

  • Fit reflector
  • Move sensor closer to door
  • Try some different timing configurations to improve detection
  • The python script that provides the data to cacti implements only the 'poll for status' command, but will later allow more control and configuration of the counting sensors.

Location

The current mounting location has the lasers In close proximity in the middle of the entrance way. To avoid issues with occlusion of beams by coats etc, the coat hooks have been moved to the next wall along, with the lab coats. This arrangement greatly simplifies the detection of the true direction of someone entering/leaving the space. Detection works reasonably well.

Powering off

  1. Remove the USB cable from the side of the unit.
  2. Remove the 12VDC jack from the side of the unit.
  3. Check the beams are no longer emitted and that no sensor indicators are illuminated.

Safety signs

Positioned above sensors.
External door warning.

Sensors

These sensors appear to be in working order. They'd should be safe to use below child-head height. They were manufactured in 1996 and use a Class II laser rated at 3mW (peak), 2kHz 2% duty cycle, with a wavelength of 655-670nm (datasheet). The model number is: Q45BB6LL

A good signal can be obtained at 1.5m by using a reflector made of aluminium tape.

Code

The code is available on GitHub - please be kind it's my first Arduino project and I know the code is filth.

The detection aspects of spacensus use an interrupt driven state machine. Anything that isn't time critical stuff happens in a run-loop.

Spacensus state machine diagram.png

FAQ

Q: This will probably get caught out by clusters of people: --81.105.17.61

A:

  • We only need an approximate count
  • The doorway is narrow so it's unlikely that the steps of more than one individual will overlap.
  • Most of the time people won't arrive in clusters

Q: Can we detect some other event such as the door opening after a prolonged lights-out period to force the count to zero? --81.105.17.61

A:

  • Yes, using the door/lights data for reset would be good if we get large amounts of drift - but I don't plan to just yet
  • This might fail if people spend the night there. AIUI this happens rarely enough that we may not care about the inaccuracy.
  • We could also use some kind of probabilistic model with the 'door-open' and 'bell' data