We met with the following goals:

  1. Understand the vibration sensor
  2. Once we have each sensor working (motion, sound, photosensitive, and vibration) working independently, we can put all four in the same code so they are all working simultaneously as one device.
  3. Try to further understand what this means for implementing our eight conditions for the pedestrian signal

Once the vibration sensor was connected, we found out that this sensor is binary. So at this point, we have three binary sensors (sound, motion, and vibration). In addition, the vibration sensor is highly nonsensitive, meaning that it does not pick up vibrations easily, even after sensitivity is at its absolute highest. It essentially needs to be hit on the table in order to pick up vibrations. We found this to be highly suboptimal. But we continued to consider how we could use this data just to make sure we aren’t prematurely eliminating an option.

Aside from the vibration sensor, we started to understand how to integrate multiple sensors. Today, we were able to get motion and photosensitive sensors to work together on one circuit using one python script. This task in itself came with a lot of errors. We had a lot of trouble understanding the difference between GPIO.BCM and GPIO.BOARD because our photosensitive sensor code was using one and the motion sensor code was using the other. In the end, we settled on using GPIO.BCM across all sensors, which meant just a small conversion regarding the pins. Our intuition on how the motion sensor works and when it works increased significantly since we played with the sensitivity a lot more. When we started out, we had to put the entire device in a different room so as to ensure that there was absolutely no motion being detected. But as we worked with the motion sensor more and more we understood how to orient the device to detect motion.