Cameras + cha-ching!

This afternoon Vicky and I researched ways to perform motion detection. Our two main options were sensors or cameras. After considering which method would grant more opportunity for iteration and which excited us more in terms of our learning goals, we decided to go with a camera. We're excited to work with OpenCV software to iteratively develop software that detects motion around our structure.

Next, we researched which camera would be most effective and still within our budget. We decided on a 5 megapixel Arducam that interfaces with a Raspberry Pi. It should be coming in on Monday!

- Gracey

Comments

Post a Comment

Popular posts from this blog

Where Mechanical At

Sprint 2 ended on Friday and we have our MVP! What that means for mechanical is that we have a box that can move nine different nodes, but control 3 sets independently, using three actuators. We made our prototype with some scrap .21" hardwood with the laser cutters. We converted the rotational motion of the sliders into linear motion with a pin and rack design, with the rack mounted on a slider with ball bearings to reduce the friction. The three gears were connected with a rod so that as one gear rotates the rest rotate as well. Our challenge coincided with retaining the gears with the bearings linearly, since the gear shaft would often tilt down (it was not a perfect press fit. We ended capping both sides of the shaft to retain it, but due to a misprint, the final design was switched, so the cap was not as effective as it should have been. The biggest issues with this design is that there was a lot of friction in the gears, and the system was too constrained, which made rotatin...
Read more

Mid Sprint 4!

The final sprint has come to pass and demo day is just around the corner! The mechanical team has worked hard to get the entire mechanical system up and running and the software/electrical team is currently working toe get the system flawlessly integrated with the web app and integrating the sound detection code into the system. We are really excited about the final demo day and we think we are in good shape for getting all of our ducks in a row in time. Stay tuned!
Read more
Image
Today Peter and I worked on reading and interpreting audio signals using pyaudio. We made use of functions from Allen Downey's ThinkDSP book to help us extract frequencies and magnitudes for .wav files. We were able to graph the distribution of the frequencies and their magnitudes and were able to see a difference when we recorded a sound with a low frequency and one with a higher frequency. Our next steps are going to involve figuring out how we can extract useful information (frequency with highest magnitude) as our code is running. We might also try to use threading so that we can be recording and interpreting sound data at the same time.  - Vicky
Read more