StripPi – Software Demo, Roadkill Electronics

I’m constantly loosing the remote for my RGB LED strip lights, and I have a few days for spring break, time to get hacking. Here’s a demo and explanation video:

I don’t mention it in the video, but the cool part of this project is how the different processes communicate with each other. Rather than interacting with the different processes through pipes, or something like stdin, I’ve decided to use a TCP websocket server:

StripPi High Level Diagram

Processes on the device send RGB values to the Strip Server via a TCP packet. This very very easy to implement, and almost all of the hard work is taken care of via the socketserver  module included in python3. This also allows for interactions with that main process (the StripPi Server process) to take place off of the Raspberry Pi as well. I plan on writing an Alexa integration for this project moving forward, and this should make that a lot easier.

The analog to digital conversion is handled by an MCP3008, exactly the same way as I did it here.

Thanks for reading, more soon.

Raspberry Pi Digital Hourglass

Trying to get the most out of a day has been big theme of my life lately, as I’m sure it is for many people. I’ve found that I always manage my time better when things are urgent; I’m considerably more productive when I have to be.

I want an ascetically pleasing way to be able to represent how much time is left in the day at a granular scale, like an hourglass. Watching individual seconds disappear will look cool and (hopefully) create that sense of urgency that I want to induce.

Technically, this is a really simple thing to accomplish thanks to python and pygame. Here’s a video of a proof of concept running on my laptop:

At the start of each day, the display is filled with squares at random locations, with a random color. As each second elapses, a square will vanish.

To make it easier to see for the video, I’ve made the squares much bigger than they will actually be for the final build. This is what the display looks like with the squares at their actual size:

The code really really simple, like less than 100 lines simple. Here’s how it works:

Here’s the version of the code running on my computer in the video:

Let’s walk through some of the design decisions of this code. The first thing that’s worth talking about is how the data for the squares is handled:

It’s just an object with no methods, and on initialization, all the parameters of the square (location and color) are generated randomly as opposed to just floating the raw numbers in arrays around (even though that’s basically what is happening). This let’s us fill the squares array very easily later on in the file here:

and here:

When it comes time to draw these squares, it also makes that pretty intuitive:

Again, very simple stuff, but worth it to talk about.

I’ll be back at my place that has the Raspberry Pi and display I would like to use for this project, so more on this then.

Thanks for reading!

Creature Capture | Variable Video Capture Length Code & Testing, Frame Rate Issues

So I’ve been working a lot in the past day in ironing out part of the night side loop (loop 3 in this diagram). Basically, it starts recording based on an input from a sensor and continues to record until these inputs stop occurring.

My test code looks like this

The interesting functions at work here are the following:

FilmDurationTrigger() Takes the period of time that will be filmed, in this example, it’s 5 seconds just to conserve time, but in application it will be 20 seconds. This code will pause for the input time, and continue to be paused upon inputs from GetContinueTrigger(). This delay allows the code to continue filming until there are no inputs.

In this example, GetContinueTrigger() returns a Boolean if a random event occurs, but in application it will return a Boolean based on the status of a motion detector.

I ran two tests, both of them produced separate results. The first one created a 10 second long video:

And the second created a 15 second long video:

These two test shows that variable capture length functionality works! As a note, the actual times on the output video varies from the amount of time that it’s designed to record for. This is because the variable frame rate nature of the video coming out of the camera module, it causes the videos to come out a little short, but they still contain all the frames of the amount of time desired to record, just scaled slightly by frame rate error.

Creature Capture | Stopping Raspivid After a Non-Predetermined Time

One of the biggest problems with the built in commands for using the Raspberry Pi Camera module is that you can’t stop a recording after an unknown time. You can record for a given number of seconds and that’s it. I have attempted to solve this problem by backgrounding the initial record process with a time of 27777.8 hours (99999999 seconds) when it’s time to stop recording, the process is manually killed using pkill.

Here is a test of my code, which I’ve called CameraModulePlus (written in python) which takes two videos, one for five seconds, and one for ten seconds, with a 10 second delay in between.

Here is a result of the 5 second duration test:

Here is a result of the 10 second duration test:

As you can see, it works pretty good for how barbaric it is. The full class for CameraModuleVideo can be found here. In the future, I’d like to encode a lot more data into the CameraModuleVideo class, things about time etc. Also I would like to monitor available space on the device to make sure there is enough space to record.

Creature Capture | Project Declaration & Top Level Flowchart

I’ve decided to embark on a video surveillance project! My family lives in a very rural part of the US, and constantly hear and see evidence of animals going crazy outside of my home at night. The goal of this project is to hopefully provide some kind of insight as to what animals actually live in my backyard.

Ideally, I want to monitor the yard using some kind if infrared motion detector. Upon a motion detection, an IR camera assisted by some IR spotlights would begin filming until it has been determined that there isn’t any more movement going on in yard. These clips would then be filed into a directory, and at the end of the night, they would be compiled and uploaded to YouTube. This video would then be sent to the user via email.

I’ve created the following flowchart to develop against as I begin implementing this idea.

I’ll be using a Raspberry Pi to implement this idea, a few months back I bought the IR camera module and haven’t used it for anything, this would be a good project to test it out.

There are a few hurtles that I’ll have to cross in order to make this project a success, like most groups of problems I deal with, they can be separated into hardware and software components.

Hardware

  1. Minimize false positives by strategically arranging motion detectors
  2. Make sure IR Spotlights are powerful enough to illuminate area
  3. Enclosure must be weatherproof & blend in with environment, Maine winters are brutal.

Software

  1. The Pi doesn’t have any built in software to take undetermined lengths of video.
  2. Must have a lot of error catching and other good OO concepts in order to ensure a long runtime.

I’ve actually come up with a routine for solving the first software problem I’ve listed, hopefully I’ll have an example of my solution in action later tonight.

Ideally, this project will have a working implementation completed by May 21, which is 7 days from now.

@heywpi | Adding new features, more Object-Oriented code

First here’s a video of me demonstrating a few of the new features:

So compared to the original version of this project, the following changes are as follows:

  • Added function that takes image from incoming tweet, finds most common color in the image and writes it to the LEDs.
  • Added fading between colors instead of just jumping between them.
  • Added routine to respond to users when an error occurs in their tweet, like it’s missing a color or something is spelled wrong.
  • Re-Wrote most of code into an objects and methods on that object to get rid of global variables.

A few notes on the new features:

The operation of the image ingestion feature is pretty simple. All you have to do is tweet an image at @heyWPI just like you would with text. It finds the most common color in the image and then writes it the the LEDs. Here’s an example:

Input:

Output:

 

It works pretty well. If you look at the code, you’ll see that I tried to make it as modular as I could so I can possibly improve the color detection algorithm moving forward without making major changes in the code. This required the system to have some kind of memory to keep track of the current values written to the LEDs. Originally, I was using global variables to solve this problem but it wasn’t all that clean so I made it all more object oriented.

As for the fading You can sort of see it in the video, but the fading between colors looks really nice, especially from and to opposite complex colors like purple to orange.

A big problem I had with different people using the project was that sometimes people would use an invalid color. I implemented a default message to send if a received tweet didn’t have a color in the text or didn’t have an image in the body.

Want to make one?

@heywpi | How To Build Version 0_1_X

1. Install the prerequisites for the python code with the following:

2. Download the main heyWPI.py file

3. Download the LEDFuns2.py file for driving the LEDs – Place it in the same directory as heyWPI.py

4. Download the Log.py file for getting feedback on the status of the system – Place it in the same directory as heyWPI.py

5. Run the following commands in the same directory as heyWPI.py, this allows the Pi to drive the LEDs. More info on this step here:

6. Now enter your twitter api information into the heyWPI.py file at the top of the heyWPI class. If you don’t have twitter API info click here to get that for free!

You should be ready to rock and roll on the software side, now let’s look at the hardware schematic.

 

I’ve tried to make this as simple as possible, but it probably isn’t the best way to drive these LEDs, moving forward I’d like to drive these strips with a constant current.

Here are the parts to build it:

If you end up building this let me know!

@heywpi | Twitter Interaction, Bringing it All Together

Here’s a video of the whole thing in use!

Using the python library, tweepy, getting the twitter interaction to work was actually very simple. The downside is that I can only retrieve mention data every 60 seconds due to Twitter’s API rate limiting.

The circuit is very simple, the RGB led strip I have is common anode, so I used N-Channel mosfets attached to pins 18 (Red), 23 (Green) and 24 (Blue). For the camera, I’m using a spare raspberry pi camera module I have.

For the names of the colors you can write to the lights, I went with the 140 X-11 colors. I figured it was a good spectrum of colors.

The source code for the whole project will keep getting updated, so check here for the most recent versions of each file.

I’d love to expand the scale of the project, if you’re a student at wpi and would like on of these in your window, please email me at the addressed listed in the about section of my website.

Thanks for reading!

@heywpi | Pi-Blaster Python “wrapper” With RGB value Inputs

PWM with a Raspberry Pi is tricky. There is an official meathod of doing this, but I’ve found that when driving multiple channels (like 3 for an RGB LED) it doesn’t work to well and is noticeably shaky when transitioning to new PWM cycles.

Looking for alternatives, I found pi-blaster. From their github:

This project enables PWM on the GPIO pins you request of a Raspberry Pi. The technique used is extremely efficient: does not use the CPU and gives very stable pulses.

It was pretty simple to create a utility to drive my RGB LEDs with. My code can be found here.

To install pi-blaster for use with this code, you’ll need to download and install like so.

Make sure you are in the same directory as LEDFuns.py

The pi-blaster directory should be within the same directory as the LEDFuns.py file.

Thanks for reading! More on this project soon.

PiPlanter 2 | Plant Update and Daughter Board Migration

First, a video:

I’ve worked very hard since my last update to move all of the hardware that interfaces the Raspberry Pi with the plants (GPIO, ADC etc) from on board the Raspberry Pi using the GIPO to a daughterboard based around an Arduino.

This has been a lot of work to accomplish, but as of about a week ago, the transition was completed in it’s entirety and everything is operating totally normally without using any GIPO on the Pi.

This provides a portability for the platform that I haven’t been able to achieve so far. As the name of the project suggests, I’ve only used a Raspberry Pi to drive all of the hardware so far as well as do everything with the software. This transition opens up the possibility of using any computer running linux to be able to drive a PiPlanter if they have the board.

I’ve outlined the “PiPlanter Hardware Specification” in the current block diagram for the project. So if you have these parts, you can make a PiPlanter. The protocol for communicating between host computer and the Arduino is outlined here. I’ve decided to go with plain text serial using a rudimentary handshake to handle the communication. Pretty much all computers have a serial port, and the Arduino is very good at dealing with it as well.

One of the next steps that I take in this project would to be to design and fabricate PCB’s for specifically for this. This is certainly going to be a challenge for me, but it’s nothing I can’t handle. This also gives me the opportunity to maybe start selling PiPlanters which is exciting. I might need to change the name for obvious reasons…

Here are some nice photos of the updated setup:


All of the code and documentation for this version of the PiPlanter can be found here.

I am going on break from school from today, December 18th 2014 to on or around January 14th 2015. Now that the PiPlanter isn’t at my house, I can’t access the network remotely and make changes to the code. The next month will be a good stress test of the new daughterboard infrastructure. Hopefully it all goes well.

Thanks for reading!