With a little soldering, we're prototyping a thermal imaging scanner which allows us to visualize thermal data. We'll be using it to see how various cases and coolers affect the thermal footprint of various single board computers, but the options are endless. With this device, you can see heat.
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Products Discussed
Prototyping RAB Platform for Raspberry Pi + Arduino
This is the RAB (Rapid Application Building) Platform you'll see Robbie using on Category5 Technology TV when prototyping Raspberry Pi or Arduino projects. It makes it a lot easier to setup your prototype, and also makes it easier to move around.
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AMG8833 IR Thermal Camera Breakout
With this affordable breakout board, you can create your own thermal imaging scanner with the aid of a single board computer such as the Raspberry Pi.
This sensor uses I2C to connect and communicate an 8x8 grid of thermal sensors, resulting in 64 points of data, which can then be converted to visual data by applying a color to heat thresholds. It's easier than it sounds since Adafruit has provided all the Python scripts ready-to-go, and we've provided a video of how we set ours up.
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Amazon.com Amazon.co.uk BangGoodRaspberry Pi Hardware: https://cat5.tv/pi
How To:
- Solder the provided 6-pin header so it protrudes from the opposite side of the breakout to the sensor.
- Connect your sensor to your Raspberry Pi as per the video.
- Boot a fresh install of Raspbian Desktop.
- Activate I2C in the Interfaces section of raspi-config.
- Reboot.
- In the terminal, type this to see if your sensor is detected:
sudo i2cdetect -y 1 - Install dependencies:
apt update && apt install git build-essential python-pip python-dev python-smbus python-scipy python-pygame - Install the drivers:
cd /tmp git clone https://github.com/adafruit/Adafruit_Python_GPIO.git cd Adafruit_Python_GPIO/ python setup.py install pip install colour Adafruit_AMG88xx - Install the sample Python scripts:
cd /home/pi git clone https://github.com/adafruit/Adafruit_AMG88xx_python.git cd Adafruit_AMG88xx_python/examples/ - See the 64-sensor thermal data:
./python pixels_test.py - See the output of the integrated thermistor:
./python thermistor_test.py - Finally, visualize the data:
./python thermal_cam.py
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Discussion
Season 14 starts soon!
Episode 664 will be live October 14! See you then.
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