SpecialBoards

Normal boards

This text was written in 2020 about boards bought in 2019. The boards evolve quite quickly.

I have worked a lot with AVR boards, Arduino, or setups with ATmega328, also ATtiny85. Sometimes with RF12, for wireless transmission. Of course with sensor attached to the boards. Sometimes this board plus sensors is too fragile or to big, or just clumsy. There are now boards with sensors built in. This saves space and makes the board more portable. For education there is the BBC Microbit board, having all kinds of expressions and input without any wires. Of course these boards are not better or so than the Arduino. These boards give other possibilites.

Example of a swatch, different sensors attached to a Arduino Pro Mini (looks quite nerdy!)

A wave of specialized micro controller boards

For a project with interactive kites: https://airlaboart.wordpress.com, I bought and investigated a lot of boards with special characteristics.

All the different categories below require quite a bit of time to get used to and to get it working.

Sometimes you have to write in another programing language, like Micropython

Sometimes you have to install a new tool chain, using the terminal window.

A few links showing this tool chain pain:

https://airlaboart.wordpress.com/2019/07/04/further-intelligence/

https://airlaboart.wordpress.com/2019/07/07/and-the-third-toolchain-maix-dock/

After this project I investigated also the

BBC Microbit (22,95) https://www.floris.cc/shop/en/home/1848-microbit-go-bundel-microbit.html

Adafruit circuit playground express (29,95) https://www.adafruit.com/product/3333

Still some wires visible: mostly to the Lipo battery and providing a switch.

There is so much you can do with the boards, this post is only skimming the surface...

SD cards included

For fast real time data collection. The data are stored on the SD card and can later be retrieved and analyzed, for instance using Processing.

Boards with SD-card:

Sparkfun Razor

IMU sensors incorporated – https://learn.sparkfun.com/tutorials/9dof-razor-imu-m0-hookup-guide/all#libraries-and-example-firmware

Adafruit feather M0 adalogger (22,93 euro) https://learn.adafruit.com/adafruit-feather-m0-adalogger/

Teensy 3.6 https://www.pjrc.com/store/teensy36.html

If the SD card is not on the board you can use this device:

OpenLog: https://learn.sparkfun.com/tutorials/openlog-hookup-guide?_ga=2.10013043.776216311.1558331043-1571920724.1558331043#firmware

Acceleration included

A lot of boards have acceleration sensors included.

These sensors are referred to as IMU

BBC Microbit (22,95) https://www.floris.cc/shop/en/home/1848-microbit-go-bundel-microbit.html
Sparkfun Razor https://www.sparkfun.com/products/14001
Adafruit circuit playground express (29,95) https://www.adafruit.com/product/3333

These sensors come into a few variaties.

3 axes, acceleration x,y,z
6 axes, acceleration x,y,z, gyro x,y,z
9 axes, acceleration x,y,z, gyro x,y,z, compass x,y,z

Only...no position!

You could think that integrating the acceleration would make it possible to keep track of the sensor and calculate the position after a certain time. The formulas from physics suggest this: just integrating over time. The problem is that the errors are building up.

Gimbal lock - Quaternions

Even more problems: you really need the coordinates to be in so called quaternions and not Euler angles to get a nice graph.

About Quaternions: https://www.3dgep.com/understanding-quaternions/ (This is more theoretical about the math)

Practical, about the sensor data of acceleration, gyro and compass contributing to the quaternions: http://www.camelsoftware.com/2016/02/20/imu-maths/

The Sparkfun Razor software has this quaternions possibility built in.

Camera included

The bigger boards now have cameras included:

OpenMV7 (75 euro) https://www.antratek.nl/openmv-h7-camera, https://openmv.io

The OpenMV system has an IDE and in this IDE, there is face recognition (sort of).

Maix Dock one (30,95) https://www.antratek.nl/sipeed-m1w-ai-dev-board-with-lcd-and-camera

For the money this combination of camera, LCD and microcontroller is quite remarkable...

The programming IDE

Maix Dock Example scripts: https://github.com/sipeed/MaixPy_scripts

AI included

Speech recognition:

Sparkfun Edge (18,09) https://www.antratek.nl/edge-development-board-apollo3-blue

Gesture recognition:

Intel Curie Tiny Tile https://software.intel.com/en-us/node/675623

The camera boards have some face recognition possibilities, that is they recognize a face - not a person...

Slow and Fast Sensors

Some data have to be tracked fast, like acceleration, gyro, compass, others can be sampled at a lower rate, like temperature, pollution, air pressure.

This means that different sets of sensors can be grouped together.

Speed test

Although any number about the processor speed seems fast, there is a significant difference in speed. For recording data in real time, for instance acceleration, speed is needed to follow every movement. For AI applications lots of calculating has to be done.

For this speed test the script in « a neural network for arduino », http://robotics.hobbizine.com/arduinoann.html , was used.

Feather M0 ADALOGGER	48MHz	62.6 seconds for a learning cycle
intel Curie Tiny Tile - Arduino101	32MHz	6.4 seconds
Arduino Due	84 MHz	18 seconds
9DOF_Razor_IMU	48MHz	62.6, exactly the same as the Feather
Arduino Pro Mini	8 MHz (3.3V versions) or 16 MHz (5V versions)	100 seconds
Teensy 3.2	48 MHz	14 seconds

the intel Curie Tiny Tile is 10 times faster than the Razor, so for heavy jobs, if possible use the Tiny Tile…

The processor speed indicated in the technical specifications does not seem to influence the results much.

When storing the data on SD cards, also this storage time has to be taken into account. No doubt the way the script is written can save time. Also the way data are stored influences the final results.

BLE included

BBC Microbit has BLE

the microbits can communicate amongst themselves quite easily.

Adafruit circuit Express now also has BLE.

Intel Curie

If you want to get the BLE data on your smart phone you have to dive into the Nordic code. I used the so called Pfod parser method, it worked (after a while): https://airlaboart.wordpress.com/2019/08/06/ble-interactions-tiny-tile-pfod-2/

Pfod: https://www.forward.com.au/pfod/index.html