Very interesting project from Google ATAP which uses a miniaturized radar device to detect hand gestures. Because it doesn’t use structured light, it has the potential to work outdoors and in difficult environments. Experience shows that structured light has a lot of limitations so radar technology like this is potentially a big step forward.
It has been around for a while – it’ll be interesting to see if it does turn into a real thing.
rtndf now has Python PPEs that support streaming data from a variety of environmental sensors. The sensehat PPE streams data from all of the sensors on the Raspberry Pi Sense HAT. The sensors PPE streams data from a variety of common environmental sensors:
- ADX345 accelerometer
- BMP180 pressure/temperature sensor
- HTU21D humidity sensor
- MCP9808 temperature sensor
- TMP102 temperature sensor
- TSL2561 light sensor
The specific sensors in use can be enabled by selectively commenting out lines in the sensors Python script.
sensorview is another new PPE that can display the sensor streams generated by sensehat and sensors. The screenshot shows the data from a sensehat for example.
Up to now the only data sources in rtndf were video and audio. imu is a new Python PPE that can be used to stream IMU data (fused pose, sensor readings etc) into an rtndf data flow pipeline. Another new PPE is imuview, this time a C++ PPE, that can display the resulting stream. The screen capture above shows the data being streamed from a Raspberry Pi SenseHat which is a full 11-dof sensor.
One of the nice things about using a pub/sub system like MQTT is that it is possible to hook into any of the pipeline links to see what data is flowing. To this end, a future PPE will be a generic viewer. The user just gives it the topic and it determines the type of data and displays it appropriately. A very handy debugging tool!