uThing::MNL™ is an easy-to-use USB multi-sensor dongle that integrates motion (PIR), luminosity, and ambient noise sensors.
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Features Integrates an infrared pyroelectric (PIR) motion sensor, with up to 6 meters detection range. Measures ambient light, providing a linear response over a wide dynamic range from 0.001 lux to…
Read More…uThing::MNL™ is an easy-to-use USB multi-sensor dongle which integrates a motion (PIR) sensor, a luminosity sensor, and a MEMS microphone used to measure ambient-noise (SPL) .
The aggregated output data generated from these 3 sensors can be used to detect presence of people or track the activity levels on an indoor space for example.
The uThing::MNL™ comes with two different fresnel lenses so the detection angle and range can be optimised for different applications by changing the lens.
The integrated STM32L412 MCU (ARM Cortex™-M4 with DSP instructions) captures raw data from the different sensors and apply various algorithms and signal processing (DSP) to convert the raw data into meaningful values. These values are then output on a configured interval over a simple Virtual Comm Port (VCP) on the USB connector in various formats (JSON, CSV or human-readable) for ease of integration.
We've seen over and over situations where companies, engineers or tinkerers are working in a relatively complex proof-of-concept IoT project involving several hardware and software components (sensors, actuators, embedded boards, connectivity, backend, analytics and so on) and they need to allocate plenty of resources in the sensors data acquisition part to get the sensor's data into a gateway.
If your use case requires monitoring human activity on indoor spaces, an interesting approach is to combine both the motion information from the PIR sensor and the ambient noise levels captured by the MEMS microphone and processed by the Cortex M4 MCU.
This dongle will save you plenty of firmware development time and struggles when your priority is just to get the raw + processed activity data into a gateway or embedded PC.
The VCP (Virtual Comm Port) interface makes trivial to export the data to a CSV file without the need to install any software and import in Excel for instance, or use the real-time values in JSON to integrate the sensor into a cloud-connected system, saving several hours to days of integration effort.
For example, in Mac/Linux a simple command like cat /dev/ttyACM0 > log.csv & will start saving the sensor data into a CSV formatted file, making super quick and simple to collect indoor activities data even for people with no coding skills.
Please find the latest documentation here.
The following are the data outputs available over USB:
The MEMS microphone is used to measure the ambient noise and the MCU uses digital signal processing to calculate the SPL (Sound Pressure Level), which is a logarithmic measure of the pressure level of a sound
By no means the microphone is used to sample intelligible voice or audio data, the only sound information transmited to the USB host are the SPL level measured over a 125ms time window, as in a Sound Level Meter (decibel-meter).
Either for a quick datalogging solution, or for painless software integration, check the open source uBridge server .
uBridge is a lightweigth, modular application that can log uThing's data into CSV files, publish into InfluxDB databases and MQTT servers with minimum configuration needed.
The module can be extended with custom plugins, client libraries for various languages will be available soon.
For Chrome (and Chromium) users, here it's a real-time demo dashboard that can be used without any configuration to initially evaluate the dongle behavior, just plug-in the dongle and start seeing data:
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