Going for a hike outdoors is a great way to relieve stress, do some exercise, and get closer to nature, but tracking those adventures can be a challenge. Our recent collaboration with K-Way led Zalmotek to develop a small wearable device that can be paired to a jacket to keep tabs on walking speed, steps taken, and even the current atmospheric conditions.
At its core, the tracker can be split into having three main functions: weather prediction, step/climbing activity, and a way to gather and send raw data over Bluetooth® Low Energy to the Arduino IoT Cloud for additional processing and training machine learning models. Performing these tasks is a Nicla Sense ME board, which contains an advanced six-axis BHI260AP IMU, a three-axis magnetometer, a pressure sensor, and a BME688 four-in-one gas sensor with temperature and humidity capabilities.
Zalmotek first collected data samples using the Edge Impulse Studio from the barometer ranging from rising to falling air pressure, as they predict clear or stormy conditions, respectively. Once finished, a classification model was trained and deployed to the Nicla Sense, where the LEDs could indicate which weather pattern is more likely. The activity tracking model, however, was trained using data collected from the IMU and labeled with either walking, climbing, or staying. After integrating them both into a single sketch, Zalmotek created an Arduino IoT Cloud dashboard for displaying these values in real-time.