The art of cave exploration, or spelunking, can get its practitioners far closer to nature and the land we inhabit, but it also comes with a host of potential dangers. Some include extreme environmental conditions, lack of oxygen/toxic gases, and simply having their path closed off due to rock falls. Seeing these problems, Rifqi Abdillah decided to create the Sajac Project based on the Nicla Sense ME attached to a K-Way jacket with the aim of assisting cavers.

Because the Nicla Sense ME contains a combination of motion, pressure, and gas sensors onboard, Abdillah used it to gather raw data about the wearer’s surroundings by continuously taking readings and then transmitting the values over BLE to a mobile device. Each sensor fusion sample was then added to the Edge Impulse Studio and labeled with either “safe,” “bad,” or “danger” depending on how harmful the conditions would be. Finally, a Keras classification model was trained and deployed back to the Nicla as an Arduino library, which is used in conjunction with an OLED screen to show the classification result.

With the model now outputting the sensor readings and if they are safe or unsafe, Abdillah went one step further and developed an app to display them in real-time on a Seeed Studio Wio Terminal. Built in MIT’s App Inventor, it allows the user to select the current status as shown by the Nicla and have it appear on the Terminal’s screen. Fellow cavers are able to be notified in an emergency via a connected LoRa radio that can transmit an alert message. 

For more details on this proof of concept, which was shortlisted as part of our K-Way competition, you can read Abdillah’s well-documented write-up on the Arduino Project Hub. It was also featured on our Arduino Day 2023 livestream, which you can see here.

Categories:NiclaNicla Sense ME

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