Cave Exploration Made Safer With The Sajac Project Powered By Nicla Sense ME
The art of cave exploration, or speleology, can bring its practitioners 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 due to falling rocks. 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 helping cavers.
Because the Nicla Sense ME contains a combination of motion, pressure and gas sensors on board, Abdillah used it to gather raw data about the wearer's surroundings by continuously taking measurements and then transmitting the values via BLE to a mobile device. Each sensor fusion sample was then added to Edge Impulse Studio and labeled with "safe", "bad" or "danger" depending on how harmful the conditions were. Finally, a Keras classification model was trained and deployed on the Nicla as an Arduino library, which is used in conjunction with an OLED display to display the classification result.
With the model now displaying sensor readings and whether they are safe or not, Abdillah has gone a 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 state as reported by the Nicla and display it on the terminal screen. Other cavers can be notified of an emergency via a connected LoRa radio which can transmit an alert message.
For more details on this proof of concept, which was shortlisted in our K-Way competition, you can read Abdillah's well-researched write-up on the Arduino Project Hub. It was also featured on our Arduino Day 2023 live stream, which you can watch here.
Categories:NiclaNicla Sense ME
The art of cave exploration, or speleology, can bring its practitioners 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 due to falling rocks. 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 helping cavers.
Because the Nicla Sense ME contains a combination of motion, pressure and gas sensors on board, Abdillah used it to gather raw data about the wearer's surroundings by continuously taking measurements and then transmitting the values via BLE to a mobile device. Each sensor fusion sample was then added to Edge Impulse Studio and labeled with "safe", "bad" or "danger" depending on how harmful the conditions were. Finally, a Keras classification model was trained and deployed on the Nicla as an Arduino library, which is used in conjunction with an OLED display to display the classification result.
With the model now displaying sensor readings and whether they are safe or not, Abdillah has gone a 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 state as reported by the Nicla and display it on the terminal screen. Other cavers can be notified of an emergency via a connected LoRa radio which can transmit an alert message.
For more details on this proof of concept, which was shortlisted in our K-Way competition, you can read Abdillah's well-researched write-up on the Arduino Project Hub. It was also featured on our Arduino Day 2023 live stream, which you can watch here.
Categories:NiclaNicla Sense ME
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