Although the advent of widespread online shopping has been a great convenience, it has also led to a sharp increase in the number of returned items. This can be blamed on a number of factors, but a large contributor to this issue is damage in shipping. Shebin Jose Jacob’s solution involves building a small tracker that accompanies the package throughout its journey and sends alerts when mishandling is detected.
Jacob started by creating a new Edge Impulse project and collecting around 30 minutes of motion samples from an Arduino Nano 33 BLE Sense’s onboard three-axis accelerometer. Each sample was sorted into one of five categories that range from no motion all the way to a hard fall or vigorous shaking. Features were then generated and used to train a Keras model, which yielded an accuracy of 91.3% in testing.
To communicate with the outside world, Jacob added a GSM module that allows the Nano 33 BLE Sense to send alerts over a 3G network to an awaiting Firebase endpoint. When the database updates, new data is propagated to a user-face webpage that shows the current status of the package along with any important events.
More details can be found here in Jacob’s project write-up.