HackitshipitPackitTrackitWatchit

Inspiration

Tracking fragile, expensive, critical and perishable goods across oceans, air and land can be immensely useful for people transporting these kinds of items long distances. Say a person is transporting priceless medicine across the atlantic. The extremely fragile insides must be protected and tracked, and kept in good condition. Our product allows the user to know the conditions of the smart container at all times. Perishable high value items like vaccines, medical supplies, sensitive equipment are sensitive to various adverse conditions in transit, and the ability to track these shipment conditions real time is a necessity

What it does

Hardware: our smart crate collects the following data with direct sensing: Movement (vibrations, shocks, rolls) - 6 axis accelerometer/gyroscope CO2 - CCS811 Ambient Temperature - DHT11 Humidity - DHT11 Object temperature - Gravity Analog Temperature probe In addition, we can provide on demand imaging and video stream with a raspberry PI camera, attached to a NOIR filter for low light conditions (containers are usually dark) and on demand lighting using a NeoPixel LED ring

Ideally, this data would be relayed via the container ship (or transport vehicle’s) relay computer, which would add the GPS data from the vehicle GPS system (since we do not have access to a container ship or cargo truck, this part was hard coded)

The mobile app displays the data collected by the shipped package. The Maps Page shows where the package currently is and you can check where it is and how long it would take to get to your house. The data page shows you a live stream video of the package and also shows you the data collected from the multiple sensors in the smart container, such as temperature, humidity, gas levels, and more. The contact page allows the user to contact the people in possession of the app with the click of a button.

How I built it

Hardware: The box was assembled using cardboard, lots of tape, glue, paper and patience! The core sensors used were MPU6050 IMU, CCS811, DHT11, Grove Analog Sensor probe and raspberry pi Camera with NOIR filter and low light add-on kit. The main controller logic was on a raspberry pi, with some of the analog readings channeled through an arduino connected to a serial port on the pi. The neopixels were programmed to illuminate the box interior just before an image is captured or a stream is started.

The mobile app was developed with Flutter. We used Flutter because it is a multi platform app that you can create simple UI quickly and efficiently. We also chose Flutter because it was easy to integrate essential APIs such as the Google Maps API.