Our idea took to solving potential inefficiencies in a homegrown industry while combating a current issue. In early 2017, $18M of maple syrup was stolen from a reservoir and went largely unaccounted for until an investigation was conducted. Along with the 44 million taps located across Canada, monitor maple syrup is a highly time-consumptive task that can be optimized to become more profitable. Our solution aims to utilize a connected network to track production and optimize collection through the internet of things.

What it does

Currently using ultrasonic sensors to determine depth of our maple syrup collection, data is relayed through microcontroller devices through a Qualcomm DragonBoard 410c into a cloud server. Data is then transferred to a mobile frontend that allows key members of the industry to access levels of syrup, which trees are ready to be collected and optimal routing. With additional features that relate to environmental factors to be integrated, the quality of the tree sap can also be evaluated.

How we built it

The system is triple faceted. On the data collection side, we integrated ultrasonic sensors to measure depth with Adafruit Feather M0 board to collect and relay information. The information is then sent through a bluetooth communication protocol into a Qualcomm DragonBoard 410c where it is served up to the cloud. Data is then processed and stored, with accessibility to modify given to the DragonBoard administrator and authorized mobile users who have access through our Android application.

Challenges we ran into

One of the biggest difficulties that we ran into was integrating the communication between the Feather M0's and the DragonBoard.

Accomplishments that we're proud of

The creation of a system that required each of us to work on drastically different components (data collection/Bluetooth communication, data integration/relaying into the cloud, server management and front-end mobile development) that conhesively worked together to realize the idea that we came up with and completed in 22 hours.

What we learned

Hardware integration can be painfully difficult but can lead to the creation of an elaborate and satisfying end-product.

What's next for MapleMesh

Integration of further features relating to environmental factors, route optimization, web interfacing.

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