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Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto
Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto
Computer Engineering
The Underwater Computer Vision – Fish Recognition project includes the design and implementation of a device that can withstand staying underwater for a duration of time, take pictures of underwater creatures, such as fish, and be able to identify certain fish. The system is meant to be cheap to create, yet still able to process the images it takes and identify the objects in the pictures with some accuracy. The device can output its results to another device or an end user.
Smartgarden, Samuel S. Lees, Matthew T. Lindly
Smartgarden, Samuel S. Lees, Matthew T. Lindly
Computer Engineering
The problem that the SmartGarden project seeks to solve is the challenge of watering succulents correctly and maintaining consistent plant health. Too much water can cause root rot and drowning while too little water can cause dehydration and starvation.
The SmartGarden solves this common problem by configuring a Raspberry Pi to measure soil moisture, store the data to an AWS server in the cloud, and water the succulent when necessary, informing the user by providing both a web-interface and a variety of notifications.