SnapCat isn't anything new or fancy. Our solution makes use of advancements in machine learning, low-power embedded systems, and wireless technologies. We aren't trying to make the tech better, we're just making it more accessible to the groups who need it.
SnapCat is based on the open-source TensorFlow software provided by Google. We make use of a pre-trained neural network that can be retrained to detect for a species (or thing!) of your choice. Our current initiative is to provide the nonprofit, Island Conservation, with a feral cat classifier that can be used in the Rock Islands of Palau.
We are currently developing a tool that expedites the classification and labeling of datasets from Island Conservation's project islands. We are also open to working with other organizations that can benefit from our technology (Examples include: poacher detection, rare animal tracking, population counting, etc).
At the moment, our solution is a post-processing tool for organizations that make use of off-the-shelf camera traps (Reconyx, Bushnell, etc). Our future plans include developing a low-cost camera that runs the classifier on an on-board microcontroller. Included in this design would be a propagation method using LoRaWAN, to transmit the detection event to a base station.