Inspiration
The motivation behind this project was to help in the survival of elephants and rhinos, namely from poachers in South Africa. The deployment goal, in the end is to have our system set up in a conservatory to help monitor the behavioral patterns of elephants and rhinos, and correlate them against anomalies, both visually and through IoT devices that will allow for environmental monitoring.
What it does
It uses a clustering based pattern recognition algorithm built on tensorflow to identify elephants and rhinos, as well as other behaviors of cohabitants and industrial anomalies.
How I built it
Using python for the machine learning algorithms, NodeJS with Express for the backend server, SAP Fiori UI5 for the front end and SAP Cloud for the deployment location.
Challenges I ran into
Having tensorflow properly operate on my local machine.
Accomplishments that I'm proud of
Getting tensorflow to recognize patterns, and using command level arguments to process data in python from NodeJS.
What I learned
Multi-platform integration and cross-language synthesis
What's next for Sparrow
Getting the IoT aspect built and running, and testing the current development, as much of it is heavily untested at the moment.
Built With
- batch
- express.js
- node.js
- python
- sap-cloud
- tensorflow
- ui5
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