Table of Contents
Using machine learning to generate data that is aggregated and shared via a dashboard to measure the impacts of reforestation projects on biodiversity.
Data showing the co-benefits of reforestation projects need to be accurately measured and analysed in an easy-to-understand format to increase trust and transparency in voluntary carbon markets. Currently, a lack of good data is keeping capital from going to projects that increase biodiversity, social impacts, and carbon sequestration.
Data, such as satellite images, acoustic sensors, and camera traps, need to be analysed by machine learning and artificial intelligence to figure out what kinds of species are there. This data can be used to look at the trend of biodiversity and how it changes over time. A digestible dashboard provides transparency to investors and stakeholders, such as governments and non-governmental organisations. This transparency promotes investment into biodiversity projects with a clearer ROI.
- IBM Watson Studio
- Juypter Notebook
- Python
- Tensorflow
- Flask API
Please run the following two scripts in order:
pip install -r requirements.txt
python3 app.py
This program will only run on a Windows machine.
You must have python3 installed on your system.
- Rupen Patel [Communicator]
- Gerry Korfiatis [Builder]
- Kshitij Tiwari [Builder]
- Ajmal N [Builder]
- Suraj Patil [Builder]
- Badmaarag Jargalsaikhan [Communicator]