Automated Poultry Diseases Diagnostics using Deep Learning

The Automated Poultry Diseases Diagnostics (APDD) project seeks to develop a poultry diseases diagnostics tool using deep learning for improving poultry health for farmers in Tanzania. The diagnostics tool is aimed at early detection of Coccidiosis, Salmonella and Newcastle disease virus from fecal samples. The project is funded by the Organization of Women in Science for the Developing World (OWSD) under the 2019 Early Career Fellowship Program and the 2020 AI4D-IndabaX Innovation Grant programme.

The APDD Project is hosted at the School of Computational and Communication Science and Engineering (CoCSE) at the Nelson Mandela African Institution of Science and Technology (NM-AIST).

The deliverables of the project are:

• A mobile application for use by farmers and livestock officers for early detection of Coccidiosis, Salmonella and Newcastle.
• A machine learning dataset for poultry diseases diagnostics.