Aim of the project
This project aims to provide an artificial intelligence-based solution to help farmers tackle the threats posed by climate change.
Project summary
Against the backdrop of worsening climate change, which leaves African farmers vulnerable to the adverse effects of erratic weather due to their heavy reliance on rain-fed agriculture, the study aims to propose an artificial intelligence-based solution to address this threat, particularly as it affects women farmers, who play a pivotal role in production and reproduction within rural households in sub-Saharan Africa. More specifically, the study seeks to adapt existing AI-based solutions to address climate-related issues, particularly the erratic weather conditions faced by women farmers, and to formulate data-driven policy recommendations on how women farmers can be empowered to make the best use of appropriate and responsible AI-based solutions. The project will be extremely useful in strengthening the capacities of women farmers as recognised drivers of the socio-economic status of rural households and will contribute to the achievement of the Sustainable Development Goals aimed at promoting gender equality, the eradication of poverty and the eradication of hunger (Sustainable Development Goals 5, 1 and 2 respectively).
Project leader: Dr Olayinka Jelili Yusuf
The team leader, who holds a PhD in agricultural extension and rural sociology, specialises in agricultural technology transfer, gender and rural development. He has been involved in several gender-focused projects, including Project 643 of the Partnership for the Development of Higher Education (DelPHE) on the theme “African Women and the Rural Environment” (AWARE), sponsored by the UK Department for International Development (DFID), amongst others. Dr Yusuf is currently an associate professor of rural sociology and extension in the Department of Agricultural Economics and Extension Services at Kwara State University, and research director of the “Artificial Intelligence for Sustainable Agriculture and Rural Development” (AI4SARD) research network.
The other team members
The team comprises researchers from a variety of disciplines and backgrounds, whose expertise will be pooled to achieve the project’s objectives.
Khadijat Olanrewaju
She holds a PhD in agricultural extension and rural sociology, specialising in the same field. Dr Khadijat has been involved in several initiatives focused on gender-based development and is currently working on organising rural women to engage in collective action for development at the extension stations of the Department of Agricultural Extension and Rural Development at Osun State University, Osogbo, Nigeria, where she is based.
Ms Martha Alade
She holds a Master’s degree in Computer Science and a Master’s degree in Research and Public Policy. She is a data analyst and advocate for gender-sensitive AI, as well as the founder and executive director of Women in Technology in Nigeria (WITIN). She has extensive experience of working with rural women to achieve food security and sustainable agriculture and has won several awards and honours for her numerous projects focused on women’s empowerment. Her recent project, WomenPRIDE.Africa, won the 2022 UN WSIS Championship and was also recognised at national level by the federal government this year. She has been selected to be part of the team tasked with formulating Nigeria’s artificial intelligence policy.
Kazeem Dauda
He holds a PhD in statistics and specialises in machine learning, data science and artificial intelligence. He recently completed a postdoctoral fellowship at the Artificial Intelligence Laboratory of the Indian Institute of Statistics in India. Dr Daud is affiliated with the Department of Mathematics and Statistics at Kwara State University and is a member of the AI4SARD research network.
Ronke Babatunde
She holds a PhD in computer science and specialises in computer vision, pattern recognition, machine learning and artificial intelligence. She is based in the Department of Computer Science at Kwara State University and is also part of the KWASU team working on the AI4FS project.
Ms Kemi Afolabi-Yusuf
She holds an MSc in Computer Science, specialising in AI and information security, from the Department of Mathematics and Computer Science at Summit University in Offa, Nigeria. She is one of the key members of her university’s team working on the AI4FS project.
Dr Latifat Olatinwo
She holds a PhD in agricultural extension and specialises in agricultural extension, gender and youth studies. She is a senior lecturer in the Department of Agricultural Economics and Extension Services at Kwara State University.
Dr Ololade Abdulrahman
He also holds a PhD in agricultural extension and specialises in agricultural extension, gender and youth, and works in the Department of Agricultural Economics and Extension Services at Kwara State University.
Abdulrahman Ibrahim
He holds a PhD in French language and linguistics and a Master’s degree in international relations and diplomacy; he is bilingual (English–French) and specialises in applied linguistics, sociolinguistics and international relations. He is a translator and conference interpreter. He is fluent in English and French and is taking several courses in French language and culture at the Department of Arabic and French at KWASU.
Institution
Kwara State University (KWASU) was established in 2009 as a state-owned and state-funded institution of higher education. The university was founded with the aim of providing high-quality education to students from the Kwara State region of Nigeria, with a focus on innovation and research.
Since its foundation, KWASU has made a name for itself as a leading university in Nigeria, with a focus on research and innovation. The university has received numerous grants and awards for its research projects, and its lecturers and students have made significant contributions to their respective fields.
Overall, KWASU has a rich history of academic excellence and a bright future ahead of it.
Not so long ago, people lived and went about their daily lives in close-knit communities. Every shopkeeper knew their customers personally and could...
This Machine Learning Glossary aims to provide a brief introduction to the most important machine learning terms – both for commercial and...