In the heart of Nigeria’s burgeoning agritech scene, a groundbreaking study is challenging the status quo of artificial intelligence (AI) and machine learning (ML) applications in poultry farming. Led by Azubuike Erike from the Software Engineering Department at the Federal University of Technology, this systematic literature review, published in the journal *Discover Artificial Intelligence* (which translates to *Otkritie Iskusstvennogo Intellekta* in English), is shedding light on the transformative potential of these technologies for illiterate farmers.
The study, which meticulously reviewed 39 peer-reviewed articles from 2010 to 2024, reveals that AI and ML technologies are not just for the tech-savvy. They are proving to be powerful tools in the hands of poultry farmers, even those who may not be able to read or write. “We found that deep learning models, like YOLO and CNNs, are achieving over 90% accuracy in disease detection and health monitoring,” Erike explains. “This is a game-changer for farmers who rely on their intuition and experience to manage their flocks.”
The benefits extend beyond disease detection. Traditional ML methods like Random Forest and Support Vector Machines (SVM) are improving feeding efficiency and genomic predictions. AI-driven supply chains are optimizing inventory and reducing costs, making poultry farming more profitable and sustainable.
However, the journey is not without its challenges. Poor data quality, computational demands, scalability issues, and the lack of explainable AI (XAI) and assistive AI (AAI) are significant barriers. Erike emphasizes the need for lightweight, adaptable AI models that can function in resource-constrained environments. “We need AI that can understand and adapt to the unique challenges faced by illiterate farmers,” he says.
The study also highlights the need for longitudinal studies to assess the long-term impact of AI and ML in poultry farming. Future research should explore real-time pathogen genome sequencing and blockchain integration to enhance biosecurity and transparency in the poultry industry.
The implications of this research extend beyond poultry farming. It challenges the notion that AI and ML are only for the educated elite. It shows that these technologies can be adapted to meet the needs of farmers in developing countries, boosting productivity and improving livelihoods. As the world grapples with food security issues, this research offers a glimmer of hope, a testament to the power of technology to transform lives.
In the words of Erike, “This is not just about AI. It’s about empowering farmers, creating opportunities, and building a more sustainable future.” As we look to the future, this research paves the way for more inclusive, accessible, and adaptable AI and ML applications in agriculture. It’s a call to action for technologists, policymakers, and farmers to come together and harness the power of these technologies for the greater good.