OLUSOJI ADEYEMO
Olusoji Adeyemo, an Azure Application Innovation & AI Specialist with Microsoft UK, has a Master's in Computer Science with distinction from the University of Hertfordshire and Caleb University, and a Bachelor's degree in Chemical Engineering from the University of Port Harcourt. He is currently enrolled to start his PhD research in Explainable AI and ML in the University of Hertfordshire UK. He is also certified in various cloud and project management technologies, including Microsoft Azure Expert, Google Expert, AWS and Scrum. He can be reached at mastersoji@gmail.com and on Linkedin: https://www.linkedin.com/in/olusoji-adeyemo/
Climate change is a defining challenge of the 21st century, and its effects are disproportionately felt in developing regions, particularly in Africa. Nigeria, as the most populous country on the continent and one of its largest economies, is increasingly experiencing the environmental, economic, and social consequences of climate change. Rising temperatures, erratic rainfall patterns, desertification, and coastal erosion threaten food security, livelihoods, and public health. Against this backdrop, Artificial Intelligence (AI) has emerged as a transformative force with the potential to address some of the most pressing sustainability challenges.
This article explores how AI-powered solutions are being leveraged across Africa and Nigeria to combat climate change and promote sustainable development.
Understanding climate change and sustainability challenges in Africa and Nigeria
Africa contributes the least to global greenhouse gas emissions but bears a significant brunt of climate change. Key environmental challenges include:
- Deforestation and land degradation: Driven by agricultural expansion, fuelwood consumption, and urbanisation.
- Water scarcity and pollution: Affecting agriculture, industry, and human health.
- Energy access and efficiency: A large portion of the population lacks reliable electricity, while existing infrastructure is often inefficient.
- Urbanisation and waste management: Rapid urban growth strains waste disposal systems and contributes to pollution.
- Food insecurity: Caused by unpredictable weather, poor soil conditions, and limited access to technology.
- Climate modeling and forecasting: AI algorithms enhance the accuracy of climate models by integrating data from satellites, weather stations, and historical records. In Nigeria, AI can improve early warning systems for floods and droughts, helping communities prepare and adapt.
- Precision agriculture: AI-driven platforms analyse soil data, weather forecasts, and crop performance to provide farmers with actionable insights. This reduces resource use (water, fertiliser) and increases yields. In Northern Nigeria, for instance, startups are using AI to guide irrigation schedules and pest control.
- Renewable energy optimization: AI optimizes the generation, storage, and distribution of renewable energy (solar, wind, hydro). It predicts energy demand, adjusts supply in real-time, and manages smart grids. In off-grid Nigerian communities, AI supports the efficient operation of solar mini-grids.
- Natural resource management: AI tools monitor deforestation, water quality, and land use changes via satellite imagery. Governments and NGOs can use these insights to enforce environmental regulations and plan sustainable land use.
- Disaster prediction and response: AI improves disaster risk management by predicting extreme weather events and coordinating emergency responses. For flood-prone areas in Lagos and Bayelsa States, AI can enhance evacuation planning and resource allocation.
- Rainforest connection: Uses AI and acoustic sensors to detect illegal logging in real-time in African forests.
- IBM’s Green Horizons: Provides air pollution forecasting and energy optimization tools in South Africa.
- Aerobotics (South Africa): Utilizes AI and drones to help farmers monitor crop health and optimize pesticide use.
- ColdHubs: Uses solar-powered cold storage managed with AI to reduce post-harvest losses for farmers.
- Hello Tractor: Combines AI and IoT to help smallholder farmers access tractor services efficiently.
- Gridless Africa: Uses AI to balance loads and reduce downtime in mini-grid power systems.
- Data gaps: Lack of high-quality, localised environmental data.
- Infrastructure deficiencies: Poor internet connectivity, electricity, and computing power.
- Limited expertise: Shortage of skilled AI professionals and environmental scientists.
- Policy and governance issues: Weak regulatory frameworks and limited government support.
- Affordability and access: High cost of AI solutions and limited access for rural communities.
- Invest in infrastructure: Improve internet access, electricity, and data centers.
- Strengthen data ecosystems: Promote open data initiatives and build data collection systems.
- Develop talent: Support AI education, training, and research institutions.
- Encourage public-private partnerships: Leverage synergies between governments, tech companies, and NGOs.
- Promote policy reform: Establish frameworks that support AI innovation and environmental protection.
- Climate-resilient cities: AI can help design smart, low-emission urban environments.
- Circular economy initiatives: AI can optimize waste management and recycling systems.
- Green finance and carbon markets: AI can track emissions and verify carbon credits.
- Youth engagement: Mobilising young innovators to create AI solutions for local climate issues.