IBM and Sustainable Energy for All (SEforALL), a UN-backed initiative promoting universal energy access and sustainable energy transitions, have launched two artificial intelligence (AI)-driven tools aimed at addressing urbanisation and energy infrastructure challenges in developing regions.
Announced at COP29, which took place in Azerbaijan this week, the solutions provide policymakers with advanced capabilities to predict urban growth and assess energy needs, fostering sustainable development in regions such as Africa, IBM said in a statement.
Open Building Insights (OBI), a platform hosted on IBM Cloud, offers an interactive map consolidating building-specific data such as location, height, footprint, and usage type. Developed in collaboration with SEforALL, the platform incorporates AI models to analyse and categorise buildings as residential or non-residential, a critical factor for planning energy infrastructure.
“The Open Building Insights platform empowers stakeholders to make informed decisions about sustainable urban development by visually consolidating building-specific data in an accessible format,” IBM said.
The tool integrates datasets from multiple sources, including the German Aerospace Centre (DLR) for building height estimation and Open Energy Maps for electricity consumption. IBM’s proprietary AI model, built on its watsonx AI platform, enhances this data by determining building usage through analysis of features like roof images and geographical data.
Currently, OBI covers all of Kenya and parts of India, with practical applications underway. Insights derived from OBI have supported energy planning initiatives in Makueni County, Kenya, projected to benefit over 1,1 million residents by 2030.
The Modelling Urban Growth (MUG) tool is an open-source AI model designed to predict urban expansion. Using a combination of historical satellite imagery, geographic data, demographic trends, and road layout information, the model generates time-series predictions to identify future urbanisation patterns.
"Modelling Urban Growth enables policymakers to predict where cities will grow, prioritising communities with urgent infrastructure needs such as electrification," IBM said.
Available on GitHub, MUG enables users to re-train the model with their own datasets, making it adaptable for global applications. The tool is particularly focused on mapping infrastructure needs in developing regions, aiding decision-makers in prioritising communities requiring electrification and other essential services.
Both tools were developed through IBM’s Sustainability Accelerator programme, which facilitates collaborations to address pressing sustainability challenges.
IBM plans to expand OBI's coverage in India and explore integrating MUG into the platform, aiming to provide a unified tool for urban growth prediction and infrastructure planning.
“These tools highlight how technology can drive meaningful change, empowering governments and communities to address rapid urbanisation and energy access challenges effectively,” said John Matogo, IBM’s Corporate Social Responsibility Leader for Africa and the Middle East.
