“Collaborating with SEforALL through our IBM Sustainability Accelerator programme helped us unlock innovation and work more closely in communities to tackle some of our biggest challenges, especially around energy and sustainable urban development,” said John Matogo, corporate social responsibility leader for Africa and the Middle East at IBM.
Damilola Ogunbiyi, CEO and special representative of the UN Secretary-General for SEforALL, and co-chair of UN-Energy, said: “We believe that integrating AI in the energy sector planning and evidence, especially for developing countries, will go a long way in designing comprehensive solutions for many of the developmental challenges currently facing the Global South and its people. The Open Building Insights Tool, which SEforALL has developed in collaboration with IBM, will help energy planners overcome critical data gap challenges to inform energy access and energy transition interventions and better deliver results for those most in need.”
Open Building Insights
Open Building Insights (OBI) is an interactive online platform running on IBM Cloud. OBI visually consolidates data in a map, providing information related to buildings in countries addressing urban planning challenges such as building location, height, footprint area and usage type. This visual consolidation makes AI models’ output easy to understand for non-technical users and empowers stakeholders to make informed decisions about sustainable urban development.
OBI’s interactive map consolidates models created by the German Aerospace Centre, DLR, which estimates buildings’ heights, by open energy maps, and provides information about electricity status and consumption and by IBM.
The brand-new AI model runs on IBM Cloud and was built using the IBM watsonx AI and data platform. It uses building-specific data – including its footprint, number of floors, roof image, location and other map data – to determine whether a building is residential or non-residential. This categorisation is key to determining the energy needs of a certain urban area. OBI is available for free to the public.
Modelling Urban Growth (MUG) is an open-source AI model designed to predict where cities will grow. The model is trained on, and validates, historical data from satellite images. Geographic data, such as slope and elevation, demographic data and structural data, such as road layout, are combined into a time series.
MUG helps users to map future urbanisation and associated infrastructure needs, enabling decision makers to prioritise communities and developing regions that need support for issues like electrification and energy services. MUG is an AI Alliance project, which is publicly available and open-source on GitHub.
