Kafaat for Reconstruction was the successful winner of the joint Aubrey-Barker Fund and FIG Foundation Research Grant from 2025-2026, receiving £20,000 towards their project “Piloting AI-Assisted Community Mapping for Housing Recovery in Harasta, Syria.

This innovative project addresses the complex challenges of urban recovery in Harasta, Syria, a city profoundly impacted by conflict and displacement. As citizens return and rebuilding commences, municipality governments have been overwhelmed with the everyday decisions needed to achieve a safe and sustainable return home for displaced families. That’s where AI comes in – to assist in transforming data into information for municipality staff, and bridge the large scale data needs with the lived experience of local residents.

The innovation: from data to action

Whilst traditional surveying often relies on top-down processes – be it expert led data capture or satellite imagery analysis – this pilot project draws on participatory and community-led processes to address the ‘expert gap’ and ensure citizens voices are heard. This participatory structure includes:

• Local training of more than 30 community members and municipal staff in digital surveying and geographic information system tools to particularly assist in ground-truthing and field validation.
• Integration of an ‘AI intelligent assistant’ within existing municipal workflows, to ensure the solution adopted is usable and sustainable. Working with staff, rather than replacing.
• Sustainability at the core. The grant supports upgrading municipal server infrastructure, ensuring the city has the long-term capacity to maintain and update its recovery database.

Artificial intelligence, combined with participatory mapping leads to technical outputs such as:

• AI-Driven Analysis: The project has sought to test deep learning architectures (such as CNNs and U-Net) to classify structural damage from satellite imagery and verified by field-collected data.
• The “Smart Assistant” Interface: In a significant technical evolution, the Kafaat- developed system features a Natural Language Interface in Arabic. This allows municipal planners—even those without GIS expertise—to ask conversational questions like, “Which area should we prioritize for repair based on inhabited buildings and water access?”.
• Knowledge Graphs: Using Neo4j technology, the AI moves beyond identifying where damage is to explaining why certain interventions are needed, connecting infrastructure status with social needs.

By bridging advanced technology with the lived experience of local residents, Kafaat for Reconstruction is demonstrating a replicable model for the how the surveying profession can evolve to deliver technical rigour alongside community leadership and dignity.