Recent N/LAB Projects

Automated Road Quality Surveys: Superior and Cost Effective

In collaboration with DFiD and the Department of Roads (DoR) Zanzibar, N/LAB is investigating methods combining remote sensing (drone/satellite imagery) and applied machine learning methods to automate the assessment of low volume road conditions. Traditionally […]

Generating Geo-demographic Data from CDR Data: Mobility

Understanding mobility at a population level provides a key role in urban planning. Traditionally undertaken by transport surveys, a key outcome is city wide Origin-Destination (OD) Matrices. While providing known utility, these traditional approaches are […]

Big Data for Resilience – Flooding in Dar es Salaam

Dar es Salaam suffers from biannual flooding caused by various factors including climate change and rapid unplanned urban growth. Receiving a ESRC-NERC-DFID grant for “Big Data for Flood Resilience in East Africa”, this project investigates […]

Transport – Road Conditions

Leveraging recent deep learning advances with high resolution drone imagery, the team has developed state-of-the-art techniques for the automatic detection of buildings and roads from aerial imagery. N/LAB is now focusing on the extension of […]

Community Mapping

Maps are crucial in emerging countries to make decisions, but often do not exist. Community mapping is a participatory process where community members map their neighbourhoods, making maps openly available in the process. In emerging […]

Refined Limit on the Predictability of Human Movement

It has been recently claimed that human movement is ‘highly predictable’ upper bound of 93% predictability shown. However, knowing an upper bound is only useful if it is relatively tight, i.e. it is close to the […]