Published on Data Blog

A SMART solution: How we helped build a low-cost flood alert and water monitoring system in African cities

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Many of us in the world are fortunate enough to live with a plethora of technologies at our fingertips. High-tech devices are part of our daily routine and we use them habitually, often without thinking much about their innovative aspects. Up-to-the-minute weather forecast apps are one such convenience that we take for granted.

In high-income countries, rainfall and flood monitoring are based on expensive and high-maintenance weather observation systems provided by state-of-the-art weather radar and modeling. However, low-income countries in Africa cannot afford these. To address the gap, the World Bank’s Trust Fund for Statistical Capacity Building (TFSCB) supported a project that aimed to accurately measure rainfall with a low-cost technique based on the cellular network signal attenuation (signal weakening during the rain) in Cameroon. In partnership with the Global Partnership for Sustainable Development Data, the Development Data Group at the World Bank funded the project’s operations and monitoring and evaluation.

SMART (Smart water Monitoring and Alert with Rainfall measurement from Telecommunication networks), developed by the French organization, National Research Institute for Development (IRD), addresses data gaps in quality climate, rainfall and water data, and helps local and sub‐regional authorities to improve urban flood and water management on a sustainable basis.

The main objective of the SMART project was to test operationalization of a mobile-data driven system to better monitor extreme rainfall events that lead to flooding and to issue real-time alerts to African cities.

SMART model
Figure 1. Illustration of the SMART project basis – the Rain Cell method: radiowaves between the RF towers from mobile phone networks are attenuated by rainfall.

The technological approach in SMART is a three-stage processing and visualizing of the data:

  1. collection and provision through a dedicated server of the radio signals transmitted/received levels over the mobile phone networks (with 15-minute time steps);
  2. open source software for transformation of the signal level into rainfall intensities and 2D maps; and
  3. integration of rain maps into a visualization tool and assessment of possible inclusion in flood model and visualization of flood risk maps.

Technical outcomes from the project included real time provision of high-resolution rain maps in two major African cities (Yaounde and Douala, Cameroon) and demonstration of potential use for flood early warning systems (EWS) and alerts. Capacity-building activities included building awareness and acceptance within telecom operators to insure the raw data flux; presenting the SMART novel concept for rainfall monitoring and flood alerts to authorities and other local decision-makers; and informing international agencies (World Meteorological Organization, etc.) to insure operationalization and scaling.

Figure 2. Illustration of the high-resolution rain maps in Douala as they were displayed in real time on the SMART Web server (

Lessons learned from the project:

  • Beyond the technical achievement, one challenge of the project was to build awareness among stakeholders and users to help develop the concept beyond the initial demonstration.
  • One major benefit from the SMART project was that it helped attenuate some of the major effects of climate risks on populations (e.g., floods related to extreme rainfall events) without the need for massive investment because of being based on existing infrastructure.
  • As a new and innovative technique, awareness and acceptability will be needed for the concept to be scaled up and operationalized for wider benefit.
  • The fact that the required data are not sensitive—i.e., no access to any personal data is required—should be conveyed in order to build trusting relationships with additional operators and companies.

group meeeting
Figure 3. Meeting at the Orange telecom headquarters in Douala to present the SMART project.


The Trust Fund for Statistical Capacity Building (TFSCB) is supported by the United Kingdom’s Department for International Development, the Government of Korea, and the Department of Foreign Affairs and Trade of Ireland.


Sun Hwa Song

Statistical Analyst

David Mariano

Communications Consultant, Infrastructure Practice Group, World Bank

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