In an era where climate change poses an increasing threat to communities worldwide, a life-changing initiative is taking shape in South Africa.
An early warning system for extreme weather events in the country is being developed to empower vulnerable communities and healthcare systems in response to the devastating impacts of flooding and associated health risks.
The WEATHER project - Warning system for Extreme weather events, Awareness Technology for Healthcare, Equitable delivery, and Resilience - is a collaboration between the University of Portsmouth (UoP), the University of the West of Scotland (UWS), the University of KwaZulu-Natal (UKZN), and the Royal College of Surgeons in Ireland (RCSI).
It has been awarded a pivotal grant of more than £2 million from the National Institute for Health and Care Research (NIHR) to develop a comprehensive warning system using cutting-edge technology and Artificial Intelligence.
The AI-powered weather prediction tool aims to help the communities already living with the effects of a changing climate by providing early warnings for extreme weather events, enabling better disaster preparedness, and protecting livelihoods.
Professor David Ndzi, Professor of Wireless Communication Systems and Head of the School of Electrical and Mechanical Engineering
Professor David Ndzi , Professor of Wireless Communication Systems and Head of the School of Electrical and Mechanical Engineering , said: "WEATHER embodies the power of collaboration between technology and human expertise. AI tools amplify our analysis and prediction capabilities, but it's the partnership with local communities that will truly optimise the system and ensure it makes a lasting difference. The AI-powered weather prediction tool aims to help the communities already living with the effects of a changing climate by providing early warnings for extreme weather events, enabling better disaster preparedness, and protecting livelihoods."
The research team will focus on two vulnerable districts in KwaZulu-Natal, eThekwini and Ugu, collaborating closely with local communities and healthcare providers throughout the process. This ensures the developed system is culturally sensitive, context-specific, and addresses the unique needs of the target population.
The joint Principal Investigators (PI's) on the project are Professor Mary Lynch , from the University of South Wales and the Royal College of Surgeons in Ireland, and Professor Saloshni Naidoo from the University of KwaZulu-Natal.
Professor Naidoo said: "A successful WEATHER project would not only benefit our communities and strengthen the health system but also serve as a valuable model for other regions facing similar climate-related risks, potentially contributing to broader improvements across South Africa and in other low- and middle-income countries."
Using cutting-edge technology and Artificial Intelligence (AI), the WEATHER project will develop a comprehensive warning system tailored to the needs of affected communities.
Geospatial technologies will collate weather and climate data while AI algorithms will analyse weather, climate and health data to identify patterns and trends which allow for more accurate predictions of flooding and associated health risks.
Additionally, AI-powered tools will continuously monitor and assess flood risks in real-time, enabling swift interventions to minimise disease outbreaks. Warnings will be shared through a mobile app providing more detailed information, maps, and resources tailored to specific locations and needs and through SMS text messages, ensuring widespread reach even in areas with limited internet access.
The grant from NIHR's Research on Interventions for Global Health Transformation (RIGHT) programme is a crucial step towards building a safer future for vulnerable communities.
The multidisciplinary team within the WEATHER project combined with innovative approaches, represents a significant step forward in addressing the challenges posed by extreme weather events in vulnerable communities globally. The project's success will pave the way for replicating and adapting the system in other regions facing similar climate-related risks.
