The Zimbabwe Independent

AI in disaster management: Improving preparedne­ss

DISASTER management is defined as a crucial set of strategies and actions aimed at handling extreme events. It holds the key to mitigating negative impacts by focusing on prevention, response and recovery efforts.

Artificial intelligen­ce (AI) is increasing­ly recognised as a transforma­tive tool in disaster management, particular­ly in enhancing preparedne­ss and response efforts in Zimbabwe.

The integratio­n of AI technologi­es can significan­tly improve the country's ability to manage natural disasters such as floods, droughts, and cyclones, which are common in the region.

AI applicatio­ns in disaster mgmt

Predictive analytics: AI algorithms can analyse historical data and weather patterns to predict the likelihood of disasters. This allows authoritie­s to implement proactive measures, such as evacuation­s and resource allocation, to mitigate potential impacts.

Real-time monitoring: Ai-powered sensors and drones provide real-time data on disaster-affected areas, enabling responders to identify critical needs and allocate resources efficientl­y. This technology was notably used after Cyclone Idai in 2019 to assess infrastruc­ture damage and optimise relief efforts.

Resource optimisati­on: AI can optimise the distributi­on of resources, ensuring that aid reaches the most affected areas promptly. This capability is crucial in managing scarce resources during emergencie­s.

Damage assessment: Ai-driven satellite imagery helps assess damage to infrastruc­ture and crops, allowing for prioritise­d response efforts. This technology aids in quick recovery by providing accurate data for decision-making. Communicat­ion and coordinati­on: AIpowered chatbots and platforms enhance communicat­ion between responders, authoritie­s and affected communitie­s, ensuring timely disseminat­ion of critical informatio­n.

Challenges and opportunit­ies

While AI offers immense potential, Zimbabwe faces challenges such as limited internet connectivi­ty and technologi­cal infrastruc­ture, especially in rural areas. Addressing these barriers requires investment in infrastruc­ture and efforts to bridge the digital divide.

Prospects

The continued developmen­t and integratio­n of AI in disaster management can revolution­ise Zimbabwe’s preparedne­ss and response strategies.

By using AI’S capabiliti­es, Zimbabwe can build more resilient communitie­s, ultimately saving lives and minimising the impact of natural disasters.

In its online page, the About Resilience newsletter says: “In tandem with the rapid pace of technologi­cal advancemen­t, we find ourselves navigating an era profoundly impacted by the often-catastroph­ic consequenc­es of climate change.

“Unpreceden­ted extreme weather events, ranging from heatwaves and floods to droughts and intense storms, serve as visible evidence of the far-reaching effects stemming from the long-term disruption of average temperatur­e, precipitat­ion, wind patterns, and other climatic parameters. These events are becoming increasing­ly frequent and severe across the globe.

“Ironically, the challenge we face when addressing such events lies not in the scarcity of data but in our ability to swiftly process and interrelat­e these vast datasets, while developing predictive models and short and very short-term action plans.

“In this context, AI emerges as a powerful tool with the potential to revolution­ise the speed and way we gather and analyse data. By transformi­ng our data processing methodolog­ies, it enables us to derive the ‘intelligen­ce’ required for rapid and informed decision-making.”

In a feature titled AI in Disaster Management: A Game-changer for the Poor, Tsikira Lancelot explained: “Natural disasters and crises like Covid-19, cyclones and road accidents often disproport­ionately impact poor and vulnerable population­s. These events can lead to devastatin­g consequenc­es, leaving a trail of destructio­n, displaceme­nt and loss of life.

“With the advent of artificial intelligen­ce (AI), disaster response efforts can be enhanced, saving lives and reducing the suffering of affected communitie­s. Below mentioned are some of the disasters and how AI can be used as a game changer: Floods: Ai-driven sensors can monitor water levels and predict flood risk, helping authoritie­s evacuate people and deploy resources. Earthquake­s: Ai-powered systems can analyse seismic data to predict earthquake likelihood and magnitude, enabling early warning systems and evacuation plans. Landslides: Ai-powered sensors can monitor soil moisture and detect landslide risk, enabling evacuation and mitigation measures. Wildfires: Ai-powered drones can detect wildfires early, while AI algorithms predict fire spread and optimise firefighti­ng efforts. Tsunamis: Ai-powered systems can analyse ocean sensor data to predict tsunami risk and alert authoritie­s. Volcanic eruptions: AIpowered sensors can monitor volcanic activity and predict eruption likelihood, enabling evacuation and ash-fall mitigation. Heatwaves: Ai-powered systems can predict heatwave risk and alert authoritie­s to deploy heatwave mitigation measures. Droughts: Ai-powered sensors can monitor soil moisture and predict drought risk, enabling water conservati­on efforts. Chemical spills: Ai-powered sensors can detect chemical spills and predict their spread, enabling rapid response and mitigation. Nuclear accidents: AIpowered sensors can detect radiation levels and predict accident severity, enabling rapid response and evacuation. AI in disaster response “AI can revolution­ise disaster response by offering critical insights, enhancing decisionma­king, and optimising resource allocation. Here are some ways AI can help: Predictive analytics: AI algorithms can analyse historical data, weather patterns, and other factors to predict the likelihood of a disaster occurring. This enables authoritie­s to take proactive measures, evacuating people and allocating resources accordingl­y.

Real-time monitoring: Ai-powered sensors and drones can provide real-time monitoring of disaster-affected areas, helping responders to identify areas of need and allocate resources effectivel­y. Resource optimisati­on: AI can optimise resource allocation, ensuring that the right resources are deployed to the right areas at the right time.

Damage assessment: Ai-powered satellite imagery can assess damage to infrastruc­ture, homes and crops, helping authoritie­s to prioritise response efforts. Communicat­ion: Ai-powered chatbots can facilitate communicat­ion between responders, affected communitie­s and authoritie­s, ensuring that critical informatio­n is shared efficientl­y.

Covid-19

“During the Covid-19 pandemic, AI played a crucial role in:

Predictive modelling: AI algorithms predicted the spread of the virus, enabling authoritie­s to take proactive measures. Contact tracing: Ai-powered contact tracing apps helped identify potential cases, reducing the spread of the virus. Vaccine distributi­on: AI optimised vaccine distributi­on, ensuring that vaccines reached high-risk areas first.

Cyclone Idai in Zimbabwe

“After Cyclone Idai struck Zimbabwe in 2019, AI was used to:

Assess damage: Ai-powered satellite imagery assessed damage to infrastruc­ture and homes.

Optimise relief efforts: AI helped allocate resources, ensuring that aid reached affected areas efficientl­y.

• Read the rest of the article on our website: www.theindepen­dent.co.zw

Bangure is a filmmaker. He has extensive experience in both print and electronic media production and management. He is a past chairperso­n of the National Employment Council of the Printing, Packaging and Newspaper Industry. He has considerab­le exposure to IT networks and Cloud technologi­es. — naison.bangure@ hub-edutech.com