Natural disasters are increasing due to climate change. An estimated 160 million people yearly are affected by hurricanes, fires, floods and other natural disasters. It is expected that the situation will get worse with time as the frequency of the events would also grow with the effect of climate change. The occurrence of natural disasters has increased four times as compared to 1971.
Traditional or manual method to assess and provide emergency aid requires a lot of effort and time. It includes rescue operations as well as immediate relief for the affected population in form of food, water, temporary shelter and medical care. Moreover, providing humanitarian assistance in an urban area is more difficult than in rural areas due to its large and complex infrastructure.
Artificial Intelligence can reduce damage by providing emergency aid more effectively and efficiently. It helps in the provision of delivery of aid and other relief activities in affected areas. It can provide resilience against natural disasters by predicting damage, geo-tagging damage for relief workers, planning optimal delivery routes, and estimating the funding plan. It can be a cost-effective solution for the countries which are on the verge of climate risk. The blog will briefly explain the need for Artificial Intelligent policy for developing countries and the way forward.
Disaster Management and Artificial Intelligence (AI)
Artificial Intelligence provides facilities like processing observational data and forecast model output post-processing. It can also be used to predict the occurrence of flash floods. It is imperative to have a dense network of sensors to monitor environmental changes. With AI, disaster resilience efforts will look different from today. Researchers can gather data to predict how many people will be displaced from their homes and where the government can provide them with alternative shelters due to disasters. Such interpretation will help relief workers to identify how much aid will be needed (food, water, medical care) and where to send it. AI algorithms can assess the flooding area, damaged roads and buildings through satellite images and weather forecasts which help workers to distribute aid more effectively and identify those people who are still in danger.
After a natural disaster, it is difficult for the government to assess the damage caused, and it may take months before an actual on-ground picture of the scenario is obtained. This leaves affected people vulnerable for a long time. However, AI can pace the recovery process and identify climate change patterns faster. It can greatly reduce the time people remain without resources and can also help target relief efforts to the most affected areas.
Predicting and Classifying the Damage
Artificial Intelligence can predict areas which are at risk by using satellite imagery and drone technology. A greater number of data sources will also make the algorithm predict with greater accuracy. A researcher in Japan tested his prediction for a flood after Typhoon Hagibis. The collected data led to an accurate prediction of the flood that occurred in Japan. On the other hand, European Commission’s Joint Research Committee (JRC) uses AI to monitor the weather and assess food security risks. A ‘Climate Service’ system has also been introduced to reduce disasters and agriculture-related risks. The AI system can provide information about major and minor damaged infrastructure.
Geotagging Damage for Relief Workers
It is a difficult and time taking process for the relief workers to manually assess affected areas for damage and relief efforts. However, if AI is used, the whole process can be made faster and more reliable. Damaged buildings and land routes can be geo-tagged to help relief workers identify the vulnerable area and allocate resources optimally for faster response and recovery. This mechanism was used to provide support to allocate damaged roads during Hurricane Harvey near Sugar Land with 88.8% accuracy and identify damaged buildings in the Northern California Santa Rosa Fires with 81.1% accuracy.
Planning Optimal Delivery Routes
Natural disasters often lead to the blocking of travel routes and relief efforts are usually delayed due to it. This destruction creates hurdles for relief workers to provide emergency aid to the affected people. However, by using Artificial intelligence technology, optimal route planning based on the damaged assessment maps can be done for faster delivery of aid in the post-disaster scenario.
Estimate the Funding Requirement
Assessing the actual on-ground damages caused by natural disasters can be a long and arduous task. Furthermore, manual costing involves a lot of human errors and can be susceptible to corruption and over or under-representation. Using AI systems to assess the damage and the overall cost associated with it can greatly reduce the financing burden of the government and help redevelop communities faster. Modern AI systems can measure the food and water, shelter, healthcare and monetary aid requirements for governments effectively.
Benefits of Artificial Intelligence (AI) for Developing Countries
Artificial Intelligence has the ability to help achieve 79% of the targets set under the sustainable development goals. The need for highly complex infrastructure for energy, transportation, health care, and education has to be fulfilled with sustainable and adaptable economies. The process can take multiple decades, however; artificial intelligence technology has the potential to overcome existing gaps in infrastructure development and can provide a more sustainable framework for the development of future infrastructure. For instance, Azuri Technologies developed a solar-powered pay-as-you-go model for rural homes in 12 countries across East and West Africa by using AI. Similarly, United Nations has used data from AI to provide emergency aid and disaster responses in Nepal during the earth quack of 2015. Artificial Intelligence for Disaster Response (AIDR) was able to identify the actual and potential victims of the disasters. The AI created digital maps and highlighted areas which needed more assistance. It was able to identify humanitarian aid needs automatically and sort any given data into different categories, such as infrastructure damage, urgent needs and response efforts. Based on this categorisation and captured data, available responders could quickly focus their efforts and supplies on the right places. This shows that AI has a cost-effective solution in case of disasters and it will be helpful for developing countries that have a limited budget.
Why Pakistan Needs AI for Natural Disaster Management
Climate change is affecting the environment and economy of Pakistan. Climate changes are anticipated to impact all sectors of the economy such as reduced agricultural productivity, increased variability of water, seawater incursion, increased coastal erosion, and increased frequency of extreme climate events. As per the German Watch, Pakistan has been ranked in the top ten most affected countries by climate change in the last 20 years.
As Pakistan records the worst floods since 2010 with rainfall crossing 390mm this season, which is 3 times higher than the national 30-year average of 135mm. The estimated impact of loss to the economy is around PKR 1.2trn (1.48% of GDP). It is predicted that GDP growth will shrink to 2.49% in FY23 and the current account deficit to grow by USD 1.98bn. Inflation will increase up to 19.7% in FY23. More than 12,00 people have died and 15,75 are injured.
In Pakistan, more than 150 extreme weather events have occurred and the country has lost 0.53 per cent per unit of GDP. It was predicted that the temperature in Pakistan will increase up to 4.38oC by 2080 which reflect that more event related to climate change will occur. The extreme weather events will be increased in intensity and frequency also. In these circumstances, Pakistan needs to invest in a disaster preparedness strategy to save its budget which can be invested in development projects. It was estimated by United Nations Office that every $1 invested in risk reduction and prevention can save up to $15 in post-disaster recovery, whilst every US$1 invested in making infrastructure disaster-resilient saves US$4 in reconstruction. To be prepared for the natural disaster Pakistan needs a framework that can predict the forthcoming risk, and AI has the ability to do so. Thus, to mitigate the impact of disaster and make infrastructure resilient against risk, the government has to revisit and upgrade its strategies.
Way Forward
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Pakistan must develop intelligent policies to integrate artificial intelligence systems in its weather prediction and disaster forecasting departments at the national and provincial levels.
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Using AI technology can greatly reduce the impact of natural disasters by forecasting their place of occurrence and the cost of damage caused. The technology should, therefore, be used for the urban planning of existing and future cities.
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Higher education institutions should develop courses and work in collaboration with the government to provide the human resource required for this exercise.
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The national disaster management authority should seek effective measures for the implementation of such programs.
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To implement AI policy government must focus on an integrated framework and coordinated action among the governmental department.
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Government should include the private sector to finance the Artificial Intelligence infrastructure.
https://news.mit.edu/2020/lidar-and-ai-road-status-clears-after-disaster-0415
https://www.preventionweb.net/news/artificial-intelligence-disaster-management-thats-how-we-stand
https://developer.nvidia.com/blog/ai-helps-detect-disaster-damage-from-satellite-imagery/
https://journals.umt.edu.pk/index.php/OTR/article/view/2594/935
https://www.sciencedirect.com/science/article/pii/S1040619020301561
https://borgenproject.org/artificial-intelligence-is-helping-developing-countries/
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