An AI-based model that not only helps identify areas vulnerable to floods but also predicts crop yields to prevent drought and ensure food security…
An app to battle uncertainty in flood-prone areas. An initiative using high-resolution spatial images and complex mathematical calculations for accurate weather forecasts to design better disaster responses.
The idea of AI-aided disaster management is indeed a reality.
Disasters of all kinds, natural and manmade — hurricanes, epidemics, bridge and building collapse, wildfires, and the like — seem to be getting more frequent and more severe across the globe. According to the WMO’s (World Meteorological Organization) 2020 State of Climate Services Report, the number of recorded disasters has increased nearly 5 times in the last 50 years, with the resulting economic losses having increased 7 times. In such situations, crisis response is critical.
Generative AI (artificial intelligence) has emerged as a transformative force that could potentially transform disaster management end-to-end while also easing the pressure on personnel.
Disaster Assessment and Prediction: A Paradigm Shift
In the past, disaster management has primarily focused on post-disaster relief efforts and response. However, there’s a crucial shift taking place, with AI helping disaster management become more proactive than reactive.
One of the biggest instances is the state of Uttar Pradesh, which is particularly vulnerable to natural disasters like heat waves, droughts, and floods. It’s taking a proactive approach to mitigate the impact of these disasters with the establishment of the CRO (Climate Resilience Observatory), which is leveraging advanced technology like ML (machine learning) and AI to collect and analyse data, enabling timely interventions and predicting potential disasters.
At the ongoing Maha Kumbh Mela in Prayagraj, India, around 250 of the nearly 3,000 close-circuit cameras monitoring the massive ground have been feeding information to the ICCC (Integrated Control and Command Center. These have provided authorities with real-time and unique insights into factors such as vehicle parking statuses, people entering the Mela premises every minute, crowd density at the bathing ghats, and even crowd accumulation at key places. The objective? To be able to issue alerts based on the pre-set danger thresholds by analysing the data so that they’re better equipped to avert the repetition of the stampede tragedy that occurred.
Another compelling application of AI in disaster management is happening in seismology to help predict earthquakes, one of humankind’s most devastating natural disasters. For instance, the Stanford researchers-developed AI model STEDS (Stanford Earthquake Detecting System) helps identify oft-overlooked minor quakes that offer crucial data about the seismic activity in the region. The idea is to set a framework that could aid in forecasting more destructive and larger earthquakes.
In other parts of the world, AI is also being used to alert the public more efficiently. In 2023, AI translation company Lilt partnered with the National Weather Service to deliver forecasts in Spanish and simplified Chinese, the two most-spoken languages in the United States after English. It supposedly reduced the hurricane warning translation times from 1 hour to 10 minutes.
Disaster Prevention
AI has also emerged as a crucial ally in preventing disasters by observing a wide range of elements, from changes in geological formations to subtle shifts in weather to anticipate potential disasters. This has greatly helped in implementing proactive strategies, just like amping up the close-circuit AI cameras at the Maha Kumbh.
One of the most compelling instances of the same is Google’s flood forecasting system, which has been currently deployed in India and Bangladesh.
This system will be particularly helpful in India, where more than 20% of worldwide flood-related fatalities take place. So, what exactly does this system do? It harnesses the power of machine learning and combines it with computational hydrology for predicting the location and severity of floods. Factors such as historical flood and terrain data are taken into account to simulate exactly how much water will flow across the land.
Finally, the system generates maps and alerts for dissemination to local authorities and the public, offering them crucial time to prepare and respond.
Another place in India using AI to combat flood situations is Assam’s Cachar district administration and its RAHAT app (Rapid Action for Humanitarian Assistance in Tragedies). The AI-based app will play a critical role in sharing important information for early warning dissemination, evacuation, search and rescue, and supplying essential items to flood-torn areas. The idea is to establish robust connectivity between the government, security forces, and the people during flood emergencies.
Hopefully, the recently proposed budget upgradation of INR 10,000 crore for the NMM (National Monsoon Mission) jumpstarts the IMD (India Meteorological Department) to improve forecasting and predict extreme weather events.
The Way Ahead: Navigating the Storm
While traditional methods of disaster prevention, like satellites, provide valuable information, throwing AI into the mix in disaster management can greatly enhance them. With AI revolutionising weather prediction, reducing economic losses, and saving lives by providing more timely and accurate forecasts, AI can be leveraged for designing better early warning systems, mitigating the impact of future calamities, and building safer, more resilient regions with safer futures.
In case you missed:
- Can we fight climate change with AI?
- Can We Really Opt Out of Artificial Intelligence Online?
- Wildlife Conservation: Is AI Changing It For The Better?
- Safe Delivery App and the NeMa Smart Bot: How AI Is Aiding Safer Births Amidst Limited Resources
- The Best Multi-Cloud Identity Management Practices
- Neural Networks vs AI – Decoding the Differences
- Colocation Data Centres: An Overview
- AI Firewalls and How They Protect Your Data
- A Beginner’s Guide to Cryptocurrency Trading in India – Part 1
- Star Topology – Benefits and Challenges
