Harnessing technology for disaster preparedness

THE whole northwestern region of India is bearing the brunt of nature's fury, suffering a series of unprecedented cloudbursts, landslides and floods over the past few weeks. Although such natural disasters have occurred before, the devastation, loss of human lives and livestock, especially in the countryside, have left haunting images of homes and villages reduced to ruins. The situation in the urban areas and metros has not been any better.The cloudbursts and landslides were caused by an unusual combination of meteorological factors, including intensified western disturbances, low-pressure systems and increased monsoon moisture from the Arabian Sea and the Bay of Bengal.India is one of the world's most disaster-prone regions, both natural and man-made. Floods, droughts, cyclones, landslides and earthquakes, coupled with other disasters, compound the country's troubles. On an average, about 60 million people in India suffer the adverse effects of natural calamities, claiming about 3,500 lives annually.The severity of the problem continues to escalate as a result of climate change and unchecked urban expansion.The primary responsibility to manage disasters is that of the state government, with the Centre providing additional resources, depending on the severity of the calamity. Undoubtedly, a lot more needs to be done at all levels to mitigate the effects of disasters on the population.Lives can be saved, damage to property reduced and recovery from disaster accelerated by taking action before floods rise, fires rage, pipes rupture, the ground shakes or contamination spreads.Besides other measures, technology can be harnessed extensively to effectively deal with these catastrophes. At present, it is used in a limited manner for forecasting, early warning and supply of essentials by drones to marooned people.Artificial intelligence (AI) is emerging as a game-changer in disaster risk reduction by enhancing data collection, analysis and response across various phases of the disaster management cycle covering prevention, preparation, emergency response, rehabilitation and reconstruction.AI systems can analyse such vast datasets as satellite imagery, weather data and sensor feeds to detect patterns and issue early warnings for disasters like earthquakes, floods and hurricanes before they strike. These predictive models give communities and authorities vital time to evacuate, reinforce infrastructure and minimise casualties.It is instructive to study how Japan, a country highly prone to disasters, deals with them. Recently, it released an AI-generated simulation of the eruption of Mount Fuji, located close to Tokyo. Mount Fuji last erupted in 1707, but is still active and overdue by geological standards.The video shows ash clouds darkening Tokyo within two hours of an eruption. A real eruption could cause power outages, food shortages and shut down transport. The simulation warns residents to stock essentials like water, food and flashlights.It is part of a government effort to raise awareness, not panic, as some citizens found the video unsettling, while others praised its clarity and urgency.Similarly, during the emergency phase of the disaster, AI-powered tools can process live inputs from sensors, drones and social media to provide real-time situational awareness. This can enable the authorities to respond faster and deploy resources, such as emergency teams, medical supplies and rescue equipment, where they are needed most urgentlyMedia reports based on data from the Punjab Government’s Department of Revenue, Rehabilitation and Disaster Management suggest that there are only 257 boats for 23 districts to respond to emergency situations, but only 114 engines. Motorised boats are vital to negotiate the fast currents of swollen rivers to evacuate marooned people and render succour to areas cut off by raging water. Even these few available boats could have been deployed optimally as per the severity of flood waters in various areas.In Iwate Prefecture, Japan, initiatives are underway to bolster disaster preparedness using AI technologies, spurred by lessons from the devastating 2011 Great East Japan Earthquake.Rikuzentakata city has pioneered an AI-driven system to enhance evacuation procedures. This system automatically contacts registered residents during emergencies, querying their evacuation status and condition via telephone. Responses are converted into text and relayed to emergency centres, addressing challenges in disseminating timely information, particularly to elderly and non-social media users.Effective disaster risk reduction relies on the combination of advanced warning systems and responsible land management to save lives and strengthen community resilience.AI can play a transformative role in minimising destruction from natural disasters by improving prediction, preparedness, rapid response and recovery operations.With AI, disaster management becomes far more proactive, accurate and adaptable — significantly reducing impact on people, property and the economy.Countries like Japan have stressed this reality by issuing strong warnings about major threats, such as the Nankai earthquake this year, with an 80 per cent chance in 30 years.Using AI to simulate even the worst-case disaster scenarios is not alarmism — it's an essential part of effective preparedness and risk management. When a disaster strikes, it's already too late to prepare.Lt Gen SK Saini (retd) is former Vice-Chief of Army staff.

Harnessing technology for disaster preparedness

Lt Gen SK Saini retd

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