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AI and IoT: The new response to natural disasters

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By Sukanya Mandal, Senior IEEE Member

As we strive towards a more sustainable environment, we are witnessing continuous efforts towards harnessing immersive technologies to minimize risks and adversities of natural disasters. Over time, the world has been a testimony of many natural disasters owing to the ever-changing environmental situations. It has led to a spurt of natural disasters that have global impact and require immediate redressal.

The advent of emerging technologies has boosted the morale of countries and governments, who are converging to explore damage relief measures for a sustainable future. Technologies, especially AI and IoT have not only enabled us to accelerate our aid response to any natural calamity but also have improved disaster predictions.

Disaster Management and IoT

IoT systems are expected to successfully deal with disaster management through accurate predictions, pre-preparedness and early warning signs. Deployment of advanced IoT solutions will help us broaden our reach in remote areas and will assess the damage and further repair it – within no time. IoT will not only help mankind use resources proficiently but will also help react swiftly in order to save millions of lives.

India has witnessed tangible results with the help of IoT, states like Odisha face deadly floods and cyclones, washing away villages and destroying the state infrastructure, on a yearly basis. But with the help of an early alarm system, the state has managed to reduce the fatalities and impact of such natural disasters. In fact, Odisha became the first Indian state to implement the Early Warning Dissemination system that covers 1000+ villages. This fail-proof technology sends location-based alerts across the region and provides a communication ecosystem that helps reach the remotest areas and gives a heads-up in advance. Such measures have successfully added to the merits of IoT ecosystem.

AI can accelerate disaster response

One step ahead of IoT stands AI -smart technology, which has enabled accurate and speedy solutions. If harnessed properly, the technology has the potential of predicting, preventing and providing response faster than ever.

AI data setups are trained to predict seismic data to analyze the patterns of earthquake occurrences, rainfall records and monitor flooding, measure the intensity of hurricanes and read the geological data to understand volcanic eruptions, such systems can reduce the catastrophic impact of natural disasters.

Last year, Google’s Pilot project to monitor flood in India with the help of AI, was a successful one – it was a Patna project. They were able to predict floods and the regions that it would be affected due to the natural disaster with an accuracy of over 90%. It was possible owing to the combination of data from government agencies that provide on-ground information – from measuring devices placed on the spot and satellite captured images of flood-prone areas. They ran hundreds of thousands of simulations on its machine learning (ML) models to predict the flow of water.In the future, leveraging AI can help disaster management bodies install drones, sensors and robots to provide accurate information about damaged buildings and landscapes, potential floods, making rescue missions safer and less time-consuming.

There is a need for smart technology to be integrated within our local communities. Immediate response and tech-based solutions can help reduce the extent of damage. However, since AI is based on machine codes, there is a scope of limitations and errors. However, the amalgamation of human, empathy and alertness, could do wonders in the field of crisis management.


If you have an interesting article / experience / case study to share, please get in touch with us at [email protected]

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1 Comment
  1. IoT app development company says

    Today manufacturers are leveraging the power of advanced digital technologies like IoT. For example, as an IoT app development company, we develop applications that help the manufacturing supervisors and managers to collect instant data from machines, assets through mobile and web dashboards to monitor the efficiency and productivity of a man and machine.

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