Amidst the pandemic, India has witnessed various disaster-related calamities. The benefits of early warning and preparedness, however, was recently evident when around 20 lakh people were evacuated from coastal India when the superstorm Amphan hit India’s east coast last May.
To limit the impact of such disasters, high-quality data is obtained via sensors and cameras. Subsequent data analysis is essential for assessing pre-disaster risk and efficiently managing it. But the large, generated data calls for the high-performance computing power of supercomputers, thus, ushering a new era of intelligence in disaster response.
AI combines data from different nodes, providing algorithmically-generated insights. Emergency response teams harness data from mobile features like Facebook Safety Check to ensure that the needs of victims are met. Post-disaster response and recovery activities are aided through wider internet access. Additionally, real-time impact assessment can be done via drone imaging.
In recent times, technology lets responders reach locations without risking their lives. High-resolution sensor drones lead to a faster, cheaper and more effective monitoring of real-time damage and increase the situational awareness of the emergency response team.
The use of drone technology, however, is at a nascent stage. Aerial surveys, though outdated, are still used for situational assessment. Decades ago, when communication was patchy, aerial surveys were often the only way to get information about the disaster. Obstructed roads and dodgy telecommunication went hand in hand with disaster. Today, UAVs are a better and economical option.
A regular monsoon affair: Urban Flooding
Metropolitans like Mumbai and Chennai have paid inadequate attention to large water system pathways. Concrete construction on marshlands, causing flooding sink and erratic monsoon, are the major reasons for urban flooding. A challenge to urban planners and policymakers, the frequency of urban flooding is rapidly increasing with its intensity linked to climate change.
Current flood-damage assessment uses door-to-door inspection and remote sensing techniques alongside satellite imagery to assess the pre- and post-event situations. Since it isn’t real-time and depends on cloud cover, it is difficult to discriminate between urban features in cloud penetrating satellites. Therefore, it fails to provide enough detail to assess micro-topography.
UAVs can be deployed in otherwise inaccessible areas, providing high-resolution outputs. 3D imaging technologies from low-altitude drone platforms, combined with satellite imagery, can help us understand and scale urban flooding.
Burning country: Forest Fires
In recent times, 16,656 fire alerts were detected in India, the highest in five years, according to the Global Forest Watch (GFW). The peak fire season beginning in early March, lasts around 3 months with the rising temperatures across north India being the reason.
Controlled burns, used to prevent forest fires, involve setting a controlled fire in the path of an approaching wildfire. With all flammable materials burnt, when the wildfire approaches, no fuel is left and the fire dies out. Locally pilot-operated UAVs, with aerial ignition systems, as opposed to firefighters can undertake the task. Giving a bird’s-eye view and equipped with thermal cameras, drone cameras can see through smoke, helping pilots monitor and map the fire’s track. Computer vision can overlay area maps and other details on the screen so pilots don’t have to refer to multiple maps.
Order from chaos: Cost of Big Data Analysis
We need computing power to make sense of the data generated. The complex size of our data is growing faster than our computing resources, putting a considerable strain on our computing fabric. Enter Quantum computing that promises to deliver an exponential increase in computing power that can execute increasingly complex machine learning algorithms.
Currently, Quantum Computers (QC’s) are the size of a refrigerator that can perform certain calculations a million times faster than classical computers. While mainstream computers use bits to store data only in binary, QCs use Quantum bits to store data in multi-dimensional spaces. Algorithms are performed using wave interference, entanglement and superposition to magnify the amplitude of correct answers and shrink the incorrect answers. This has instigated a race in the industry to launch a viable quantum computer.
However, Quantum computing is still a distant dream with much research still needed to make it a mainstream reality. Given its potential, Quantum computing can transform the world.
The author is Co-Founder, Integration Wizards Solution IRIS Tech
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