News Karnataka
Thursday, November 30 2023

IETE hosts Webinar on Deep Learning for Disaster Management

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Dr Jyothi Prakash Singh explaining Deep Learning for Disaster Management mainIETE Mysuru Centre organized a webinar “Deep Learning for Disaster Management” On 30th January 2021. The Chief Guest for the webinar was Dr Jyothi Prakash Singh, Head, Department of Computer Science & Engineering, National Institute of Technology, Patna, India. 

Prof Nataraj C R, Chairman, IETE Mysuru centre, Dr Bhagyashree S R, Vice-chairman, IETE Mysuru centre, Dean (Research) & Professor, Dept., of ECE, ATMECE, Mysuru, Dr Parameshachari B D, Hon., Secretary, IETE Mysuru centre, Professor & HOD, Dept., of TCE, GSSSIETW, Mysuru, Prof Shashidhara S Gokhale, Hon., Treasurer, IETE Mysuru, EXECOM Members of IETE Mysuru Centre participants from various colleges participated. 

The session was commenced by welcoming the Speaker, panel members and participants by Abhishek M V, Dept. of ECE, MIT, Mysuru. The webinar was coordinated by Pavithra AC, Asst., prof., Dept., of E & C, ATMECE, Mysore and EC Member of IETE Mysuru centre & Priya MS, Asst., Prof., Dept., of E & C, MIT Mysore. 

Dr Jyothi Prakash Singh highlighted the insight about the current disaster management approach which involves satellites and drones that gather data from areas that are prone to disasters. But how effective are the results of this approach? The current disaster model fails to: offer data in real-time, gather data from multiple sites at the same time, and suggest proactive steps for disaster prevention

Additionally, the current disaster management systems do not offer clear and crisp images of disaster-prone regions. This is why it’s high time experts implement deep learning in disaster management to overcome these current issues.

Data from multiple sources, such as weather reports, satellite images, disaster history, can be used to train a deep learning system. After the training, a deep learning machine can foretell the occurrence of a disaster using a convolutional neural network. With insights drawn from a thorough analysis, experts can predict the imminent occurrence of disasters, helping people to follow a proactive approach and minimize the impact of catastrophes.

No one can pause or halt the occurrence of natural or human-made disasters. We can only take steps to reduce their impact. By integrating deep learning applications such as drones, experts can get real-time data on areas that are about to get hit by a disaster. Timely and sufficient measures can then be taken to save lives and property. Furthermore, drones can also track specific areas, such as forests and narrow geographical locations, so that special help can be extended to such difficult terrains. Today, deep learning is ready to show its potential in unconventional areas like disaster management. In an era of increased social media, tailored advertising, and big data, it’s easy to forget that deep learning can be used for more than just improving home technology and the user experience. Deep learning could prove useful in humanitarian aid efforts as well.

The Session was concluded by thanking the participants by Priya MS, Assistant Professor, Dept. of ECE, MIT, Mysuru. The webinar was attended by more than 200 participants from all over the country. This webinar was appreciated by the participants. They expressed that this webinar gave valuable inputs and most of the doubts related to on “Deep Learning for Disaster Management” were cleared by the resource person. he event was compered by Deekshitha,  Student, Dept. of ECE, MIT, Mysuru.

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