Truly, Machine learning holds the potential to solve and predict the upcoming calamity with its predictive analysis. Not only this, but it can also assist the team by letting them know about the level of damage. Natural calamities are imminent like Cyclone, flood, storm, tsunami etc cannot be avoided by humans. However, there’s a belief that severity can be reduced by practicing the disaster management techniques.
There are numerous cases available where the natural disaster took place such as the monsoon flood in 2017 which hit Bangladesh and ruined the life of 1200 people. Despite all the advancements, natural disasters are taking place and destroying the private n public property.
Although, ML is a technology which learns from the users and their tasks. While the learning process is going on, the machine understands every step without any guidance. So, that was the time when the bureaucrats realized that ML has the more potential then it seems. It can help in coming up with the disaster with the better strategy.
How ML is helping?
- It notifies the authorities about the areas which are severely affected by the disaster
- It helps in predicting the possible calamities
- Empowers the disaster management by letting them know about the area require immediate action
Recently in an interview with AI innovators, conducted by Forbes, Demian Borth said the goal is to make architecture which can take different modalities such as audio and video. For instance, a self-driven car(comprises of the camera with radar) which is not only working on visual rather in the audio signal as well and i.e over one network. The different architecture can improve the system performance by implementing late fusion, infusion etc. For example, the satellite uses early fusion for remote sensing. In the same way, the government can use the multi-model information for disasters like flooding, wildfires. The information can be used to take immediate actions on the fire or flood and how to access there.
Both the cases were thoroughly analyzed and predicted that how fire changes the direction with wind and in which direction it is spreading. In the latter case, the team has started working with MediaEval Satellite Task. Teams from the different region are working and submitting the results based on a neural network such that the best prediction can be obtained.
Isn’t it fascinating? The implementation, the innovation and the outcomes all in one domain which is not small instead a whole universe comes in it. To know more about it, you must continuously explore and learn from the right place. Well, there are a lot more webinars, articles, courses such as Machine learning course are available over internet which gives answers to all your questions. The course involves parametric/ non-parametric algorithms, neural networks, kernels, bias/variance theory and a lot more innovating process in ML and AI. Such that in the end, you will be able to implement the algorithms to build your own smart device.
A smart high-resolution map, discovered by Allenby which can empower the emergency response team by predicting, planning and preparing for the upcoming disaster especially for the flood. The map is based on the AI implemented aerial imagery can show an object up to 3 feet square, means 1000 times more precise than the normal map used by the forecasters. Let’s simplify it for you, for instance, you want to catch an Uber driver on the jammed street, and because of the limitations of the normal map (except uber app itself), you won’t be able to find him. As the map only shows the objects as huge as Walmart. But, with the high-resolution map, the task becomes easier.
Thus, one thing is certain that machine learning will yield multiple applications, important is how smartly we make use from it. Disaster management is one field which can avail the significant benefits from the ML applications. So, explore more, Learn more.