A Deep-Learning-Based Emergency Alert System

Nowadays, there are a lot of dangerous situations related to natural disasters and military conflicts that take place all over the world, and this is why the issue of alert systems is so relevant.

Having read the posting by Brian, I managed to realize that the problem that he mentions is really urgent for the society and it is necessary for those specialists working in the spheres related to human safety and health to pay an increased attention to development and implementation of new methods helping to alert people living in rural areas who sometimes do not have an access to the Internet, television, or radio.

Therefore, as it is clear from the posting by Brian, different organizations in the United States and all over the world including NWR and NOAA have started taking additional measures in order to provide citizens with an access to this important information at any time. As for my personal opinion concerning this posting by Brian, tornado preparedness remains a significant problem for our society even though alert systems used nowadays are quite developed.

Moreover, I suppose that it is very important that the author focused on rural citizens; nowadays, almost all the people living in cities and towns all over the world have an access to the Internet or may be warned with the help of various means of information. Apart from that, I believe that it is important to discuss the systems that have been designed in order to warn people not only about various types of natural disasters such as tornadoes, earthquakes, or floods but also about military actions and possibility of terrorist attacks.

Therefore, another important fact that can be mentioned within the context of the topic is related to the existence of EAS that was established almost twenty years ago in the United States and replaced the previous alert system that had been used for more than thirty years (Kang & Choo, 2016).

Speaking about alert systems, it is important to mention that they are also changing in accordance with the status of development of modern technologies. For instance, almost nine years ago there was a series of attempts to develop and implement one more system allowing to warn citizens of the United States about possible dangers. This system was supposed to work with smartphones that were becoming more and more popular during that period of time. About four years ago, the specialists finished working on this system (WEA) and people living in particular states of the country were provided with an opportunity to use it and get the information with the help of their smartphones. Although the alert system called EAS is supposed to be the most important one in the United States, another system available on smartphones and other devices may work independently from it.

In general, I support the opinion expressed by the author that such group of people a rural citizens may be called vulnerable because of the lack of cable and limited access to the Internet. Nevertheless, as it is clear from many discussions devoted to the topic of alert systems, it may be stated that modern specialists are not satisfied with what has been achieved before, and there are a lot of attempts at perfecting certain methods and the devices used. For instance, in order to provide more people with an access to the important information concerning natural disasters, they pay attention to improving siren coverage in different parts of the United States (Mathews & Ellis, 2016).

References

Kang, B., & Choo, H. (2016). A deep-learning-based emergency alert system. ICT Express, 2(2), 67-70.

Mathews, A. J., & Ellis, E. A. (2016). An evaluation of tornado siren coverage in Stillwater, Oklahoma: Optimal GIS methods for a spatially explicit interpretation. Applied Geography, 68(1), 28-36.

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