Natural disasters are out of the reach and influence of human beings. However, a lot can be done to minimize loss of lives. Artificial intelligence is one viable option that can potentially prevent massive loss of lives while at the same time make rescue efforts easy and efficient. To learn more, checkout the infographic below created by Eastern Kentucky Universitys Online Masters in Safety degree program.

In the period between 2005 and 2015, a total of 242 natural disasters occurred in the United States of America. These caused loss of human lives and massive destruction of property across the country. Storms registered the highest number of natural disasters with 134 recorded incidents. Other disasters included the following, in order from the highest number to the lowest. 51 flood incidents, 37 fires, 9 extreme temperature periods, 6 droughts, 4 earthquakes and 1 landslide.

In 2015, flood incidents were responsible for over $1.3 billion in property damages in the U.S., and 32 deaths. In one specific incident, about 12,000 Americans were affected when a flood ravaged through the states of Texas, Colorado, Oklahoma and Arkansas.

Fire-related cases are responsible for over $2 billion in damages and 6 deaths in 2015. A particular wildfire that occurred in Northern California affected a whopping 7,302 people.

Storms caused the highest amount of damages and property destruction worth $3 billion. These incidents also caused 46 deaths. Convective storms often travel through southern states reaching Texas and New Mexico.

Artificial Intelligence can greatly help emergency and disaster management efforts not only in America but also the rest of the world. Today, Drones, robots and sensors can provide intelligent and accurate information concerning landscapes and damaged buildings. This allows rescue workers to understand the topography of a landscape and the extent of damage to a building. Drones can be used to find victims trapped in debris allowing rescue workers to get to them quickly.

Qatar Computing Research Institute (QCRI) is a free online tool developed by the Qatar Foundation for Education, Science and Community Development. The company is based in Doha, Qatar. QCRI aims to increase efficiency of agencies and volunteer services during disaster management. The tool utilizes machine learning to automatically identify texts and tweets that relate to particular crises.

1CONCERN produces a common and comprehensive picture during emergency operations to be used by emergency operation centers. Its main goal is to assist these centers to allocate resources that are needed for rescue efforts. The tools also prepare effective planning modules, which stimulate lifelike disasters purely for training purposes. These modules also determine potentially vulnerable areas that would be affected the most during a natural disaster.

1CONCERN has been able to map about 163,696 square miles, and has covered over 39 million people so far. In addition, it has analyzed nearly 11 million structures and modeled an impressive 14,967 fault lines. This allows the program to be prepared and stay alert in case a natural disaster occurs.

BlueLine Grid was created and developed by Bill Braxton, David Riker and Jack Weiss. Braxton is the current Police Commissioner of the New York Police Department (NYPD). Until 2013, he served as the chief of the Los Angeles Police Department (LAPD).

BlueLine Grid is a mobile communications platform developed to assist rescue efforts during disasters. It connects all users to an established network of first responders, security teams and law enforcement bodies via voice, text, location and group services. This platform is effective because it allows users to quickly find public employees by geographic proximity, area or agency. It also fosters efficient connectivity, collaboration and communication.

Artificial Management for Disaster Response has proven effective in many natural disasters around the world. Technology allows people to quickly and efficiently respond to such cases, and save many lives in the process. However, these systems are not only reactive but also proactive. By predicting earthquakes and quickly warning potential victims about impending disasters, these intelligence systems have proven to be quite useful. Below are two incidents were AIDR averted massive loss of life.

In April 2015, an earthquake hit Nepal causing massive damage to property. The 7.8 magnitude quake occurred near Lamjung. Barely 72 hours after the first wave hit, over 3,000 volunteers mobilized via Standard Task Force (STF). STF is one of Digital Humanitarian Networks member organizations. The volunteers were pooled from over 90 countries and were soon on the ground ready to help victims and survivors.

The volunteers were able to assemble quickly because they were tagged in crisis-related photographs and tweets. AIDR used all the tagged tweets to identify and categorize needs based on urgency, infrastructure damage and resource deployment. This allowed rescuers and volunteers to work efficiently as a unit to help affected victims.

On September 2015, Chile was hit with a massive earthquake with a magnitude of 8.3. It occurred about 29 miles from the city of Illapel. Quick reaction from emergency responders was able to evacuate thousands of people out of the identified danger zones swiftly. This prevented further loss of life. Whats more, minutes after the quake, disaster warning sirens rang throughout the impacted areas up to the nearby coast. Mobile phones in the area were targeted with warning messages of a potential Tsunami following the aftermath of the quake. Residents in all the designated coastal areas were asked to evacuate these danger areas immediately.

Many American startup companies are coming up with ways of using artificial intelligence (AI) in a bid to save lives when natural disasters occur. Leveraging artificial intelligence has numerous potential pros making it a suitable solution to use. Using robots, sensors or drones can help first responders and rescue workers quickly access the situation as well as the extent of the damage caused to come up with a suitable action plan of saving trapped victims. It also makes rescue efforts less time-consuming, safe and properly coordinated.

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Using Artificial Intelligence for Emergency Management ...