From Preparedness to Immediate Response: AI in Disaster Management

We’re currently in the middle of coronavirus disaster, “the worst pandemic in more than 100 years,” according to Antony Fauci, MD, Director of the US National Institute of Allergy and Infectious Diseases. More than 1.39 million people have already died from the virus, with at least 58 million cases reported in 188 countries to date.

It shows just what an unexpected disaster can do. From widespread human loss to economic turmoil, it can be a painful experience. The worst part is that these disasters happen almost all the time, from the Haiti earthquake in 2010 that left at least 220,000 people (2%+ of the country’s population) dead to Typhoon Haiyan that killed at least 7,000 people in the Philippines. In the face of such calamities, being prepared can make a critical difference. Stockpiling prepper supplies and equipment can mitigate the severity of the impact, offering a lifeline amidst chaos. These supplies include not only the basics such as emergency food and drinking water but also communication tools, lights, and equipment necessary for navigating through debris-strewn landscapes. By proactively equipping oneself with these essentials, individuals and communities can better prepare for unforeseen disasters, potentially minimizing the impact and ensuring a swifter recovery process.

Artificial Intelligence to the Rescue

Many experts now believe that artificial intelligence (AI) can play a central role in anticipating and ultimately containing even the worst disasters. The following are just a few ways AI could help;

• Anticipating the chaos

First and foremost, disasters don’t just happen out of nowhere, especially the large ones. There are usually plenty of warnings. For the coronavirus, ABC News reports that there were warning signs as far back as November 2019. Satellite images and the analysis of wire and computer intercepts raised alarms over an “out-of-control disease” that would pose a severe threat.

In the case of Covid19, AI can be programmed to mine social media data, news reports, public health data, and search engines to track reports of illnesses or increased queries relating to symptoms.

This information can then be used alongside hospital admissions data to monitor disease spread and raise the alarm when predefined density is reached. AI solutions can also raise warnings if individuals from an infected region are traveling into new territory.

The same approach works in anticipating natural disasters such as earthquakes. In this case, too, the massive shockwaves often come after several warning signs. IoT sensors developed specifically to detect certain ground movement types can help detect smaller earth movements and raise the alarm about a potential earthquake.

• Preparing the populace 

Once the disaster strikes, the next step is to ensure everyone is informed and knows what to do. Here too, AI solutions can be vital.

AI, working alongside other technologies such as mobile and IoT, expands reach and offers faster response at reduced costs. The systems can send out alerts and news to keep everyone in the know and provide the necessary digital resources to understand what’s required.

For instance, partnerships between AI platforms and telecom providers provide an affordable, accessible way to alert citizens about tsunamis and earthquakes. In China, the telecom company Xiaomi recently integrated an earthquake warning function into its MIUI operating system. The application warns users about impending earthquakes before their impact is even felt.

Artificial intelligence can also fill gaps in existing disaster alert systems. An excellent example is the US Emergency Alert System, which relies on a cellphone or radio broadcast and often fails to reach people inside buildings. Some tech companies are looking into the possibility of using AI to analyze CCTV footage in real-time to determine the potential for disasters, such as earthquakes, and sounding alarms within buildings.

• Facilitating response 

After sounding the alarm, next comes the response. While AI cannot administer medication to covid19 patients or evacuate occupants in case of a fire, it can aid the response process in many valuable ways.

First off, AI allows responders to monitor the disaster in real-time. Whether it’s doctors responding to Ebola outbreaks or firefighters rushing to put out an enormous flame, AI makes it possible to view the situation unfold in real-time. The responders can also get up-to-date alerts about what’s happening. Processing this information allows the decision-makers to determine the best course of action depending on the disaster’s location and severity, among other factors.

Secondly, the latest AI technologies can also facilitate autonomous vehicle response. This is especially useful when human intervention isn’t a straightforward option, such as where there’s lots of rubble and property damage. If survivors are trapped beneath the ruins, AI-powered autonomous vehicles, drones, etc., can be sent into the area to collect further information or even evacuate casualties. 

Another potential application is fighting fires. Some experts have proposed tree-mounted IoT sensors that monitor natural factors, such as humidity, carbon monoxide, and carbon dioxide. When there’s a fire, readings drastically shift, immediately alerting authorities. Immediate response can be critical in saving lives and even properties.

In addition to the technological advancements mentioned, the role of specialized fire watch agencies becomes paramount in addressing the challenges posed by wildfires. These agencies, equipped with cutting-edge technology and trained personnel, play a crucial role in fire prevention and early intervention. The integration of AI technologies, such as tree-mounted IoT sensors, can significantly enhance their capabilities in swiftly detecting and responding to potential fire outbreaks.

For instance, the Colorado Fire Watch Company, a leading entity in fire prevention, has embraced state-of-the-art systems to monitor environmental conditions. Their network of sensors strategically placed in high-risk areas continuously analyzes factors like humidity, carbon monoxide, and carbon dioxide. In the event of a significant deviation indicative of a potential fire, the Fire Watch Company’s immediate response mechanisms are triggered. This proactive approach not only aids in preventing wildfires but also allows for rapid deployment of resources to mitigate the impact. As communities increasingly recognize the importance of such specialized agencies, collaborations with innovative companies like the Fire Watch Company become instrumental in safeguarding lives and properties from the escalating threat of wildfires.

• Disaster prevention 

Finally, AI is also likely to play a starring role in preventing disasters in the future. Researchers at the Monash Data Futures Institute in Australia are currently using data sourced from the European Science Agency’s Sentinel-2 satellite to analyze images of various areas of the Victoria state to determine ways to prevent perennial bushfires.

So far, the researchers have analyzed more than 4,300 high-resolution images and, using a time series classification, are in the process of building models and annotated data to better understand vegetation cover, land use, and how these factors affect bushfires.

“These maps have the potential to assist in the prevention of bushfires,” says Joanna Batstone, the Institute’s director. “They can also help with agricultural planning, flood modeling, pollution management, and rehabilitation.”

“Many disaster reduction approaches today rely on single data streams such as assessing temperatures, rainfall, or vegetation. We need to bring those data sets together,” he continues.

Remember that AI also provides the data and analytics necessary to learn from previous disasters. After a fire, AI solutions provide the tools to analyze the incident to determine what went wrong and possible remedies.

Still so Much to Come

The main challenge with all these applications is that AI itself has only been here a short while. Technologies such as Machine Learning (ML) and Deep Learning (DL) necessary to derive answers from AI solutions are just beginning to make sense. Additionally, critical complementary technologies, such as IoT, are also just taking off.

Therefore, it could be a few more years before we see AI make a proper impact on disaster preparedness and recovery. However, when that time comes, the impact could be huge!

Have any questions about AI, its applications, or related technologies? The experts at NIX Solutions are always looking to help.