From Data to Action: Leveraging AI and IoT for Disaster Preparedness and Response

Natural disasters such as hurricanes, floods, and wildfires regardless of their scale or type can create havoc in communities, causing significant loss of life, vegetation, and property damage. However, with the advent of emerging technologies such as artificial intelligence, its subsets, and IoT, among others, a possibility seems to happen where we meet, manage, and even prevent disaster management challenges directly with the strength of these cutting-edge technologies. Two major transforming forces have been the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) offering unprecedented capabilities in predicting, preventing, and responding to catastrophic events.?

Artificial intelligence is a “set of technologies that allow computers to perform advanced functions, such as seeing, understanding language, analyzing data, and making recommendations.” IoT or Internet of Things is “the collective network of connected devices and the technology that facilitates communication between devices and the cloud, as well as between the devices themselves.”? These two technologies aren’t just reshaping our approach to disaster resilience, the economic benefits are also substantial. The World Bank estimates that the effective use of digital technologies in disaster risk management could save up to $65 billion annually in disaster-related losses worldwide.?

So, let’s understand how these technologies predict disasters and aid in faster recovery. Additionally, we’ll also cover the significant impact of technology on recovery, its promising prospects, and a few challenges this techno-driven approach towards disaster management would have overcome to create more resilient communities in the face of natural and man-made disasters.

Smart Solutions: How AI and IoT are Shaping the Future of Disaster Management

With climate change and global warming at its peak, there’s no question that there’s an urgent requirement for far more rigorous, reliable, and real-time forecasts of such catastrophes. This is not just to evacuate residents from the epicenter, and improve existing infrastructure but also to build emergency structures, and enter a vigorous state of preparedness. According to Forbes, natural disasters cost the US approximately $165B in 2022. Hurricane Ian alone was responsible for nearly $113B in damages in September 2022. While, between 2019 and 2023, India faced damages worth $56 billion due to weather-related disasters.??

Moreover, the UN's Global Assessment Report (GAR2022) revealed that disaster events are projected to reach 560 a year by 2030, exposing half of the world’s population to floods, storms, and tsunamis. The recent landslides that devastated Waynand, Kerala are one of the many reasons we need immediate and advanced measures to reduce vulnerabilities associated with disasters, enhance resiliency, and mitigate the event’s overall impact.

Leveraging Technology in Emergency Management: Changing the Game

Disaster management and recovery is a complex, multi-tiered process that requires several different government and non-government organizations working together. This collaboration of effective planning is quick and uses the most advanced tools and technologies, so let’s understand how technologies such as AI and IoT are making this possible. The impact of these technologies is already evident.

During the 2023 California wildfires, AI-powered early warning systems helped evacuate over 50,000 residents, reducing potential casualties by an estimated 70%.

In Bangladesh, IoT-based flood monitoring systems provided crucial lead time for communities along the Jamuna River, saving an estimated 4,500 lives in the 2022 monsoon season.

As we face the mounting challenges of climate change and urbanization, the role of AI and IoT in disaster management becomes increasingly vital. These smart solutions are not just improving our ability to respond to disasters; they're fundamentally reshaping how we prepare for and mitigate their impact.

From Prediction to Prevention: AI Technologies in Proactive Disaster Management

AI is not just about predicting disasters; it's increasingly being used to prevent them or mitigate their impact. These AI applications are not only improving our ability to prepare for disasters but are also helping to build more resilient communities. Leveraging the power of data and machine learning, we can anticipate potential risks, strengthen our infrastructure, allocate resources more effectively, plan for emergencies with greater precision, and empower individuals with the knowledge they need to stay safe.?

AI as a technology for disaster management, especially machine learning, is turning out to be a component in the field of disaster risk reduction. It has moved beyond the role of predicting events, creating hazard maps, and real-time event detection, to offering situational awareness, aiding decision-making, and more. However, the true genius of AI lies in its adaptability. With the evolving situations, AI models can adjust their predictions, thus ensuring that relief strategies remain relevant. Moreover, natural language processing, another AI branch, now scans social media in real-time during disasters.

Let’s understand how else the technology is enabling faster responses to emerging threats or pleas for help.

• Climate modeling: AI-powered climate models can predict long-term weather patterns and potential climate-related disasters with unprecedented accuracy. For instance, IBM's Deep Thunder system uses machine learning to provide hyperlocal weather forecasts up to 84 hours in advance with 0.2 to 1.2-mile resolution. This level of precision allows for tailored preparedness strategies in specific neighborhoods or even individual city blocks.
• Infrastructure resilience: Machine learning algorithms analyze structural data to identify vulnerabilities in buildings and infrastructure, allowing for preemptive reinforcement. In Japan, AI systems like those developed by Fujitsu are analyzing decades of earthquake data and building performance to predict how structures will respond to seismic activity. This enables targeted retrofitting, potentially saving billions in repair costs and countless lives.
• Resource allocation: AI systems optimize the distribution of resources based on predictive models, ensuring that high-risk areas are adequately prepared. The United Nations Development Programme has implemented AI-driven systems in countries like India and the Philippines to optimize the pre-positioning of relief supplies. These systems consider factors such as historical disaster data, population density, and infrastructure accessibility to determine the most effective resource distribution strategies.
• Evacuation planning: AI algorithms can design efficient evacuation routes and strategies based on population density, traffic patterns, and predicted disaster paths. The Odisha State Disaster Management Authority (OSDMA) has developed an AI-powered early warning system called "SATARK" (System for Assessing, Tracking, and Alerting Disaster Risk Information based on Dynamic Risk Knowledge). During Cyclone Fani in 2019. SATARK's early warnings and efficient evacuation planning helped the state government evacuate over 1.2 million people within 24 hours before the cyclone made landfall.
• Public awareness: AI-powered chatbots and virtual assistants provide personalized disaster preparedness information to the public, enhancing community resilience. The American Red Cross has implemented an AI chatbot named "Clara" that can answer questions about disaster preparedness in multiple languages. In its first year of operation, Clara engaged with over 2 million users, providing tailored advice based on individual circumstances and local risk factors.

The Future of Disaster Response: How IoT is Changing the Game in 2024

IoT technology revolutionizes disaster response by providing real-time situational awareness and enabling rapid, coordinated action. The Internet of Things or IoT has different use cases across industries, and for disaster management, it stands out because the availability of real-time information along with real-time analytics cannot be understated in planning for prevention and response to disasters. The technology due to its access to sensors, high-speed connectivity, cloud computing platforms, ML and analytics, and conversational AI, offers disruptive potential in the prevention, preparation, response, and recovery phases of disaster management.

Here are five ways IoT is transforming disaster response:

• Smart emergency vehicles: Connected ambulances and fire trucks equipped with IoT sensors can transmit real-time data on their location, status, and the conditions they encounter. For example, the New York City Fire Department has implemented a system called FireCast, which uses IoT sensors and AI to predict and prevent fires. In emergency response, these smart vehicles can provide real-time updates on traffic conditions, optimal routes, and patient status to hospitals. This technology has been shown to reduce response times by up to 30% in pilot programs.
• Wearable tech for first responders: IoT-enabled wearables monitor vital signs and environmental hazards, enhancing safety and efficiency in the field. The U.S. The Department of Homeland Security's NGFR (Next Generation First Responder) program is developing smart clothing with integrated sensors that can detect toxic gasses, monitor heart rate and body temperature, and even track the posture and movement of firefighters in low-visibility environments. These wearables can alert both the wearer and remote command centers to potential dangers, significantly improving first responder safety.
• Drone networks: IoT-connected drones provide aerial surveillance, deliver supplies to inaccessible areas, and assist in search and rescue operations. In China, telecoms giant Huawei has developed a drone-based 4G network that can be rapidly deployed in disaster zones to restore communication. Meanwhile, companies like Zipline are using autonomous drones to deliver medical supplies in remote areas of Rwanda and Ghana, a model that could be adapted for disaster response. These drone networks can cover large areas quickly, providing critical information and resources in the crucial early hours of a disaster response.
• Smart buildings: IoT sensors in buildings can detect structural damage, guide evacuations, and provide vital information to rescue teams. For instance, Japan's Earthquake Early Warning System uses a network of seismometers to detect tremors and automatically trigger actions in connected buildings, such as shutting down elevators and opening doors for evacuation. In the aftermath of an earthquake, these smart buildings can provide real-time data on structural integrity, occupancy, and environmental conditions, guiding rescue efforts and potentially saving lives.
• Resilient communication networks: IoT-based mesh networks ensure continuity even when traditional infrastructure fails. Project Loon, an initiative by Google's parent company Alphabet, uses high-altitude balloons to create an aerial wireless network to provide emergency internet coverage in disaster-stricken areas. This technology was successfully deployed in Puerto Rico after Hurricane Maria in 2017, helping to restore connectivity to over 100,000 people.?

Top 4 AI and IoT Innovations Revolutionizing Disaster Response

Brief mentions of how technologies like AI and IoT have been empowering new-age disaster management and are changing how we can reduce the impact of natural disasters and man-made disasters.

• Japan's earthquake alert system stands out, providing seconds to minutes of warning before a tremor hits, saving lives and infrastructure.

• Bangladesh's cyclone warning system has significantly reduced fatalities by ensuring timely evacuations.
• In Europe, the European Flood Awareness System (EFAS) offers early flood predictions, aiding in swift response and mitigation.
• According to HCL Tech, “Ericsson is working with a Chinese company to use 5G in disaster management, including accurate disaster prediction, visible disaster occurrence, shared data silos, coordinated emergency command and timely evacuation.

However, establishing early warning systems isn't without challenges. Ensuring accurate predictions, managing high installation costs, and creating public awareness can be daunting. Naturally, international collaborations, investment in research, and community-based education can pave the way for more effective and widespread warning systems.

Summing It Up

There’s no doubt that the integration of Artificial Intelligence and Internet of Things technologies is revolutionizing disaster management. From predictive modeling and early warning systems to smart emergency response and resilient infrastructure, these technologies are empowering us to better prepare for, respond to, and recover from disasters. In addition, we can see how the technologies are moving beyond improving our ability to save lives, reducing economic losses, and building more resilient communities. However, as we look to the future, it's clear that we're only scratching the surface of what's possible.?

The convergence of AI and IoT with other technologies such as 5G networks, edge computing, and other emerging technologies promises to create even more sophisticated and effective disaster management systems. Yet, as we embrace these technological advancements, we must also address important challenges. Ensuring data privacy, bridging the digital divide to make these technologies accessible to all communities, and maintaining the critical human element in decision-making are all crucial considerations.

At Binmile, we intend to be at the forefront of enabling digital transformation that can contribute to the development of more resilient systems against disasters with our innovative solutions, powered by IoT and AI. As a software development services company, we are committed to creating robust platforms that can withstand and rapidly respond to various catastrophic events, thereby enhancing overall disaster preparedness and response capabilities and building a safer, more resilient world for all.