Integrated AI-Driven Humanitarian Assistance

In the context of destabilizing events, the topic of vulnerability refers to the increased risk of negative experiences, effects, and reactions before, during, and after a disaster. For example, the vulnerabilities of people with low socioeconomic status (SES) are more likely to live in precarious housing, have difficulty accessing resources after a disaster, and are more likely to experience trauma during and after a disaster. may indicate a high It also means that they are less likely to receive disaster warnings, have the ability to respond to disaster warnings and evacuate, and are able to receive assistance after a disaster. Use vulnerability as a measure of risk or likelihood - not actual adverse experiences, impacts, and responses

Pakistan faces one of the highest levels of disaster risk in the world, ranking 18th out of 191 countries in the 2019 Inform Risk Index. In Pakistan, approximately 76% of the geographic area is designated as underserved areas and approximately 96% of the population has difficulty accessing healthcare and Enhanced Immunization Program (EPI) facilities. The situation is exacerbated when most of these areas are prone to frequent disasters. Floods are the most common. UNISDR estimates Pakistan's average annual loss from floods at about $1 billion. The greatest challenge facing affected people is immediate rescue preparedness, including women and children who are most at risk of food insecurity and malnutrition, shelter, death, loss of livelihoods, and reproductive and other healthcare disruptions. is not in order. It's not just Pakistan, but all the third-world Wnations, including India, Afghanistan, and Indonesia, will face hardships when hit by a disaster they're unprepared for. Most of these problems are a direct result of a lack of funding, education, and accessible technology to efficiently meet challenges such as not knowing how to forecast the weather and avoiding large-scale damage. Who is in charge? government? But what if they lay the groundwork to complicate such challenges?

Across the world, people with low SES are more likely to live in disaster-prone homes than people with high SES. When they experience disasters, they can experience greater material loss, poor protection from disasters, and greater destruction of their homes. The World Bank and GFDRR have found that people living in poverty around the world are more likely than others to live in areas of high disaster risk. They explain that this may be because more dangerous areas are cheaper or simply more accessible. We are looking at the likelihood that people live in areas where there are high levels of poverty, noting that people living in poverty are more likely to endure heat and drought because of where they live. Mixed results have been obtained about the relevance of living in flood-prone areas, but the situation in urban areas is less clear.

We propose an EADR Framework

E: early detection

1. Develop AI models specially trained on specific country meteorological and geological data to ensure accurate forecasting and early detection of region-specific events. An AI system that can process and analyze data collected by drones. AI can quickly assess the severity of disasters, identify areas of highest risk or urgent need of evacuation, and determine suitable landing sites for rescue operations.

2. Analyze collected data using AI algorithms to account for local weather patterns and country-specific seismic activity. Detects anomalies and leading indicators of extreme weather events such as floods, heat waves, and seismic motion. AI systems use real-time data to determine the most efficient route for drone evacuation, taking into account factors such as terrain conditions, airspace restrictions, and available landing zones. This allows people to be transported quickly and safely to shelters and medical facilities.

A: Automated Communication

1. Develop automated communication systems that can process and understand messages in multiple languages e.g. in Pakistan including Urdu, Punjabi, Sindhi, etc.

2. Conduct awareness campaigns for the people of third-world nations on automated communication systems, their capabilities, and how to use them effectively to report emergencies and seek help.

3. Integrate AI systems with a robust communications infrastructure to send automated alerts and alerts to affected residents, local authorities, and relevant emergency response teams. This ensures timely information reaches those at risk and facilitates coordinated rescue efforts. 

D: Drone deployment

Delivery to affected areas, especially inaccessible areas e.g. mountainous terrain region of Pakistan

1. It uses satellite imagery and mapping technology to identify remote and inaccessible areas of Pakistan that are prone to natural disasters, such as mountainous areas and flood-prone areas.

2. Design drones with adaptable payload systems to transport Pakistan's vital supplies such as clean water, food, emergency medical kits, and tents suitable for extreme weather conditions.

3. Deploy specialized rescue drones to safely transport people from disaster areas to designated safe zones. These drones can carry multiple passengers, have safety features such as emergency parachutes and buoyancy aids, and carry medical supplies for immediate assistance.

4. Equip rescue drones with live video streaming capabilities and two-way communication systems to enable remote monitoring and guidance by responders. This allows emergency responders to assess the situation in real-time, instruct people to evacuate, and provide medical assistance if needed.

R: Research

1. The use of big data supports disaster recovery efforts by providing insight into the extent of damage, infrastructure needs, and population movements. By integrating data from remote sensing, aerial imagery, and ground surveys, researchers can create detailed damage assessment maps and prioritize restoration efforts.

2. Big data analytics help assess the social and economic impact of disasters on affected communities. By analyzing social media data, financial transactions, and public health records, researchers can gain insight into the psychological, economic, and public health impact of disasters.  We advocate an EADR framework that effectively summarizes the most viable and innovative ways to address the challenges facing the healthcare sector.

Our solution serves the nation with a lack of efficient government agencies and authorities who face serious consequences in the context of destabilizing events just because of the slow response by those in charge of their safety. It is specially designed for the underserved groups of society e.g. women, and children who are the most vulnerable. This AI system is completely automated and will work on its own as soon as extreme changes in its surroundings e.g. fast wind speeds, high temperature imposing a risk of fire, or ground movements indicating a possible earthquake. All those living in poor areas which are at the highest risk of being affected will be protected by this AI-integrated technology. The elderly who can’t travel long distances will be assisted by specialized rescue drones. The solution is specially designed for more than 60% of the world’s population living in poverty and in the most dangerous areas. This is fast than any human response could ever be. It targets those living in e.g. KATCHI ABADIS.

Currently, these populations are being taught the basics of the system and given education on how this operated and what to expect. They're also being taught the way of evacuation and given psychologist meetings to remain calm in such situations, something that is significant for their mental health. They're also getting connected with the authorities and fsmilrising ith NGOs so they know who to seek in times of help, someone they know will help despite all odds.
The impact of this system is beyond just safely rescuing people. The system is going to identify early changes so authorities and people in the danger zone could be informed before the disaster actually strikes. This would allow them to prepare themselves for a possible disaster. This does not only mentally prepares them for any trauma of immediate capture but also gives them the time to be with their families, take all their necessary belongings, and leave the area in a protected manner. The system is highly efficient and responsive, it will immediately signal all the data recorder to connected departments.
The system also helps in providing supplies to the affected people. These supplies will come from trusted NGOs working for the safety of people and food will be completely organic to eat thereby not compromising their health or putting them in danger of food poisoning or malnutrition.
Lastly, the data collected from the event will be further processed nd researched by professionals in the department so they can identify any trends, differences, and similarities in previous data records and propose reasonable solutions to prevent the disaster as a whole. For example, Pakistan is most prone to high floods. If data were to be collected like the time they most likely to come, the weather, the seasons, and the areas, and the more refined this information would be, the more effective solutions could be implied. Therefore, our AI-integrated solution is the best as of yet.

We believe that I and my team are the most suitable and well-formed people for this solution as we ourselves have lived in such poverty-stricken areas our whole life. We are aware of the challenges that these people face, we understand their struggles, and having been through it ourselves really made us understand the necessities of the time. We are and try to remain as connected to these underserved people as possible. Our homes lie in close proximity, about 20 km at max and so we’re well near to promptly reach ourselves to help those in need. Moreover, we pay weekly visits to their houses and are in communication at all times keeping track of the progress. Having designed such a solution ourselves gives us an edge over how to operate, what impact to expect, and how to work in times of failure. The whole team is being trained by professionals to properly manage situations in terms of natural disasters. NGOs are doing their work of collecting funds to maximize their food ration and help the maximum number of people. We plan onto scaling our work to all the villages of Pakistan by raising more funds, and if possible, we’ll take it to a global level

The idea of this whole AI-Integrated system is fully developed with all its objectives and features as mentioned earlier in the solutions. The fact that it's a prototype rather than a concept is that we have proof to show for the start-up of the device. We have a whole, complete design of the device and  know the build-up process. As soon as it passes all the required tests of technology and development, it will soon be running and showing growth.

upto 50,000 people currently living in areas at most risk of destabilizing events e.g. Balochistan, Swat

One of the main purposes for applying to Solve is the fact that it recognizes our project and gives us a platform to showcase our idea which could possibly run and impact more people than currently being offered. The biggest challenge we’re currently facing is technology-wise, we need more knowledge and have loopholes in our design that we believe if assisted by a professional in the field of IT and physics, or just simply AI, could really help us overcome. Pakistan currently has no support whatsoever in overcoming these problems during these destabilizing events. The government is too busy politically that they’re far from focusing on such urgent and disastrous matters.  The NGO's currency working is either not developed enough and as they're human-run, they are very slow in response and take days or events months in reaching out to those affected by the time, many deaths have occurred. SOLVE could help us firstly get access to professionals so they can work with us on our prototype and make it 100% work. Lastly, SOLVE could provide us with support to reach these inaccessible areas in Pakistan safely. As a women-led team, it's dangerous for us to o these areas unaccompanied. There are risks of human trafficking, violence, or rape in extreme cases. We plan on expanding our project globally and helping all the third-world countries, we believe that with SOLVE, having a global reach could be possible and people not only in Pakistan but all over the world could be positively impacted and helped during these destabilizing events when they're left vulnerable, helpless and have nobody to seek, something which is completely not their fault.