NorthStar

❗Problem

• There were 949 deaths related to flooding in Europe in the last 10 years additionally 1 in 8 europeans are at risk from floods today and this will only increase due to global warming.
• An example of the devestating affect of floods are the floods that occured in Valencia Oct 29, 2024 where 221 people lost their lives.
•  A large factor in the high amounts of deaths was the lack of premtive warning as well as people not knowing where to go.
• Quotes from survivors:
• “The storm hit in the morning. But the water didn’t get to us until 8 in the evening. Yet, nobody warned us, nothing. Nobody cared.” source
• “We started to drive not knowing which direction to take.” source
• We want to solve the problem of not knowing where to go during a natural disaster such as a flood.

💎 Solution

We propose a dynamic web application that utilizes satellite imagery and geospatial intelligence to instruct people before/during natural disasters (such as floods) on safe routes to evacuate.

The webapp is capable of being embedded in the existing infrastructure such as EU-Alerts due to being fully hosted in the cloud and not requiring installation on individual devices.  

The webapp has the following features:

• Flood height prediction using Efas 

• Identifying high risk areas that should be avoided

• Providing live gps navigation evacuation routes for drivers and pedestrians that avoid high risk areas

• Distress button that automatically calls authorities and provides them with your location

The first stage is helping during flooding, as it is a common natural disaster with a high mortalitiy rate in Europe. However, we plan on extending the technology to various scenarios, including earthquakes, volcanic eruptions, nuclear crisis, and wildfires. By making it possible to embed our app in the existing infrastructure it is possible to quickly make it accessible to citizens across Europe.

💸 Buisness Case

Our plan is to use a SaaS with european government/ the EU being our customer. The users will be citizens of those respective countries. Since we are expecting very high traffic for our webapp during a natural disaster we are planning on using larger servers to accomodate for this. From our research we found that for a million concurrent users it costs €65,000 per month. There is also the cost for further development and expansion of our webapp which we estimate at €16,000 per month. Making the total costs somewhere around  €80,000 per month. We estimate the benifit that could come from our webapp as being able to save 10% of flood victims, given that the number of flood victims over the last 10 years is 949 in europe and that the expected the value of life estimate for an average european is €3,273,91 we estimate the money saved by our app being €31,069,406 over the next 10 years (assuming the number of deaths stays the same). This is only the value saved from applying our technology on floods, imagine the impact if we were to apply it on more natural disasters . 

🛰️ EU space technologies

We utilize information from EFAS which is a part of the Copernicus emergency service. Flood prediction models are generated with the use of the Copernicus satellite system and the LISFLOOD hydrological model. Currently the LISFLOOD model struggles with predicting flood height in urban environments therefore we intend on using the surface runoff prediction, rainfall prediction and drainage prediction of LISFLOOD along with the Copernicus digital elevation model to predict flood height in urban areas taking building heights into account when guiding people to a safe location. 

Furthermore, using satellite data offers several advantages over traditional methods for flood mapping, making it a superior choice for effective disaster management. Satellites provide wide-area coverage, capturing extensive regions in a single pass, which is difficult to achieve with ground-based surveys. They deliver real-time data, crucial for prompt flood detection and response during emergencies. Enhance reliability by enabling all-weather and day-night imaging, penetrating cloud cover and functioning regardless of lighting conditions. Additionally, the increasing availability of free satellite data makes this technology cost-effective and accessible. Satellite-derived data can also be seamlessly integrated with hydrological models to improve flood forecasting and monitoring, enhancing the accuracy of predictions. 

🔭 EU Space for Defence and Security

Which of the 3 challenges are you solving, and how does this contribute to support the EU Defence and Security ecosystem?

We are dealing with challenge 1, enhancing defense & security with geospatial intelligence. 

Major contributions of Geospatial Intelligence for Defence, Humanitarian Aid, Contingency Planning and Security Surveillance

1. Optimizing disaster response: By providing real-time updates from satellite imagery, our platform enables rapid and efficient evacuation by identifying the safest pathways for drivers and pedestrians during disasters such as floods. This minimizes chaos and ensures timely action to save lives.

2. Humanitarian aid: Our application streamlines crisis management by reducing confusion and providing clear, actionable guidance for both citizens and responders. This strengthens the EU’s capability to manage crises effectively and protect vulnerable populations. 

3. Enhancing contingency planning: Leveraging historical and real-time data from Copernicus EO systems, our platform predicts flood risks and other disaster scenarios. These predictive insights enable authorities to proactively plan and allocate resources, improving preparedness and resilience.

🤼 Team

Ayudh (MSc Computer Science & Information Security Technology) - Versatile computer science skills, main focus on networked system design and cyber security

Abbas (MSc Embedded Systems) - Experience with wireless sensor networks and embedded networks. Minor in technology entrepreneurship

Divo (BSc Computer Science) - Seasoned fullstack developer

Marom  (MSc Artificial Intellgence) - Experience with real life computer vision applications, has worked on space grade code for a cube satellite through “Aster in space’’

Salaheldin (BSc Computer Science) - Experience in full-stack development and embedded systems, leadership experience as a technical student assistant for Internet of things course

Thomas (BSc Computer Science) -  Experience with user-oriented design, embedded systems and algorithmic problem solving, with a minor in entrepreneurship

Yunsu (BSc Computer Science) - MATLAB Developer Intern at ASML, focusing on performance optimization through data analysis, mathematical modeling, and developing advanced MATLAB solutions

Yusef (BSc Computer Science) - Backend engineer at bol.com, with experience (and interest) in all things tech

https://github.com/Ayudh-M/NorthStar