Guardian Angel-UAVs for Drowning Prevention

Drowning-Rescue: Tackling a Global Crisis with Autonomous Technology

Drowning is a devastating global issue, causing hundreds of thousands of preventable deaths annually and ranking as a leading cause of unintentional injury mortality. Current prevention methods, such as lifeguards, often face limitations in coverage, response time, and consistency, especially across vast beaches, busy pools, or unpatrolled natural waters like lakes and rivers. These gaps leave many at risk, highlighting a critical need for a more technologically advanced, rapid, and reliable water safety solution to augment existing measures and provide protection where none currently exists.

Drowning-Rescue addresses this challenge with an innovative system of autonomous Unmanned Aerial Vehicles (UAVs) powered by advanced Artificial Intelligence and computer vision. Our solution provides 24/7 vigilance by continuously monitoring swimmers using AI-driven visual tracking and deep learning to instantly recognize drowning patterns. Upon detection, the system alerts authorities and simultaneously dispatches a UAV to deliver a flotation device, drastically reducing response times. This modular system is adaptable for diverse environments—from beaches and pools to lakes and rivers—aiming to significantly enhance safety, support or replace traditional lifeguarding where needed, and ultimately save lives by making every aquatic environment safer.

Our Drowning-Rescue system will leverage a combination of terrestrial and European space-based data, information, and signals, including Galileo/EGNOS for high-precision UAV navigation and Copernicus for environmental context like water body mapping and weather conditions. This integration ensures rapid, accurate victim location and enhances operational planning, significantly boosting the system's effectiveness in time-sensitive emergencies and diverse environmental conditions.

The primary terrestrial data includes real-time visual feeds from on-site and UAV-mounted cameras, crucial for our AI-powered computer vision and deep learning algorithms to track swimmers and detect drowning patterns. This, combined with AI-derived information like distress alerts and victim coordinates, allows for immediate alarm triggering and autonomous UAV response, making Drowning-Rescue a robust, context-aware solution for enhancing water safety.

We are primarily addressing Challenge #2: Smart Emergency Healthcare Delivery. Our Drowning-Rescue system supports the healthcare ecosystem by acting as an ultra-fast first responder in acute drowning emergencies, delivering immediate flotation aid via UAV to prevent submersion and buy critical time. This rapid intervention is key to improving survival rates and reducing the severity of long-term health consequences associated with hypoxic brain injury.

Furthermore, the system enhances Emergency Medical Services (EMS) efficiency by providing early warnings and precise victim locations (via Galileo), enabling faster EMS dispatch and supporting Search and Rescue (SAR) operations. By mitigating the severity of drowning incidents, we aim to decrease related hospital admissions and the burden on healthcare facilities, while collected data can inform public health strategies, making Drowning-Rescue a vital link in the chain of survival for aquatic emergencies.

Our team is a highly qualified and dedicated group of researchers passionate about leveraging cutting-edge technology to solve critical public safety challenges and enhance healthcare outcomes. We bring a synergistic blend of expertise in AI, engineering, and research to the Drowning-Rescue project.

The core team members are:

• Ahmed Abdelrahim - Role: Chief Executive Officer & UAV Systems Lead

  • Bio: Ahmed is a Post-Doctoral Researcher with a D.Sc. in Process Metallurgy and an ongoing M.Sc. in Computer Science (AI), complemented by degrees in Mechanical and Environmental Engineering. He drives the project vision and spearheads the technical development of the UAV platform.

• Eslam Eldeeb - Role: Chief Technical Officer & AI Lead

  • Bio: Eslam is a Post-Doctoral Researcher holding a D.Sc. in Wireless Communications, along with M.Sc. and B.Sc. degrees in Communications and Electronics Engineering. He leads the development of our AI-driven drowning detection algorithms.

• Ahmed Elabasy - Role: Chief Operations Officer & Biomedical Tech Lead

  • Bio: Ahmed is a Doctoral Researcher pursuing a D.Sc. in Medical Science and Technology, with an M.Sc. in Biomedical Engineering and a B.Sc. in Communication and Electronics Engineering. He oversees operational strategies and the integration of biomedical considerations into the system's design and application. He is also responsible for sensor integration and communication systems development.