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Safe Homeland

A collection of ML microservices and apps for enabling Open Source inteligence gathering

  • 113 Raised
  • 1 Juries


  • Poland


  • 2. Making the seas more secure
  • 3. Protecting our critical infrastructure



💎 Idea

Safe Homeland is a system designed to monitor our country in order to improve its safety. We aim to shorten reaction time of appropriate services when danger occurs. It's divided into 2 layers:

I Layer - satellites

Satellites data provides us amazing observation abilities. We decided to focus on critical infrastructure, images of places of interest are constantly analysed. If some abnormality is detected - the signal is sent to our system. There are 2 types of satellite alarms: marine alarm informing about unregistered boats around coastline (polish example: gas port in Świnoujście) and inland alarm focusing on airports, mines, power stations, rafineries (Polish example:  transport aircraft base in Powidz).

II Layer - citizens impact

Power of people is invaluable. We believe that reaction against dangers can be performed a lot of faster if we get the information from people. Many pairs of eyes are definitely better than none. Designed app allows citizens to send their own alerts. You can find fields such as: description, type, image and location when you notice something dangerous. Then algorithms calculate reliability and credibility of the application. If they exceed the threshold - notification goes to operator above. 

Notifications from both layers are checked by the operator. He has several options to perform, e.g. send a police patrol or send a drone.

🛰️ EU space technologies


🏦 Space for Defence & Security

We decided to primarily tackle ,,Protecting our critical infrastructure". We were impressed by the use of unmanned vehicles by the Ukrainian army and the Belarusian people in the attacks on Sevastopol and Machulishchi airfield. 

This showed us that there is a great need for protecting our infrastructure, as the ability to do high risk strikes behind enemy lines requires a great amount of recon, which can be denied.

🤼 Team

Our team is composed of experienced hackathon hackers and computer wizards that is set on improving our collective European future in this changing world.

Kamil Kowalczyk

Fullstack developer focused on the mobile space, AI/ML, designed and implemented the mobile apps for our project, also the closest person to the adult in charge in our team. Works profesionally at Limango and studies full time IT/ML at Silesian Technical University, where he works on reasearch papers.

Karol Rogoziński

The tamer of wild ML magic and the all-knowing detector of clouds in satellite photos. Together with Ola worked on integrating Cassini and Mundi datasets with our project. Professionally data scientist, analysing banking business cases.

Ola Jamróz

The Data Trailblazer and ML Sorceresses, together with Karol explored the European space datasets and developed uses for them. Experienced hackathon hacker and pitch maker.  

Kuba Forczek

Model implementer, logistics expert and python-glue aficionado, hooked up YOLO models to the database and configured CUDA acceleration for our ML microservices. Professionally - developer at Siemens and student of Warsaw University of Technology.

Grzegorz Koperwas

Fullstack and devops wizard, designed and implemented the admin application and set up the backend. Runs his own server and contributes to few open source project outside his studies in network security and professional work at STX Next.