TEKNO MUCİTLER
DISASTER DETECTION AND WARNING SYSTEM
We are the Tekno Mucitler team, winners of first place in Turkey at the Codeavour 6.0 International Technology Competition. With our Disaster Detection and Warning System, we use sensors to detect disasters such as fire, flood, and earthquake, and artificial intelligence to count the number of people inside the building. In emergencies, we send real-time automatic alerts to the authorities to help save lives.
Sensor Warning System
Working with smoke, liquid and gyro sensors that detect fire, flood and earthquake, the system instantly signals dangerous and safe areas with laser lights.
People Counting with Artificial Intelligence
The artificial intelligence model analyzes live camera footage to instantly count the number of people inside and provides real-time data to the evacuation guidance system.
Data Logging and Instant Notification
The number of people detected is recorded in the database; in case of a disaster, an alert is sent to the authorities via IFTTT and the laser system is activated.
MISSION & VISION
Children Coding the Future
Our aim is to use technology to benefit human life. With our project, we develop smart solutions that save time in disasters and work for a safe future. By using our teamwork, coding and artificial intelligence skills, we are launching not just a project but an awareness movement.
Hardware Design
The physical infrastructure of our project was built on Arduino. Smoke, liquid, and gyro sensors detect various types of disasters, while laser modules visually mark safe and hazardous areas. The prototype, which is both low-cost and easy to install, was designed and tested by team members in real-life scenarios.
Artificial Intelligence and Counting System
Our PictoBlox-trained artificial intelligence model analyzes camera footage to count people entering and exiting the building. It works in sync with the evacuation guidance system by identifying how many people are inside. This count data is stored in the database and supports smart decision-making during emergencies.
Notification and Data Management
The number of people detected is instantly recorded in the database. When a disaster is detected, an automatic message is sent to the authorities via IFTTT Webhooks infrastructure. At the same time, lasers show safe exit directions with light. In this way, rescue teams can learn how many people are inside and which roads are safe.
TRAINING & PROCESS
Learn, Apply, Implement!
We received training on Arduino, sensors, artificial intelligence and data management. We learned how to create solutions to real world problems with the knowledge we gained at BİLSEM and our school.
DISASTER DETECTION AND WARNING SYSTEM
What Does Our Project Achieve?
Disaster Detection System
Our project detects fire, flood and earthquake with smoke, liquid and gyro sensors respectively. The system automatically activates when a disaster is detected, activates all other units and initiates a rapid response process for safety.
Automatic Notification System
In case of a detected disaster, an instant notification is sent to the authorities via IFTTT Webhooks, through SMS or e-mail. This ensures that emergency teams receive accurate information immediately, enabling rapid response and effective use of the evacuation system.
People Counting with Artificial Intelligence
The artificial intelligence model trained in the PictoBlox environment instantly counts people entering and exiting through the camera. This information is recorded in the database and transferred to the evacuation guidance system, allowing authorities to know how many people remain inside during a disaster.
Coding and Hardware Compatibility
The Arduino-based infrastructure is fully integrated with sensor modules and the PictoBlox software. The coding process was developed by the team members, and the system was thoroughly tested to ensure that each component functions as intended.
Instant Data Recording
The number of people detected by the system, sensor triggers and routing information are stored in a database. In this way, event history can be tracked, the accuracy of the system can be analyzed and advanced reporting can be done.
Laser Guidance System
Red and green lasers, which are activated in the event of a disaster, visually indicate safe exit routes inside the building. The evacuation process is accelerated by showing dangerous areas with red light and safe directions with green light.
A & G
Research and Development
The Disaster Detection and Warning System was developed based on scientific research and technical development processes. Problem definition, sensor and laser selection, artificial intelligence training and testing phases were carried out based on research. The entire system was successfully tested in terms of hardware and software.
Counting with Artificial Intelligence
The object recognition model trained on the PictoBlox platform counts the number of people in the building instantaneously with the camera. This count is used to determine the number of people staying inside during a disaster. The data obtained plays a critical role in the decision-making and routing functions of the system.
Machine Learning
Our model is based on a machine learning algorithm that has been tested in different scenarios to improve accuracy. The system, which works with visual data, provides high success in entry-exit counting. Improvement was made with regular data throughout the training process.
Laser Application
Arduino, sensors, artificial intelligence, and laser modules are seamlessly integrated to operate as a unified system. The laser system highlights hazardous areas with red light and safe exit paths with green light. Thanks to this technological harmony, the system remains portable, affordable, and scalable.
Our Team
He took part in the software side of the project. He trained the AI model in PictoBlox, connected the system to the database, and implemented the IFTTT integration.
She is the team's mentor. She provided technical and methodological support throughout the process. She guided the team in areas such as teamwork, presentation, and time management.
She took part in the hardware and coding aspects of the project. She ensured the system's physical operation by connecting smoke, liquid, and gyro sensors to the Arduino.
Blog
Project Journey & Insights
Başakşehir Fire Station Visit
To introduce our Codeavour 6.0 project, we visited the Başakşehir Fire Department of the Istanbul Fire Department, one of the best organizations in the world. We shared how our Disaster Detection and Warning System works and received feedback from the team.
Visit to Istanbul Provincial Directorate of National Education
After our first place in Codeavour 6.0 Turkey, we met with Mr. Murat Mücahit Yentür, Istanbul Provincial Director of National Education. We introduced our project, shared our competition process and thanked them for their support to education.
Visit to Gaziosmanpaşa District Governorate
After our first place in Codeavour 6.0 Turkey, we visited Gaziosmanpaşa District Governor Mr. İskender Yönden in his office. We introduced our project, shared our award and thanked our district governorship, whose support we have always felt.
TEKNO MUCİTLER
Ready to Discover the Project?
This innovative project we have developed as Tekno Mucitler aims to transform technology into benefits for human life. Check out the details of this system we created with the support of Arduino, sensors and artificial intelligence, and get inspired by us!