References

Artificial Intelligence-Supported NVA (Non-Value-Added) Analysis System in Production Lines

As part of this project, footage from CCTV cameras positioned in TOFAŞ Automobile Factory Inc.'s production areas will be processed using AI-based video analytics to track operator movements. The system will automatically classify value-added (VA) and non-value-added (NVA) activities in production processes, reducing cycle times and increasing productivity. The model will operate in real time, providing instant improvement opportunities, and will also provide detailed performance analysis and process optimization based on historical records in offline mode.

Artificial Intelligence-Supported Proactive OHS and Field Inspection System

The developed system analyzes CCTV camera footage in real time using advanced artificial intelligence and computer vision algorithms to automatically detect safety and security violations. The system can identify various scenarios with high accuracy, including irregular behavior on-site, unauthorized area violations, dangerous situations, detection of personnel with or without helmets, and irregular behavior. Each detected violation is instantly communicated to the responsible personnel, along with a location and timestamp, along with a detailed description of the incident.

Artificial Intelligence and Thermal Camera Based Open Area Temperature Change and Widespread Early Warning System

The AI- and Thermal Camera-Based Open Area Temperature Change and Early Warning System is an innovative security solution that monitors temperature increases in real-time, particularly in high-risk areas such as coal stockpiles and dumpsites. Data collected by thermal cameras is continuously evaluated by an AI-powered analysis engine to identify potential heating trends, abnormal temperature increases, and pre-fire symptoms with high accuracy. The system sends instant alerts to the relevant teams when critical thresholds are reached, enabling rapid response. This minimizes fire risks and significantly enhances the operational safety and sustainability of the business. This product offers a scalable and reliable early warning solution for industrial facilities and energy production areas.

SSB AHLAT Project

As part of the SSB AHLAT Project, an innovative border surveillance system based on Swarm UAVs and artificial intelligence was designed and implemented to effectively ensure border security. The UAV system developed as part of the project integrates artificial intelligence, deep reinforcement learning, wireless communication technologies, FANET structures, and feature recognition algorithms, creating a multi-layered security architecture. This integrated system provides continuous, autonomous, scalable, and highly accurate surveillance at the border.

Artificial Intelligence-Based Glass Breaking Test Automation System

An AI-based glass breakage test automation system has been developed to fully automatically assess whether tempered automotive glass meets the ECE-43 standard. The system analyzes the resulting fragments with high precision to ensure compliance with the standard. It also automatically counts the fragments and presents the results to the user through a detailed reporting module. This AI-supported infrastructure minimizes human error in testing processes, increases accuracy and repeatability, and develops a fast and reliable quality control system that can be integrated into production lines.

Yapay Zeka ve Bilgisayarlı Görü Tabanlı Makine ve Personel Verimlilik Takip Sistemi

The AI ​​and CV-based Machine and Personnel Productivity Monitoring System offers an advanced solution designed to identify performance issues in personnel-operated machinery in factories in real time. Footage from CCTV cameras is analyzed with AI algorithms to instantly assess personnel movements, machine interactions, and operational flow. The system automatically identifies productivity losses, downtime, inappropriate usage scenarios, and potential signs of malfunction, providing managers with meaningful insights that can enable rapid action.

Artificial Intelligence and Computer Vision Based Glass Quality, Measurement and Defect Detection Automation System

Our project, accepted within the scope of the TÜBİTAK 1711 Artificial Intelligence call, has been completed. The project, developed using computer vision and artificial intelligence technologies, provides highly accurate and uninterrupted quality control in flat glass production lines. Using advanced image processing algorithms and deep learning models, the system can analyze glass dimensions, hole locations, and surface integrity with measurement precision of up to 200 microns. Critical defects such as cracks, edge fractures, surface deformation, and geometric deviations are detected in real time, completely eliminating human-induced errors and standardizing production processes.

Artificial Intelligence-Based Glass Breaking Test Automation System

An AI-based glass breakage testing automation system has been developed to fully automatically assess whether tempered automotive glass meets the ECE-43 standard. The system analyzes the resulting fragments with high precision to ensure compliance with the standard. It also automatically counts the fragments and presents the results to the user through a detailed reporting module. This AI-supported infrastructure minimizes human error in testing processes, increases accuracy and repeatability, and develops a fast and reliable quality control system that can be integrated into production lines.

Web-Mobile Based Project and Purchasing Management System

The web- and mobile-based Project and Procurement Management System offers a user-friendly solution designed to enable organizations to manage all project processes and procurement operations through a single, centralized platform. The devolved system increases operational efficiency by digitizing critical workflows such as project planning, task tracking, budget management, bid collection, procurement approval processes, and document management. Real-time notifications, flexible role and authorization definitions, comprehensive reporting tools, and mobile access support enable users to make rapid decisions from anywhere.

CAPITAL GLASS

Artificial Intelligence and Computer Vision Based Machine and Personnel Productivity Tracking System

The AI ​​and CV-based Machine and Personnel Productivity Monitoring System offers an advanced solution designed to identify performance issues in personnel-operated machinery in factories in real time. Footage from CCTV cameras is analyzed with AI algorithms to instantly assess personnel movements, machine interactions, and operational flow. The system automatically identifies productivity losses, downtime, inappropriate usage scenarios, and potential signs of malfunction, providing managers with meaningful insights that can enable rapid action.