1) "A New Distance Education Model and Application Platform in Higher Education" (TÜBİTAK 1001):
In this project, it is aimed to develop a distance education platform to be used by higher education institutions across the country. Within the scope of the project, a model will be created first and then a prototype system will be implemented on 16 universities. The features of the system to be developed are briefly as follows: Each institution will be able to create the curricula of the departments in their units in the system proposed through the web. Later, weekly virtual courses can be created for the courses in the plan and other training support materials (documents or videos) can be published on the platform. Access to live broadcast lectures or digital materials; student, group, class, program, department, faculty, university or everyone can be managed at scale. Another benefit of such a platform is that the curricula and course contents that are open to everyone are kept in one place and all universities have access to the course contents.
2) "Development of a Customized Traffic Planning Tool for Sakarya City by Processing Multiple Camera Images with Evolutionary Neural Networks (CNN) and Machine Learning Techniques" (TÜBİTAK 1002):
The purpose of this study is to process the video data with a software system obtained from cameras mounted for observation purposes at the intersections, to classify the vehicles passing through the intersection, to find their speed and to determine the intersection exit directions with high accuracy. The software to be developed within the scope of the study will be able to make city traffic analysis from the online outputs produced by the system or the data obtained can be used as input for simulation software tools (eg PTV Vissim). The simulation tools can give accurate results only with the correct statistical data. In this respect, this study is important for healthy city traffic planning. Some preliminary studies were carried out within the scope of the project and submitted to Sakarya Metropolitan Municipality (SBB). SBB, selected among the cities of smart city vision application, showed an interest in the study and decided to support it within the scope of traffic and signaling projects. The outputs of the project will directly contribute to the city's traffic planning and indirectly, improving the quality of the city's living space will contribute to the reduction of emissions and traffic noise. In this framework, it is aimed to increase the cooperation between Sakarya Metropolitan Municipality and Sakarya University by using current technologies. For the online video processing system, artificial intelligence and machine learning techniques will be used. The data processing unit will be developed on the basis of convolutional neural networks (CNN: Convolutional Neural Network) and vehicle recognition and classification training will be conducted using existing images.
