• International Project Development and Management: INTALA LAB specializes in developing and managing various agriculture and livestock projects on an international scale. Our team members, experienced in their respective fields, collaborate with international stakeholders to produce innovative solutions.

• Academic Support and Assistance: Undergraduate and graduate students working in our laboratory contribute to their academic development while gaining hands-on experience by directly participating in projects. Additionally, our graduate students not only play active roles in projects but also assist in laboratory courses at our university.

• Education and Awareness: To accelerate and raise awareness about digital transformation in the agriculture and livestock sectors, our laboratory organizes educational and informational activities. Through seminars, workshops, and training programs, we acquire knowledge and skills on current topics from stakeholders in the industry.

Bees have played a critical role in flowering plants for over 140 million years. Among the most important insect species for pollination are honey bees. Furthermore, honey has been regarded as a source of healing both historically and in the present day. Despite Turkey and Argentina being among the top three global honey producers, they have not been recognized for delivering high-value end products due to the impact of honey fraud on the international market. The aim of this project is to create a smart value chain driven by quality-based, market preferences and consumer demands, recorded with transparency throughout the process from beekeeping sites to the processing of collected honey, thereby building trust between buyers and sellers. To tackle global and local challenges, a transparent, efficient, and effective honey value chain is necessary to achieve a dynamic and responsive honey-food system.

The primary objective of TOP4HoneyChains is to develop a system that will enable smart honey value chains in Turkey and Argentina, using a transnational approach with Polish partner UEKat and Latvian partner LBTU. In summary, the main goal of the TOP4HoneyChains project is to enhance the effectiveness of traceability and transparency to achieve smart honey value chains.

Optimization of ICT-Supported Bee Collecting Sites and Beekeeping Routes for Efficient Honey Production (BEE-OPTECH4Honey) aims to elevate traditional agricultural practices to an industrial level and create better marketing opportunities. To this end, the project plans to validate a system using real-world data that identifies ideal locations, potential nectar areas, and the most efficient migration routes through technological approaches such as decision support models, optimization models, and GIS-based image processing models.

As an integrated system, BEE-OPTECH4Honey aims to combine digital technologies, an optimization model, and a GIS-based image processing model to provide users with access to and management of production process data. This prototype will be tested in a simulated environment that evaluates the system's performance based on specified criteria, demonstrating the effectiveness of the proposed system.

The primary goal is to offer a comprehensive and reliable solution to facilitate the production of high-quality beekeeping products while enhancing the efficiency, productivity, and sustainability of beekeeping operations. This validation process aims to establish a robust foundation for the reliability and validity of the proposed system, ensuring its applicability in real-world scenarios.

Our laboratory's founder and lead researcher, Dr. Şahin Aydın, has been accepted into the “InsectAI – Image-Based Artificial Intelligence for Insect Monitoring and Protection COST Action." The InsectAI COST Action aims to support insect monitoring and protection on both national and continental scales to understand and combat declines in common insect species. The action will bring together a critical mass of researchers and stakeholders in image-based insect AI technologies to guide the research agenda, build research capacity across Europe, and support implementation. 

The InsectAI COST Action will organize workshops, conferences, short-term scientific missions, hackathons, design sprints, and more across four working groups. These groups will address how to best meet societal needs with image-based insect AI technologies, support innovation in image collection hardware, develop standard approaches for image processing, and create new data analysis and integration methods to transform data into actionable insights. Dr. Aydın will lead research activities in the Image Processing and Data Analysis and Integration working groups as part of this action.

This project aims to create a holistic platform by integrating software components based on open data processing models to support precision agriculture and develop an open data platform in agriculture. An important goal is also to ensure the collection of product-specific data from field stakeholders by creating data collection forms based on modern software design patterns using ontologies specific to agricultural products. The project aims to develop a web-based open data platform by integrating semantics and syntax to publish structured data specific to agricultural products for all stakeholders and to generate agricultural knowledge using modern computer science techniques such as machine learning, deep learning, and artificial intelligence.