The combination of the Internet of Things (IoT), cyber-physical systems (CPSs) and big data analytics is transforming the manufacturing and supply chain processes. As supply chains become more digitalized, it is important for logistics operators and all stakeholders to provide easy access to technology, adopt agile information technology, security and, more importantly, unite them under the same roof. Innovative solutions provide features such as planning, route optimization, capacity planning and traceability. Another benefit is less idle time. Decreasing the idle time improves the fuel consumption and economic efficiency of transport companies. The project focuses on designing new systems that can respond quickly to new adaptations and changes with improved, flexible solution methods. Thanks to cognitive solutions in the project, deliveries can be rescheduled to meet the increased demand for milk runs within the partnership. A physical object in the supply chain (cargo, vehicle, warehouse, parking space, other transport modes, systems, and so on) will be defined as cognitive logistic objects (CLOs). COG-LO will process massive amounts of heterogeneous data and present a cognitive framework for CLO to understand, predict alternatives and provide solutions for temporary events. Holistic access, operation control and advanced encryption methods will have their security and privacy measures strengthened in accordance with relevant laws and regulations, especially with General Data Protection Regulation (GDPR). The project will offer a cooperative and cognitive framework. Tools that will help the information exchange between CLOs will be provided, decisions will be taken after large amounts of data have been processed and partnership opportunities will be evaluated in this framework.

Road transport has various economic, environmental and social effects. The environmental effects include diminishing natural resources, land use, toxic effects on humans, and other issues arising from noise, accidents and greenhouse gas emissions (GHGEs). GHGE, carbon dioxide, nitrogen oxide and particle emissions, in particular, are especially important as they threaten human health directly, as in the case of air pollution, and indirectly, ozone layer depletion and global warming. In recent years, citizens of developed countries are demanding action to reduce these negative effects and clear city centers of the GHGEs. As a result, governments have begun implementing new regulations pertaining to the use of fossil fuel-burning vehicles. Consequently, alternatives such as solar energy, bio-diesel fuel, electric, liquefied natural gas (LNG) and compressed natural gas (CNG) have become more popular. In addition to these developments, studies that promote electric car use in logistics and provide new approaches have come under the spotlight in recent years. Electric cars are highly advantageous in cargo and passenger transport as they have zero GHGE emissions and a low energy cost. However, they have some disadvantages, such as high cost, limited range and long charging periods. It is possible to eliminate these disadvantages in logistics with efficient planning of electric vehicle operations. As such, the route planning for these vehicles has become more important. This problem has also entered the vehicle routing problem (VRP) literature as the electric vehicle routing problem (EVRP). The project will cover the EVRP with time windows (E-VRPTW) of an electric vehicle fleet.

The project aims for the correct prioritization of shipments with the use of an effective Material Flow System, and for a more accurate monitoring of bar-code labels on the products during the logistics warehouse operations through the utilization of the integrated dynamic image verification and analysis system, which will be developed in-house. For the project, Turkey’s first ever Smart Camera system will be designed, boasting a GPU Core and a 2.13 gigahertz Quad Core processor. With the embedded smart camera design, image processing applications can be run directly on the system thanks to its high processing power, without the need of expensive and large computers. The system can quickly process high resolution images with a single camera and scan moving bar-codes and QR codes which are located on different parts of the products.

The project is based on the principle of internet of objects, with an aim to have devices communicate with each other and with people to make decentralized decisions. The development of a tracking system with real time monitoring and intervention capabilities will make it possible to meet international standards and eliminate security vulnerabilities in transport activities.