In the bustling heart of Bucharest, a new data-driven approach is revolutionizing the way industrial sites and warehouses are selected, promising significant commercial impacts for the energy sector. Marin-Mihail Patru, a researcher from the National University of Science and Technology POLITEHNICA Bucharest, has developed an open-source framework that leverages freely available geo-spatial datasets and advanced GIS tools to optimize site selection.
The framework, published in the Journal of Industrial Design and Engineering Graphics (Revista de Proiectare și Grafică Industrială), utilizes datasets such as OpenStreetMap, CORINE, DEM, and Sentinel, combined with GIS tools like QGIS and Python. This powerful combination allows for a multi-criteria decision analysis (MCDA) that considers user-defined weights, budget constraints, and continuous updates from satellite data. “This approach not only identifies suitable locations based on terrain, infrastructure proximity, and land availability but also ensures that the process is low-cost and replicable,” explains Patru.
The implications for the energy sector are substantial. Efficient site selection can lead to reduced operational costs, improved logistics, and enhanced supply chain management. By using remote sensing, GIS, and optimization techniques, the framework provides a flexible system for real-time, data-driven decisions. “This is not just about finding a piece of land; it’s about finding the right piece of land that aligns with your strategic goals and budget,” Patru adds.
The framework’s ability to continuously update with the latest satellite data ensures that the information is always current, allowing for dynamic decision-making. This is particularly valuable in a rapidly evolving urban landscape like Bucharest, where infrastructure and land use can change quickly.
The research highlights the potential for similar frameworks to be developed in other cities and regions, fostering a more efficient and data-driven approach to industrial and warehouse site selection. As the energy sector continues to grow and evolve, such tools will be invaluable in optimizing operations and reducing costs.
Patru’s work is a testament to the power of open-source tools and freely available data in driving innovation. By making the framework open-source, he invites collaboration and further development, ensuring that the benefits of this research can be widely shared and built upon.
In an era where data is king, this research offers a compelling example of how data-driven decision-making can transform industries. As the energy sector continues to seek ways to optimize operations and reduce costs, tools like this will play a crucial role in shaping the future of industrial engineering.