Internet of Things and Digital Twins in Public Procurement: A Model for Smart Control and Corruption Prevention

The present report introduces a conceptual model for applying Internet of Things (IoT) and Digital Twin technologies in the process of awarding and implementing public procurement contracts. The model integrates structured data from the national e-procurement platform CAIS EOP with sensor data from the actual execution of projects, creating an interactive digital twin of each procurement procedure. Machine learning algorithms are used to analyze key risk indicators such as the type of procedure, selection criteria, estimated values, concentration of bidders, and deviations in deadlines and budgets. Bulgaria has a strong foundation for developing such a model thanks to the open data published by CAIS EOP and the possibility to export datasets in CSV and XLS formats. The forthcoming publication of data in the OCDS (Open Contracting Data Standard) format will further facilitate the development of analytical platforms, visualizations, and civic monitoring tools. The absence of Bulgarian integration into the Public Procurement Data Space (PPDS) provides a strong argument for the originality and necessity of a national-level model. The data can be used by institutions such as the Commission for Counteracting Corruption, the Commission on Protection of Competition, and the Cybercrime Directorate to analyze cartel practices and corruption risks, as well as by civil society organizations for independent oversight. This approach transforms public procurement oversight from a reactive process into an intelligent, predictive, and transparent system, strengthening trust and integrity in public spending.