PREDICTIVE MANAGEMENT AND ENSURING DIGITAL SUSTAINABILITY OF LOGISTICS PROCESSES OF TRANSPORT ENTERPRISES BASED ON CMS INTEGRATION INTO SECURE DIGITAL TWINS

Topicality. The article substantiates a conceptual approach to optimizing logistics costs of motor transport enterprises by integrating camera monitoring systems (CMS) into digital twins. The relevance of the study is driven by the need for digital transformation of logistics and the shift from reactive to predictive fleet management amid resource price volatility and geopolitical risks. The purpose of the work is to develop and validate a scientific-methodological approach to intelligent management of logistics costs based on the synergy of visual telemetry and dynamic modeling. The research applies methods of systems analysis, simulation modeling, and expert assessments. The following results were obtained. The architecture of a digital twin of the enterprise is formed, with CMS serving as the primary data source on vehicle movement, technical condition, and psychophysiological behavior of drivers. A predictive management matrix incorporating 13 key indicators (grouped into safety, operation, and economics categories) has been developed. A model is proposed that accounts not only for internal fleet parameters but also for external determinants (resource prices, weather conditions, regulatory requirements), enabling real-time adaptation of logistics operations. Conclusion. Validation results based on industry data (2022–2025) confirmed the economic efficiency of the approach. Implementation of the system yields a return on investment (ROI) of 277% in the base scenario with a payback period of 4–6 months. Sensitivity analysis under a pessimistic scenario (10% deviation of factors) demonstrated model robustness with an ROI of 134% and payback within 9 months. The practical significance of the work lies in providing specific recommendations for reducing transportation unit costs, minimizing unplanned downtime, and lowering risks, thereby contributing to the sustai nable development and investment attractiveness of modern transport enterprises.