INTELLIGENT FORECASTING OF ENVIRONMENTAL RISKS IN CIRCULAR ORGANIC WASTE MANAGEMENT SYSTEMS

Abstract

An intelligent system for forecasting and integrated assessment of environmental risks in circular organic waste management systems is developed with a focus on the municipal governance level. The proposed approach is based on the integration of multi-source data flows from sensor networks, geographic information systems, public registries, municipal information platforms, and utility services into a unified analytical and predictive framework. A structural–functional model of the intelligent system is constructed as a multi-layer architecture that combines data acquisition and aggregation modules, an analytical–integration layer, a predictive modeling block, an environmental risk assessment module, and a decision support system, complemented by feedback, adaptation, and learning mechanisms. A structural-logical model for the integrated assessment of environmental risks is developed to formalize the forecasting of hazardous events by combining probabilistic estimation of event occurrence with quantitative evaluation of potential environmental impacts. An integral risk index is proposed as a unified multi-factor indicator of environmental hazard, enabling standardized risk measurement, classification of risk states, and their transformation into formalized management decisions. A risk-oriented categorization logic is implemented to support scenario-based response strategies and adaptive management processes. The obtained results establish a coherent methodological foundation for building intelligent environmental safety systems within the framework of circular economy and digital governance. The proposed models provide systemic integration of forecasting, analytics, risk assessment, and decision support, forming a unified management contour for organic waste systems. This creates practical preconditions for the implementation of risk-oriented management strategies at the community level, strengthening the ecological resilience of municipal infrastructures and supporting scientifically grounded digital transformation of environmental governance processes.