IoT-enabled environmental monitoring and adaptive governance for ecotourism areas

Ecotourism areas require timely and adaptive environmental governance to balance ecological conservation with increasing tourism activities. However, existing studies primarily emphasize environmental sensing and data acquisition, while insufficient attention has been devoted to integrating real-time monitoring with dynamic risk assessment and adaptive decision-making within a unified governance framework. To address this gap, this study proposes an IoT-enabled environmental monitoring and adaptive governance framework that integrates distributed sensing, state-space modeling, environmental risk assessment, and multi-objective optimization. A key novelty of the proposed framework lies in its integration of cyber-physical environmental monitoring with adaptive governance through a unified analytical architecture capable of supporting continuous environmental assessment and management optimization. The framework is validated using a hybrid research design that combines empirical observations from 12 ecotourism sites collected during 2018–2024 with calibrated simulation-based analyses. The results demonstrate that IoT deployment substantially improves monitoring efficiency and estimation accuracy, reduces environmental risk, and enables low-latency system responsiveness for real-time environmental management. These findings indicate that the proposed framework enhances monitoring precision, supports adaptive ecological decision-making, and provides a practical technical pathway for intelligent and sustainable governance of ecotourism areas.