Artificial Intelligence and Satellite-Based Infrastructure for Environmental Sustainability: Opportunities in the Context of Global Technology Ecosystems

The integration of artificial intelligence (AI), satellite-based communication infrastructure, and renewable energy systems represents a critical technological pathway toward achieving long-term environmental sustainability. Advances in low Earth orbit (LEO) satellite networks, intelligent energy management systems, and AI-driven analytics have enabled new approaches to environmental monitoring, risk assessment, and sustainable resource optimization. This paper explores a conceptual and simulation-based framework for applying AI-enabled satellite infrastructure to environmental sustainability challenges in Indonesia. By referencing technological ecosystems developed by leading global technology enterprises in the fields of electric vehicles, satellite connectivity, and intelligent energy systems, this study proposes an adaptable model suitable for developing countries with complex geographical conditions. A MATLAB-based simulation using artificial neural networks (ANN) is employed to demonstrate the feasibility of AI-driven environmental risk prediction using satellite-derived environmental indicators. The results indicate that AI-based models can effectively capture nonlinear relationships between environmental variables and sustainability risk indices. This study contributes a scalable and policy-relevant framework for integrating AI, satellite infrastructure, and renewable energy systems to support sustainable development strategies in emerging economies.