Data-Driven Decision Support (Sustainable Dev.)
Technical Explanation
This cutting-edge service uses data analytics, modeling, and GIS to inform decisions for sustainable development. It might involve building digital dashboards of sustainability indicators, running simulations (e.g. traffic flows, air quality models) to guide urban planning, or employing AI to analyze big datasets (like satellite imagery or IoT sensor data) for smart city management. The goal is to support policy-makers or project planners with evidence-based insights that balance economic, social, and environmental objectives.
Main requirements
Increasingly required by smart city initiatives, sustainable development programs, and large corporations committed to ESG (Environmental, Social, Governance) goals. Needs robust data infrastructure – sources of reliable data, computational tools, and skilled analysts. It often entails scenario modeling (e.g. what development pattern yields lowest carbon emissions) and requires clear communication of results to decision-makers. The main requirement is collaboration between domain experts (urban planners, ecologists, engineers) and data scientists to ensure models and analytics address real-world questions accurately.