SDGreen: A computational framework for advancing sustainable development goals in smart universities using IoT

• SDGreen: an IoT-driven framework for sustainability management in smart universities. • MAPE-K–based autonomic architecture for continuous SDG monitoring on campus. • Automated generation of sustainability indicators from real energy consumption data. • SDGreenSim: simulator for campus-scale communication and infrastructure analysis. • Validated using real building energy data and indoor mapping from a university campus. The 2030 Agenda for Sustainable Development promotes environmental protection, inclusive economic growth, and social inclusion. Universities play a key role in this global effort, contributing both to research that addresses sustainability challenges and to the development of environmentally responsible campuses. This paper introduces SDGreen, a computational framework designed to advance the Sustainable Development Goals (SDGs) in smart university environments. The framework adopts the MAPE-K (Monitor – Analyze – Plan – Execute over a shared Knowledge base) autonomic computing model to integrate Internet of Things (IoT) and Big Data technologies for the automatic collection, analysis, and generation of sustainability indicators. In addition, we introduce SDGreenSim, a simulator that estimates the communication and data infrastructure required for smart campus deployments. To validate SDGreen, we used real energy consumption data from sensors installed in university buildings to generate a sustainability indicator based on the GreenMetric methodology. The system also optimized sensor measurement intervals, achieving a reduction of at least 97% in the number of collected samples without compromising the monitoring of energy consumption trends. For SDGreenSim, we used geographic information system (GIS) data representing a large university campus to simulate sensor deployments and estimate the data volume generated per building. The simulation results can assist IT administrators in assessing whether the existing communication and storage infrastructure can support increased data demands or if capacity expansion is required.