SmartAirQ: A Big Data Governance Framework for Urban Air Quality Management in Smart Cities - Kaginalkar, Akshara; Kumar, Shamita; Gargava, Prashant; Kharkar, Neelesh; Niyogi, Dev (Frontiers in Environmental Science, 2022)
Rapid urbanisation across the world has put an enormous burden on our environment. Cities from developing countries, in particular, are experiencing high air pollution levels. Addressing the challenge, the new WHO global air quality guidelines and various nations are mandating cities to implement clean air measures. However, these implementations are largely hindered by limited observations, siloed city operations, absence of standard processes, inadequate outreach, and absence of collaborative Urban Air Quality Management (UAQM) governance. The world is experiencing transformative changes in the way we live. The 4th Industrial revolution technologies of Artificial Intelligence, Internet of Things, big data, and cloud computing are bridging gaps between physical, natural, and personal entities. Globally, smart cities are being promulgated on the premise of those technologies and data aid in improving urban services. However, in many instances, the smart city programs and UAQM services may not be aligned, thereby, constraining the cumulative advantage in building urban resilience. Considering the potential of these technologies as enablers of environmental sustainability, a conceptual urban computing framework ‘SmartAirQ’ for UAQM is designed. This inter-disciplinary paper outlines the SmartAirQ components: 1) data acquisition, 2) communication and aggregation, 3) data processing and management, 4) intelligence, 5) application service, 6) High-performance computing (HPC)-Cloud, and 7) security. The framework has integrated science cloud and urban services aiding the translation of scientific data into operations. It is a step towards collaborative data-driven sustainable smart cities.