Augmenting Smart Cities with AI Driven Business Intelligence for Real Time Governance
Keywords:
AI Driven Business Intelligence, Smart Cities, Real Time Governance, Predictive Analytics, Urban Data, Explainable Ai, Citizen Engagement, Iot Integration, Block chain In Governance, Data Privacy, Algorithmic Bias, Sustainable Urban Planning, Resource Optimization, Urban Resilience, Smart City InfrastructureAbstract
Recent advancements in urban development requires rapid innovations in the data-driven governance frameworks. This paper looks at how AI-driven Business Intelligence (BI) systems expands the potentials of the smart city and responsive, real time, and predictive governance. AI-empowered BI systems perform sophisticated real time analyses of data generated by IoT sensors, public I infrastructures, and urban IoT, providing decision analytics in real time in multiple domains including traffic control, energy distribution, waste disposal, and public safety. It Synergizes the varied systems and decision frameworks to build analytical systems. It improves governance transparency and citizen engagement. It allocates resources efficiently while optimizing urban resilience. It solves urban governance challenges of data sustainability, algorithmic bias, and infrastructural unsophistication. This paper reviews the governance of urban AI, integrating emerging paradigms of Explainable AI (XAI), cross-governance with blockchain, and the convergence of AI and IoT. This paper serves as the research base for urban policymakers, planners, and technologists to build galvanizing AI-BI systems.
