AI-based Energy Forecasting for Net Zero Smart Cities
Date:
In this talk, I discussed how AI-driven energy forecasting is accelerating the transition toward net-zero smart cities by enabling more accurate, adaptive, and efficient energy management. The presentation explored key AI methodologies, including advanced time-series models, deep learning strategies, and hybrid AI techniques, designed to integrate real-time IoT grid data, weather information, and historical consumption patterns. I highlighted major challenges such as data integrity, model scalability, and cybersecurity, while demonstrating through case studies how AI significantly improves energy planning, distribution optimization, and supply–demand balancing. The talk emphasized AI’s growing role as a foundational technology for achieving sustainable, net-zero urban development. The talk can be found here.