Track 1: AI for Smart Energy Systems |
Track 2: AI in Infrastructure and Urban Development |
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Intelligent energy forecasting
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Renewable energy integration
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Smart grid optimization
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Demand response systems
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Energy storage management
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Fault detection in power networks
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AI for energy trading
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Carbon emission reduction strategies
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Smart city planning
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Intelligent transportation systems
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AI in construction management
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Infrastructure resilience modeling
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Predictive maintenance of assets
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Digital twins for infrastructure
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AI in water and waste systems
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Sustainable urban design
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Track 3: Machine Learning and Data Analytics |
Track 4: Emerging Trends and Applications |
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Deep learning for energy applications
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Reinforcement learning in infrastructure
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Edge AI and IoT integration
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Big data analytics in energy systems
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Federated learning for smart grids
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AI-driven risk assessment
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Multi-agent systems in energy networks
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Data-driven climate modeling
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AI for hydrogen economy
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Blockchain in energy and infrastructure
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AI for disaster management
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Autonomous energy systems
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AI-powered environmental monitoring
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Robotics in infrastructure inspection
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Human–AI collaboration in energy design
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Policy, ethics, and governance in AI applications
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