Smart cities use AI, IoT sensors, and big data to predict traffic, crime, and pollution before problems occur.

AI traffic models like LSTM analyze road sensors and GPS data to predict congestion 30-60 minutes in advance.

Adaptive traffic lights adjust timing based on vehicle flow, reducing commute times and fuel consumption.

Predictive systems achieve up to 95% accuracy in forecasting traffic patterns and congestion spread.

AI policing tools analyze crime data to identify hotspots and predict possible incidents with up to 85% accuracy.

AI CCTV and video analytics detect accidents, illegal parking, and suspicious behavior in real time.

IoT air sensors monitor pollutants like PM2.5 and predict pollution spikes linked to traffic and industry.

Smart city platforms combine weather, traffic, and industrial data to forecast air quality and issue alerts.

Cities like Singapore, Barcelona, and Dubai use predictive AI systems to improve safety, mobility, and sustainability.

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