October 2, 2025

Mobility data privacy in AI: Ethics, safety, and trust

Mobility data privacy in AI is a defining challenge of our era, even as movement signals power smarter cities, safer transportation networks, and timely public health insights, enabling proactive traffic management, disaster response coordination, and resilience planning, and it requires privacy-by-design principles, ongoing risk assessment, and collaboration among engineers, policymakers, and communities.From traffic forecasting to emergency response, the value of location data comes with a responsibility to protect individuals’ rights, minimize exposure, respect autonomy, and ensure that benefits are distributed fairly across communities and across all stakeholders who contribute data, from municipal agencies to private partners.

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October 1, 2025

AI-based Traffic Forecasting: Predicting Peak Hours With AI

AI-based traffic forecasting is transforming how cities anticipate congestion, optimize routes, and plan infrastructure, delivering clearer signals for decision-makers about when and where to act and how mobility policy can evolve.By leveraging cutting-edge models and diverse data streams, practitioners move beyond simple averages to forecast peak-hour conditions, enabling proactive measures such as adaptive signal timing, dynamic lane management, and targeted traveler information campaigns.

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