Latest news with #urbanmanagement
Wall Street Journal
2 days ago
- Business
- Wall Street Journal
How to Get to Near High-Speed Rail—on the Cheap
Forget flashy bullet trains and gazillion-dollar tunnels: Alon Levy, a fellow at the NYU Marron Institute of Urban Management, says America's railways could reduce travel times and transform intercity trips with simpler, far cheaper fixes. In a new study, Levy and co-authors make the case that with a combination of smarter scheduling, new track switches that allow trains to approach stations at faster speeds and a fleet of modern electric trains, the Northeast Corridor connecting Boston to Washington, D.C., could be humming with near high-speed rail service. Imagine a Boston-to-New York City trip that takes about two hours—instead of the roughly 3.5 hours it can take today—for a fraction of the cost of prestige megaprojects.
South China Morning Post
30-05-2025
- Politics
- South China Morning Post
China's smart cities streets ahead, but same AI challenges apply the world over
Each night in the darkest hours, a fleet of drones patrols the eastern Chinese city of Nanjing, watching over potentially dodgy areas such as underground station exits and the riverside to deter any would-be criminals. Advertisement The nightly routine has been operating since last year, according to a report published in April by the city's police bureau, which detailed its use of artificial intelligence to plan patrol routes. According to the report, the AI puts a laser focus on patrolling Nanjing's blind spots – the areas generally ignored by human patrols. The city's experience is part of China's efforts to scale up the use of AI in urban management, to better handle complex challenges brought by the massive scale of city life and rapid urbanisation. The Chinese leadership has long viewed AI as a tool for transforming the economy and refining its governance, launching the 'smart cities' initiative and other programmes over the past decade. Advertisement Despite this rapid progress, analysts warned that China's AI governance faces challenges – including privacy protection and limited community involvement – that are mirrored in other parts of the world as governments race to adopt the technology.
