Buildings and Cities: Difference between revisions
descriptions the future of cities
(descriptions the future of cities) |
|||
Line 28:
=== The future of cities ===
*'''[[Efficient sensing]]:''' The proliferation of sensors poses the question of how to minimize the energy use related to capturing, sending and storing the data. ML can help recognize what is the most information, possibly on the edge, make sensing more efficient.
*'''[[Causal inference]] of policy interventions:''' The effect of policy interventions are often uncertain, and it is important to evaluate them to evaluate their effectiveness. Causal inference methods in ML can help observe the effects of policies from observational data.
*'''[[Assessing urban climate]]:''' Cities have an influence on their local climate -- which they tend to make hotter -- which has important implications for climate change mitigation and adaptation. ML can help investigate climatic processes in cities at high-resolution and how they related to the built infrastructure.
*'''[[Enabling nature-based solutions in cities]]:''' Nature-based solutions, for example planting trees, can provide multiple benefit including sequestrating carbon and providing cooling. ML can help assess what is the current vegetation in cities and pinpoint opportunities for planting trees.
*'''[[Predictive Maintenance|Predictive maintenance]] of public infrastructure:''' Public infrastructure, for example street lighting, can include a large amount of individual components that are difficult to monitor. ML can help predict which components are more likely to be dysfunctional to ease maintenance operations.
=== Urban transportation ===
| |||