Cities Get Smart with Artificial Intelligence

Today more than half of the world’s population lives currently in the urban areas, and this number should rise to two thirds by 2050. Rapid urbanization cause problems like pollution, traffic, and crime.

Municipalities can no longer afford to ignore digital technologies in order to enhance performance, well-being, and engagement with citizens. Whether it is through energy, transport, water, health care, or waste, the transition from city to smart city lies in the intelligent use of public data and ML to enhance Public Services. Day-to-day living of inhabitants can become more comfortable thanks to the technological advancements such as AI, machine learning, and the internet of things (IoT).

The Spirit of the City: Capturing Network-Generated Data for Better Cities Watch Video

Challenges

  1. Cooperation – For cities to truly leverage the benefits of the AI and use its potential, it is necessary to change the mindset. People need to be well informed and educated in order for the transition to be smooth
  2. Privacy – Billions of devices are creating data daily that are further analyzed by AI platforms. With facial recognition and cameras at a time where every search, every move, and every test informs a merchant authority or an insurer, consumers are (rightfully) concerned about topics like data privacy, ethics, and responsible AI.

 

High-Value Use Cases

Transportation, parking, and traffic management: Road surface sensors or closed-circuit television cameras incorporated into parking spots allow cities to create a real-time parking and traffic maps, reducing the the time drivers have to wait to find an empty space or be in traffic. Smart transportation also includes public sector, and thanks to AI, there are lots of opportunities for improvement of public transit (like advanced predictive maintenance, for a start).

Manufacturing and farming: Machine learning techniques allow for the prediction of everything from environmental impacts on crops to unforeseen supply failure based on large swaths of proprietary (e.g., historical data) and third-party data (e.g., weather patterns).

 

Smart Police and crime prediction: Cameras and sensors can increase security in the cities and surrounding neighborhoods. The cameras are able to identify people who are smoking in the forbidden areas, track movement of all registered vehicles, or even monitor crowd density and cleanliness of public spaces. Thanks to the historic data available from different departments of the city, police can predict category and intensity of crimes depending on a neighborhood.

Smart Waste management: Installing sensors on waste bins can make waste collection more efficient. Authorities can receive notifications when the bins are about to be filled and ensure reducing of operational costs by eliminating unnecessary pickups, providing dynamic collection routes and schedules for optimization of waste management.

 

Dataiku for Smart Cities

Dataiku is the platform democratizing access to data and enabling organizations to build their own path to AI. Dataiku enables smart city initiatives by making AI accessible to a wider population (not just data scientists), facilitating and accelerating the design of machine learning models, and by providing a centralized, controlled, and governable environment, Dataiku allows massive scaling of AI efforts.

 

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