How Data Science is going to propel us into the era of Living Cities
You have probably already heard of the concept of Smart City. According to Wikipedia a smart city is “an urban development vision to integrate multiple information and communication technology (ICT) solutions in a secure fashion to manage a city’s assets. […] The goal of building a smart city is to improve the efficiency of services and meet residents’ needs.” Embedded sensors all around the city are relaying data back to a city management team or organization. For a data scientist a city is a gold mine of data.
Whether people know about it or not, cities around the world are already turning into smart cities. United-States cities, such as San Francisco, Los Angeles, Chicago, New-York and many more available at Data Gov have started making their data publicly available since 2009.
In other cities such as Barcelona sensors around the city now transmit relevant information in real-time. The city has light and metal sensors that detect if a parking spot or loading area is occupied. This data helps motorists find parking, but it also provides data about parking patterns, helping officials improve management of urban mobility. Barcelona also installed LED lighting technology reducing cost and pollution; the lights detect motion but also gather environmental information such as humidity, temperature, pollution and noise. (source: Ten reasons Why Barcelona is a Smart City)
City data is used by private and public organizations and even individual data scientists who wish to find insightful information within it and use that to find solutions that will have a meaningful impact on the lives of individuals in the city.
For instance, I recently participated in the Bayes Hack 2016 hackathon where lots of governmental data had been made available for people to come up with solutions to important problems such as preventing hazardous freight accidents. Code for America also encourages the analysis of this data for Social Good. And companies like PredPol, IBM or Hitachi use publicly available crime data to build crime predicting models.
As a simple (and maybe obvious) diagram this is what the system looks like:
A city can be broken down into four basic elements: Transportation, Safety, Infrastructures and Environment. Each one has sub-elements. Transportation has walking, wheelchairs, bikes, motorcycles, cars, buses and trains; and also streets, bridges, railways, etc. Safety includes police departments, fire departments and also construction crews that maintain city infrastructures; transportation of hazardous material and keep air and human resources clean. Infrastructure has houses, apartments, bridges, sport infrastructures and parks, etc. Environment is about how clean the air and water is for Nature, keeping the city in balance with Nature and also minimizing the negative impact of the city on the world environment.
By answering questions related to the four elements we are solving the cities problems by understanding what data to gather, how we can analyze it and most importantly how we can take action. This will help us come up with an automatic analysis method to bypass the middle-men in the smart city system: Data Scientists & City Officials.
Cities will become Living Cities.
The diagram for a living city would then look like this:
And if I were to use the Wikipedia definition of a Smart City for my concept of Living City it would be this:
“A Living City is an urban development vision to turn a Smart City into an “intelligent” entity capable of self-analyzing the data generated by its sensors and taking self-actions to satisfy the needs of the individuals living in it.”
Just like for smart cities there are different stages to turning a city into a living city.
The first stage will be immediate analysis and providing insight to city officials. In Transportation we can predict when streets are wearing out. For Safety we can deploy police officers according to a hotspot map. For the environment we can predict when to pick up trash and maintain open-spaces. This is already being done in many big cities around the world.
The second stage will be immediate analysis and human response. This would be sensing or anticipating an issue and sending humans to solve it. For instance, a road needs to be repaired and workers are immediately sent on site or a person is being attacked and the police are immediately sent to the area.
The third and last stage will be immediate self-analysis and self-response. This third stage requires new revolutionary technologies. The idea is that if a person is being assaulted in the street then the city might protect them with a sort of bubble while it surrounds the attacker, with say quadcopters, identifying him and following him until human police officers arrive on site.
Once this final stage of living cities is reached then I think that cities themselves will no longer change in concept. However they will change with the future evolution of the nature of our technologies. Imagine a city made of technologies that are no longer going against nature but that are beneficial to it. Trees that emit light at night on demand, streets that self-heal, filter water and dissolve trash, solar-surfaces that transform sunlight into electricity, bio-electric cars and bio-degradable waste. This will be the ultimate evolutionary stage of our society. By then our world and even our very human nature will have radically changed. (I will further explain this concept in an article on the evolution of technologies in the city, what lies beyond the Singularity.)
To put things into perspective I’ll share with you what I believe San Francisco could look like with technologies that exist today. First off, the streets would be made of solar roadway panels (Solar roadways), among many actions they would generate electricity with solar power, filter rain water, provide emergency warning systems, change the street signs on the ground with LEDs to indicate accidents up a head or changes in the street plan, and most importantly sense their environment. With solar roadways we would have extensive knowledge on how many cars are on any given street at any time, if someone is in danger or if there was an accident. The panels could easily be replaced in case of damage and this could be done automatically thanks to self-driving cars (Self Driving Car). Predicting degradation infrastructures, self-healing concrete (Self-healing Concrete) and 3D printing concrete (http://www.totalkustom.com/) and steel (MX3D) would allow the city to maintain a safe status. Predicting crime, fire hazards and accidents would permit the city to deploy necessary human’s resources where they will be most needed. Satellite imagery and individuals relaying sensitive information would allow the city to deploy efficient public transportation, also improving safety and environment. Sensors in trashcans would indicate bins that our full (Smartbin). Sensors in city drains or sidewalks would indicate pollution levels and air filters would indicate levels of air pollution. Sensors at the corner of streets could measure weather data but also light intensity in city and noise. With just this San Francisco would be a new revolutionary city.
All this thanks to the amazing technologies we are developing and the power of data science.