Our planet is urbanizing at an unprecedented speed. More and more people are moving to urban areas, and especially in Asia, megacities have reached an unimaginable scale compared to cities in the West – spanning to upwards of 60 million people.
The United Nations has estimated that more than half of the 4.5 billion Asian people will live in cities by 2026 – driven by reasons such as a better quality of life, access to better services, and a better job market. However, such rapid urbanization has generated tremendous economic and societal challenges regarding transportation, energy, and safety and security. To counteract such challenges, AI has become the solution.
What is AI?
AI or “artificial intelligence” has various definitions and understandings but generally, it is identified as a digital computer or computer-controlled robot having the ability to think and perform tasks like a human. AI can also learn new tasks by itself (machine learning), which is why it is also called machine intelligence. While many fear that machines will take over when they hear such descriptions, the odds are high that AI will instead support the work of humans so that they can focus on more creative tasks. So readers, do not worry!
What is more important than fearing a Terminator-like apocalypse is that AI is fed with sufficient and high-quality data. As I learned a few months ago, it is not enough to feed it data. To make AI work, specifying the data to the problem you want to solve is vital. The data should be collected and taken from real-life examples and research must be conducted with appropriate methodologies.
While we still lack enough experts and researchers in the field of AI, it is also important to say that examples from the past may not speak for the presence and for the future, so to speak. Making a computer learn by itself but also constantly feeding it new data, therefore, becomes necessary.
In regards to reducing the economic and societal issues in megacities, examples of data can be statistics on how many people are using a subway station daily, how many free parking slots are available, or identifying the most congested roads.
Collecting data has become easier. These days, all major cities in Asia have surveillance cameras watching 24/7, and even the general public can have access to them via websites such as insecam.com.There are approximately 500 million cameras around the world, and this number is going to increase to a billion cameras within the next three years – making data collection through cameras, of which many stream in HD resolutions, possible.
Recently, China built “the world’s biggest camera surveillance network” with 170 million CCTV cameras nationwide and an estimated 400 million additional ones going online over the next three years.Using those cameras to collect data allows AI scientist, experts, and researchers to develop and build-up AI software, technology, and solutions to ameliorate the infrastructural, energy, and safety and security challenges in Asian megacities; and around the world. However, China’s system has also been quite controversial as the country is using it to impose a social point system on its citizens to identify who is a “good” or “bad” citizen – allowing them to identify who to prefer as a potential client, worker, employee, etc. But despite all the controversies surrounding camera systems, as we will see, they can also have some benefits regarding the collection of data.
Advantages of using AI in public transport
Everyone who has taken the subway during rush hour in Tokyo, Hong Kong, or Singapore knows that every passenger resembles a sardine in a can. Commuting has been sometimes, literally, painful, as every last passenger tries to squeeze into the subway. With more people moving to or living in urban areas, this situation is not going to change.
Famous for its businesses, fashion, cuisine, and culture, Tokyo is also renowned for its extreme rush hour traffic. The daily number of passengers taking the train in the Tokyo area is approximately 20 million people; which is more than the population of over 100 countries.
Yet, with transportation problems arising due to unpredictable traffic, human errors, or accidents, which are also increased by more and more people using subway systems, delays will become more frequent. In such cases, AI can help to avoid or predict the unpredictable.
AI can predict potential disturbances on the train or subway track, identify potential person accidents or train malfunctions, or exchange information across subway lines about delays and prevent further delays. AI can track passengers’ behavior to find alternative routes. On railroads, cameras and sensors equipped with AI technology can identify debris on tracks, potential hardware failures, or other malfunctions – allowing workers to respond quickly to errors. Accordingly, such cameras and sensors can also react promptly to detect accidents, medical emergencies such as the collapse of a person, or any other kind of emergency that require an instant response.
I can also imagine that AI will help to identify possible suicide attempts by identifying people who look like they are contemplating throwing themselves in front of a train. As countries such as Japan or South Korea have high suicide rates, AI may predict suicidal behavior and avoid such tragedies.
AI & traffic reduction
Traffic is a daily routine for many people living in Asian cities. Having lived in Tokyo and Jakarta, as well as having been to almost all major cities in Southeast Asia, I am not kidding when I say that I have spent much time standing in overloaded train cars. Of the top 10 most congested countries in the world, Thailand and Indonesia are the worst. In 2016, Thai people experienced the worst traffic jams – spending an average of 61 hours a year in traffic – while Indonesians spend on average 47 hours. To ameliorate the public transportation system and to reduce road congestion, many experts believe that autonomous or self-driving cars are the solution; as I learned at the first Japanese-German-French AI Symposium.
Human drivers naturally create traffic and research has shown that autonomous cars can control traffic flow by adjusting the style of driving. They do that by continually recalibrating their “understanding” of their surrounding by using several cameras and sensors. Researchers from Vanderbilt University (USA), Temple University (USA), and Rutgers University-Camden (USA) found that even a 5% increase in autonomous cars on the streets could reduce the stop-and-go traffic waves and the total fuel consumption by up to 40%.
While some experts say that autonomous cars will increase congestion, the reason for that is simple: Introducing self-driving cars to a system which is made for traditional cars will evidently cause some incompatibilities at the moment. Autonomous vehicles cannot communicate with conventional cars, and data is still not 100% enough to allow the car to work 100% accident-free. However, imagine millions of self-driving cars driving around in the cities of Asia like Will Smith’s car in the film I, Robot; this will surely make it easy to reduce traffic and avoid traffic accidents. Furthermore, with fewer traffic jams and cars on the street, carbon dioxide emission will decline.
Moreover, as more autonomous cars are on the street, taxi and other car services will be encouraged to offer more sharable transportation services. This would translate to people not owning their car but instead, relying on such car services.
For example, Dubai, which named itself the AI City-State of the Future, has stated in a video – showing the vision of the city for 2050 – that future cars will not be owned but shared. Also, Japan has begun testing autonomous taxis in Tokyo city for the upcoming 2020 Tokyo Olympics, which will make it easier for visitors to move from A to B.
Seeing myself going back to Asia many times in the future, I cannot wait to see a change happening soon. While I do enjoy the train rides even if they are packed, I would still prefer avoiding delays or being assured that I can get from A to B without having to worry about train breakdowns, accidents, or hours spent in traffic jams.