Congested city? Here’s an AI-based public transport solution

One of the major components of smart cities is the optimized usage of transportation systems. As more and more people around the world migrate to cities and governments scramble to find the right ways to manage them, urban congestion becomes a serious issue.

Several attempts have been made to come up with solutions to this problem and one of them is from the London-based NumberEight. The company aims to solve global urban congestion problems by developing technologies that encourage people to take public and shared mobility services as opposed to single occupancy vehicles.

Speaking to asmag.com, Abhishek Sen, CEO and Co-founder of the company, said that Numbereight’s artificial intelligence software leverages low-power smartphone sensors to detect and predict passenger movement across various modes of transport.

“This helps public transport operators, like rail, get an end-to-end journey understanding, giving passengers the feeling that their digital devices are chaperoning them around as opposed to the other way around,” Sen said. “We are initially focusing on the rail sector in the U.K. and look to further expand to other European markets.”

“We are initially focusing on the rail sector in the U.K. and look to further expand to other European markets.”

Using artificial intelligence for smart transport

Simply put, Numbereight processes real-time sensor data from smartphones and wearable devices without the need for any other external hardware. But what makes its solution special is that it leverages fundamental artificial intelligence (AI) techniques to model passenger movement across several modes of transport, thereby identifying key transition points such as waiting at the platform to getting on the train.

According to Sen, his experience working with some of the largest technology companies has helped to create a solution that gets the job done with minimum botheration to the user.

“Doing these tasks accurately and without hampering the user’s battery life is extremely challenging and our solution is up to the task,” Sen said. “We are confident of this because of our previous experience developing wireless and sensor fusion software at companies such as Apple and IBM and our previous academic experiences.”

Sen believes that further developments in AI technologies along with future interaction methods make for a very exciting future that encourages people to ditch single occupancy vehicles in favor of public and shared transport services.

Service economy trend to drive demand?

Overall, the idea of leveraging AI and sensor fusion techniques to understand and predict passenger movement does sound exciting and promising. But there are several factors to consider when analyzing the potential demand for the product.

To Sen, global trends such as the service economy, with companies like Netflix, Uber and Spotify, massive urban congestion and a passenger demand for convenient and personalized transport could be the primary reasons for demand. “By focusing on the mobility and transport sector, we are uncovering a whole range of use cases of our software that will greatly improve the passenger experience,” he said.

Asked about how the idea for the product came up, Sen talked about a project that inspired him.

“During my Master’s thesis at TU Delft in the Netherlands, I developed a system that used artificial intelligence and smartphone sensors to automatically generate smart music playlists based on a user’s current situation such as working, exercising, commuting and more,” he said. “I was tired of having to change my music every time based on my surroundings and so did my Master’s thesis on this problem. Since moving to London, we noticed the massive inefficiencies commuters face every day and we realized that our software could greatly improve the passenger experience by encouraging people to ditch their cars and switch to public transport.”