There is a lot of buzz about Connected Cars and how they will be soon cruising round our streets, but how about the millions of people who commute on buses and trains each day? Can they also benefit from the Internet of Things (IoT) “revolution”?
According to APTA (American Public Transportation Association) in 2016 Americans took 10.4 billion trips on public transportation. People board public transportation 35 million times each weekday! In comparison, according to Morgan Stanley in 2016 Uber completed 168,528 per day and Lyft had a daily average of 26,783 trips.
Summing up the numbers: ~200,000 car hailing daily trips in the U.S. compared to 35 million public transportation trips every day! Uber and Lyft together represent only 0.6% of transportation trips in the country.
Considering these astonishing numbers, why do we still see in any major city people looking at their phones tracking when Uber or Lyft drivers will arrive, and at the same time a few yards from them people at a bus stop just waiting, having no idea when their bus will arrive.
Why technology is not catching up with public transport? Why don’t we see many apps as good as Uber and Lyft for public transportation?
Most bus companies in the country have implemented Automatic Vehicle Location (CAD/AVL) systems to track their bus fleets using GPS, but not always this data is available to users, and when it is available, users still need to figure out exactly at which bus stop they are and in which direction buses are heading.
Not mentioning the Visually Impaired. Have you ever wondered how difficult it is for them to figure out if they are at the right location (they can’t read stop signs!), when their bus is coming and when to board?
Regarding service planning. Transit Agencies still have limited statistics about ridership to build their fixed route bus transit service as efficient as possible. Some are implementing Passenger Counter Systems, which is a great step forward, but still won’t answer questions such as: how long users wait at each bus stop before boarding? Which connections they use? How the weather can influence these statistics? etc.
We believe the Internet of Things can drastically change all of this. We are working with transit agencies to “sense” when users arrive at Smart Bus Stops, and automatically push text and voice notifications of bus departures serving that particular bus stop. Transit agencies can also anonymously collect very important usage statistics.
The visually impaired don’t need to do anything at all, as soon as they arrive at a bus stop they will hear notifications informing when their preferred routes will arrive.
Users can also benefit from other relevant Smart City Data around the bus stop such as particle matter or carbon monoxide emissions from nearby micro air quality stations, or information from bike sharing stations and much more.
When enough data is available Machine Learning will completely change the service planning process. The result: Users will have to wait less, service will be more efficient!