01 Jul 2020
Train stations and data: The future is already here
The ‘station of the future’ is smart, connected and data-driven. By combining Wi-Fi and cellular connectivity, internet of things (IoT) sensors and other technologies, transit authorities can gather data and optimise operations. They can use data to develop schedules, adopt a proactive and preventive approach to maintenance, enhance security and transform the customer experience. As economies around the world recover from the COVID-19 pandemic, these capabilities will be some of the vital tools required for rebuilding customer confidence and ensure operational flexibility to meet any new contingencies.
Transit authorities around the world are already using connected technologies. Examples include smart ticketing, biometric security, asset monitoring and more. These are already improving safety, reducing costs and minimising service delays. The next step is to bring these different services and technologies together into a cohesive whole.
BAI Communications works closely with its partners to modernise their transport systems. Some of our solutions include using anonymised association data (gathered when a device connects to a Wi-Fi network) to help automate passenger counting, alleviate platform congestion, improve safety and gain insights into how passengers are traversing the subway system.
Using data to improve transit systems
With large numbers of commuters using transit systems daily, the need for visibility into ‘on-the-ground’ conditions to improve safety and operational efficiency is growing.
Most commuters carry a mobile device (typically a smartphone) that joins different Wi-Fi access points as it travels across the rail network. Transit operators can gather and anonymise the mobile association data each connection generates.
Combining this data with information from other sources within the system – such as smart cameras and sensor-equipped rolling stock – results in rich streams of information that authorities can use to optimise their operations. For example, the data helps authorities to predict, or to know:
- Which platforms are overcrowded?
- What are the effects of a service disruption?
- What happens during large-scale city events?
Automated passenger counts for optimal flow and route planning
Gathering real-time information on the number of devices within a subway system is difficult. It must be fast, accurate, and at sufficient scale to generate meaningful analytics. But digital connectivity makes it easy.
In the past, transit authorities would deploy workers once a year to count commuters entering and exiting stations manually, using clickers. This approach resulted in some inaccuracies during busy periods, was labour intensive and resulted in delays collecting and tabulating the data. It also didn’t take into account factors such as time of day, weather conditions, service delays and different station locations.
Using anonymised mobile association data, transit authorities, such as the Toronto Transit Commission, can access a detailed picture of passenger movements every 15 minutes. This data simplifies planning for day-to-day operations. It also informs surge planning – for cultural and sporting events – and contingency planning for fires or other disasters.
Preventing overcrowding and platform congestion
Accurate passenger information has many uses. Chief among them is managing overcrowding and platform congestion. Overcrowded platforms and stations can quickly become uncomfortable or even dangerous, whether due to service delays, inclement weather or other causes.
Transit authorities can use device association data to help manage such congestion more effectively, allocating resources such as support staff or extra vehicles to meet passenger needs. They can resolve crowding issues before conditions become hazardous. Future uses include using cameras and smart passenger gates to monitor traffic flows into and out of a station.
Access to this type of information can also help transit authorities proactively communicate information to passengers and provide regular schedule and progress updates to clear crowds as efficiently as possible.
In large cities like New York or London, there may be a dozen or more ways for a commuter to get from point A to point B, making it difficult for transport operators to optimise traffic flows.
Device association data can do more than present real-time information on foot traffic within stations; it can also identify patterns of movement through the entire network. By understanding the paths taken through the subway system, transit authorities can ‘nudge’ commuters towards the most-efficient routes. Passengers can enjoy a simpler, safer and faster trip, while the operators gain efficiencies of scale and can further optimise their services.
The importance of privacy
The starting point for data gathering is to address the profoundly and rightly held concerns many people have about companies and government bodies accessing their information.
BAI takes data privacy seriously, and we have implemented numerous security measures to protect the user information we gather, following industry best practices. Based on the number of devices connected, algorithms calculate overall ridership. All data is handled anonymously and in aggregate. We use salting and hashing to ensure all data is fully encrypted and obfuscated. While we do not store any personally identifiable information, we treat all our data with the same stringent privacy protections that would be required if we did.
Building a better future with data
These applications represent just a few of the capabilities data-driven systems provide. Other possibilities include:
- Individualised notifications: To inform commuters about service changes or interruptions to their chosen or most common trips.
- Video analytics: To transform video feeds into intelligent data to help protect passengers and staff across the entire network.
- Environmental monitoring: To monitor and improve air quality, reduce noise pollution, and more.
- Preventive maintenance: To massively reduce costs and service disruptions.
We will explore these solutions in future blogs. For now, our focus is on further developing our suite of sophisticated data solutions to deliver on transit optimisation such as cost reduction, efficiency and customer experience improvements.