Passenger flows in stations are fluctuating and dependent on many external factors such as events, weather, holidays, etc. Tracking and estimating the number of people in the infrastructure is therefore very often complicated.
Therefore, not knowing the passenger flows in its stations can cause many problems, whether it is in terms of security, passenger comfort or even the resources deployed by the station operator.
There are several types of low-cost technologies to know the number of people in the infrastructure such as wifi tracking, infrared cameras, passive waves etc… The problem with these is the reliability of the data (which is in fact more statistics than reliable data).
Thanks to the technological progress in the field of counting, new technologies based on complex algorithms have appeared via video analysis obtained by 2D or 3D cameras.
Another interesting technology is laser LIDAR technology. This is the same technology used for autonomous vehicles (cars, trains, etc.) and allows for the scanning of large areas such as platforms or station halls.
Each station has a different infrastructure with its own challenges in terms of coverage: high ceilings, large areas to be covered, no internet coverage, etc. So using only one type of technology to equip a station or a network of stations seems complicated and non-optimal.
With software, engineering studies, experience and know-how, it is possible to use these types of technologies together to optimise the coverage of a station (both in terms of cost and performance).
Once the station is covered, a number of interesting features will be possible such as:
- Knowing in real time the number of passengers in the station and its different sections
- Knowing how many seats are free and where they are located
- Manage the cleaning of sanitary blocks (by getting an alert after a certain number of passages)
- Optimise staff resources
- Manage security in the infrastructure and on the platforms
- Knowing the number of people in the shops and malls
- Maximise advertising revenue