A MARKET LEADER IN INTELLIGENT MOBILITY
Currently 3 rail operators from 2 countries are already using OpenCapacity's capacity forecasting or performance analytics tools.
Collect, analyse, predict, display
OpenCapacity is a system to collect, analyse, predict and display the occupancy, accessibility and performance of public transport.
We measure passenger load by using existing public transport data sources, such as weight sensors, CCTV cameras, door sensors, and ticketing information. Cross-referencing these sources helps us strengthen the overall accuracy of passenger numbers.
Real-time information display
Our system provides real-time information on available space inside train carriages, buses, and other modes of transport to passengers and operators via information screens, mobile apps and dashboards.
This will allow passengers to better plan their journeys and travel more comfortably, as well as allowing operators to further optimise their systems.
Machine learning and predictive modelling
Displaying the occupancy of an approaching train is not enough. At large transport hubs many passengers will alight from a busy train, making room for others waiting on the platform.
It is therefore essential to analyse the data for patterns and cross-reference it against other data sources like weather and event calendars to model and predict passenger flow.
A particularly pertinent piece of information is the capacity after alighting, which is the result of OpenCapacity’s predictive modelling.
Gerrit Boehm, PhD
Gerrit holds a PhD in Persuasive Technologies focusing on novel, innovative products and services to enhance Public Transportation. He has 13 years of experience in human-computer interaction, design engineering and emerging technologies. His core interests lie in IoT, Big Data & Smart Public Transport to deliver Intelligent Mobility.
Peter is a technical lead with over 20+ years experience in implementing solutions in health, infrastructure and finance. Over the last 6 years, he worked in lead roles for several tech startups. Peter’s background is in Business Intelligence and Spatial Analysis and has been driven by presenting big complex datasets as meaningful information. He holds an MSc in Computing and an MBA in Innovation Management.
Eugenio Piasini, PhD
ML & AI Expert
Eugenio holds a MS in Theoretical Physics from the University of Pavia(Italy) and PhD in Neuroscience from University College London (UK). Recently, he has been a Visiting Research Fellow at Harvard Medical School, and he is currently a Postdoctoral Researcher at the Italian Institute of Technology. He is interested in information processing in complex systems, and particularly in biological and artificial neural networks. His expertise covers machine learning and statistical modelling methods.