Formed in 2012, we are a British technology company established to develop insights and predictive analytics derived from mobile network data (MND) in compliance with data privacy laws.
We enhance anonymised raw mobile network data to enable organisations to identify trends with the flow of people across a variety of different transportation modes.
This provides our customers with valuable insights – including origin-destination, dwell time and journey paths on foot, in a vehicle or by train – to help them make informed decisions about future planning and development. We have helped to shape over 100 projects in the UK and internationally by creating customised data sets based on anonymised mobile network data (MND) and machine learning.
OUR PEOPLE MOVEMENT PORTAL
People movement analytics for everyone
Our new People Movement Portal is an evolutionary shift forward. Insights based on Mobile Network Data (MND) can now be delivered quicker and at a lower cost, without sacrificing the high-quality standard for which Citi Logik is known.
But you don’t have to take our word for it, see for yourself by exploring a range of sample data across our pre-built templates. Self-service analytics has arrived!
Big Data analytics enabling smarter decisions in the rail industry
railanalytics is a suite of services that tailor Citi Logik’s expertise with mobile network data and IoT data to the specific needs of train operators and rail passengers.
- RailMonitor: RailMonitor provides real-time and historic train occupancy data that can forecast train occupancy before a train arrives at a station. It acts as an operational decision support tool for TOCs and allows passengers to make informed journey choices.
- StationWatch: StationWatch provides passenger flow information for railway stations. Available in both real-time and as historic datasets, it enables station managers to improve operations.
- StationAnalytics: StationAnalytics shows the catchments for railway stations and provides information on the first-mile/last mile of rail journeys.
- DelayAnalytics: DelayAnalytics enables operators to assess the impacts of train delays and understand how passengers respond to them.
Mobile network data for Transport
Citi Logik have developed custom datasets using MND for over 100 transport and urban planning projects in the UK and abroad.
With a team of experts in population movement, transport modelling and big data, we offer a flexible, transparent approach to enable clients to exploit the huge potential of mobile network data.
Our transportdata capability provides insight on the following:
- Where do people travel from and to? Our journey generator determines where trips start and end. Rail trips can be split into ‘station to station’ and ‘first mile/last mile’ legs.
- By what mode do people travel? Our algorithms detect the mode of each trip – rail, slow mode, HGV or ‘other road-based’ mode. We also identify how many people are stationary.
- Why are people travelling? Our pattern recognition infers the purposes of each trip.
- What route are they taking? We snap the trajectories of each trip to the corresponding road or rail route. We are currently developing a ‘snap to flight’ offering for the aviation sector.
Data is vital for city and transport planners
The role of mobile network data in understanding travel patterns and road use
City and transport planners, operators and policymakers need to understand the interplay of road infrastructure, travel patterns, travel times and congestion. This is critical to plan work patterns, public transport operations and urban regeneration against a backdrop of rising populations and urbanisation – two trends exerting increasing pressure on cities’ infrastructure.
Advanced demand estimation models incorporating big data sources including mobile network data can provide these insights, helping guide decision-makers on investments in road infrastructure construction, maintenance and transport operations.
More reading: “The future for Mobile Network Data in transport“.
Mobile network data is cheaper and provides more information
The rise of mobile network data
The use of anonymised mobile network data (MND) to understand mobility patterns has become increasingly popular in recent years. Traditional survey methods are expensive, potentially disruptive, prone to human error and provide only a limited snapshot in time.
MND is considerably more cost effective and can provide information on population and vehicle flows both historically or in real-time. MND has a valuable role as an integral data source providing insights to better inform decision making in the development of transport planning models.
FOR MOBILE NETWORK OPERATORS
Monetise your data
An opportunity for Mobile Network Operators
Now mobile network operators can plug these powerful analytics capabilities into their data and offer them as a service to customers.
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