Cipher: Monitoring the Tube

01 September 2019
Image of trains from a height.
Processing, storing, analysing, and visualising large volumes of data for signalling systems As the amount of raw data generated by sensors and monitors across the London Underground network grows, the difficulty in manipulating, analysing, and gaining insights from the data increases measurably. Cipher transforms monitoring data into intuitive diagnostic information, making it easy for customers to extract meaningful insights to support their asset management decisions.

Key Features

Cipher provides tools for interrogating both vehicle and vehicle detection information. It handles a terabyte of data every month, automatically parsing, pre-processing, and storing the low-level train data in the cloud.

The embedded analytics module allows users to submit their own custom queries to Cipher’s underlying data set, using distributed processing to provide rapid results. Cipher’s versatile and straightforward interface allows for both a high resolution interrogation of specific datasets, and a broad overview of trends across the network. We are currently trialling an implementation of Cipher on the Jubilee line.


Cipher enables engineers to leverage substantial quantities of data efficiently, providing a clear and timely understanding of the state of the network and fleet. It helps to identify where and when issues occur, as well as the preliminary patterns and indicators of emerging problems.

Cipher eliminates the need for manual data processing and handling by using an entirely automated pipeline. By combining distributed processing technology with data pre-processing, Cipher provides useful analytical insights from datasets that are too large for traditional exploratory techniques. In short, Cipher reveals the insights hidden within big datasets to the advantage of infrastructure asset managers.