Northern Rail

Knowledge Base App for Northern Rail

Northern Rail is the primary train operator in the north of England. It plays a vital role locally by connecting tens of thousands of people to work, leisure, education and more every day and operates more stations than any other train operating company in the United Kingdom. We worked with Northern Rail to provide them a knowledge base app that would revolutionise their operation notices process.

 

The problem

Northern Rail approached us requiring an app that would revolutionise their process of operation notices. Their previous operations notices system was based on vast amounts of PDF and paper documents that they received from Network Rail. At this point in time, Northern Rail didn’t have an app or an electronic system that could process and translate their operation notices documents into a convenient app form. It was our job to devise a system that would translate the information contained in their current PDF and paper systems into a mobile app which would allow Northern Rail staff quick and easy access to the right documents. 



Analysis

As Northern Rail didn’t have an app based system at this point, we needed to devise a way in which all of their PDF and paper documents could be successfully converted into HTML format. The difficulty of this was ensuring that the HTML versions of documents maintained accuracy to the various facets of the PDF documents, including images and diagrams such as route maps and tables. With this we needed to find a way that the constitutional elements of the texts and images in the PDF documents could be translated into HTML without breaking them or incorrectly changing the size of the files (as many commercial conversion tools are prone to do) as there was a restriction on bandwidth limit. Fine tuning the HTML files for optimal performance was one of the technical challenges.   We had previous experience in creating knowledge base apps for rail companies, for example, we created the Lorolpedia for London Overground, which is now Arriva Rail’s Arrivu, so we knew we could adjust our existing framework to cater for Northern Rail’s own specification requirements.

Solution

We used our custom content management system (CMS) Cadenza to build the overall framework of the app. While Cadenza was primarily built for custom websites we were able to build a feed in the CMS which integrates content from the Northern Rail server into the knowledge base app as required. In addition to this feed function, we also build an audit element so that the feed records who has requested certain information and what has been sent so that any further requests do not include any repeated information. To convert the PDFs into HTML, we examined various conversion routines and identified one that met the technical requirements. This conversion system now allows for a simple conversion process whereby users can simply drag and drop a PDF file into a folder which is then automatically converted and stored in the system. In addition to these two functions we also created a backend which users can create articles in a way that is similar to creating a web page in a CMS. This means that staff can create their own notices and publish them through the app. Users can also submit feedback through a form in the backend, allowing for messages to be sent between staff. Finally, given the size of Northern Rail’s network, we implemented a system that recognises which depot the user is based at and the app then connects to the particular server. As each depot receive their own individual operating notices the app determines which depot the user is at and interacts with Northern Rail’s database to identify the serial number from the mobile being used and supply the user with the specific operations notice for their depot.

Result

The Northern Rail knowledge base app took 3 months to create and implement. It is currently being used by drivers and conductors across Northern Rail’s fifteen different routes and has received excellent feedback.


Back to Category

Date

22 March 2017

Categories

data base