Northumbrian Water came to us with the aim of improving their prediction capabilities for forecasting potential pipe burst points. The original process involved engineers surveying large areas which was often very time-consuming, and in some cases inefficient. Their previous tool to find leaks in pipes could have left customers with a longer wait for water. The main aim in this project was to best-equip engineers by providing them with an ‘Optimised DMA pack’, containing the right information at the right time. Emphasis was put on creating a quick and easy automation process which collated live, up-to-date data on hydrant and valve locations, along with previous pipe burst points.
Our end goal was to create a user friendly Shiny app to map the information we had for each DMA, an assigned area. Shiny is an open source R package that provides a framework for building web applications. We created a clear user interface for parameter entry, allowing an engineer to visualise the features mentioned above, within a selected DMA. Shape files containing geolocation data wereused to map the outline of pipes (along with locations of valves and hydrants) onto a map of the UK. We acquired user studies and used agile methodology throughout the app development stage, to ensure we were meeting the engineers’ needs.The database automatically updates every morning to ensure LT’s have access to the most up-to-date data.
The end product of this project was a Shiny dashboard used to visualise DMA data, region by region. The current app is being used to enhance the ‘DMA pack’ accessible to LT’s going to survey a particular DMA. In addition to the mapping tool, we have processed information in regards to bursts, valve locations and soil types into interactive tabular data previews. We also assisted Northumbrian Water in deploying the application onto their internal server, to provide them with an easy to manage platform for maintaining and running the application. Northumbrian Water are using the app on a daily basis, which further emphasises the purpose of the automated database update feature.
Jumping Rivers created a data pipeline and visualisation dashboard for public and policy maker consumption. The aim was to increase transparency and encourage positive change to the workplace environment. The application allows exploration of key performance indicators stratified by a host of protected characteristics.
The client came to Jumping Rivers having already written the code for their problem in VBA. They were trying to evaluate four measurements for agreements with their clients. However, VBA is limited in speed. Jumping Rivers were required to build a bespoke R package to replace and quicken the code.
At the end of 2017, contacted Jumping Rivers. AGR TRACS International estimates the volumes of oil and gas in subsurface reservoirs. Their work involves combining a set of inputs for each reservoir layer (such as area, thickness, and up to five other inputs) – and then multiplying these inputs together.
Over the last two years, we have been working with a cutting edge electronics company to build advanced algorithms using R and Python. Since they are at the research & design stage of the development process, their data structure is unique and challenging.
After winning a Water Hub Hackathon, Jumping Rivers were contracted to create a platform for the client using R Shiny, published on RStudio Connect. The platform aggregates raw data from many third party sources both internal and external to the EA, through bespoke APIs, commercial databases, and asset management systems.
The client wanted to assess the viability of R and R Markdown as a reporting tool for creating complex, bespoke documents. We recreated sample reports for them in R Markdown, showcasing that all of their specifications could be met, and provided them with example code and training.
Jumping Rivers built a tool for creation of experimental risk assessments via a centralised web application. The dashboard allows for collaborative working during the data entry and assessment formulation, report generation and tracks versions along iteration of the process.
The IFoA required a bespoke R and RStudio platform to run their new R-based Actuarial CS1 and CS2 exams. We developed a system that delivered the exam and provided a convenient submission portal. Examiners could monitor results and feedback via a Shiny dashboard.
The client had developed an advanced, in-house Shiny application. We transformed the application into a commerical project, that is now being used by their clients.
In the spring of 2018, NHS Scotland expressed a need to move from their existing software, SPSS and SAS, to using R. The difficulty they faced was that there are over two hundred data scientists in NHS Scotland, which made training everyone in the new software a logistical challenge.
In 2018, Northumbrian held their annual Innovation Hackathon. Our winning entry, allowed enginneers to reduce leakage throughout the North East.
In spring of 2020 Northumbrian water engaged with Jumping Rivers to build a modelling solution to better understand risks to the consumer within their network in order to provide a better service.
