Best poster competition winners announced

Timemap Poster

Congratulations to Isaac Williamson, Callum Mardle and Charlie Cook from the TimeMap project team at Canterbury and Ashley White, Daniela Miteva, Fardusa Jibril, Modestas Garkevicius and Simran Mattu from the Scientific Research Project team at Medway, whose final year project posters were voted the best in an online vote by students and staff.

Following the cancellation of the computing showcase poster fair in March due to Covid-19, the School of Computing moved the poster fair online to celebrate the hard work put in by the final year students and supervisors. The students and staff in the School also had the opportunity to vote for the best poster as they would normally do with an on-campus event.

Orla Garratt, Marketing and Communications Manager for the School said, ‘We know how much work goes into the final year projects and it was such a shame that our students missed out on the chance to display their work and talk about their projects in person. The virtual fair was a way of displaying the high standard of work that we have come to expect from our students and we had a great response in the number of votes the posters received. A huge thanks goes to the team who helped get the posters, descriptions and voting online.’

TimeMap Project description

TimeMap ‘The best app for searching accommodation. Built by students, for students’.Current property search tools only allow users to search for properties based on the distance from a single geographical area, in our own experience we have found this to be extremely limiting when searching for university accommodation. A much greater concern for students is the length of time it will take to get from their accommodation to their university campus.

Our project offers a more efficient property search tool for students, allowing them to search by specifying the duration of time they wish to be from their university by either walking, cycling or driving. Additionally, there are often secondary points of interest (shops, gyms, nightlife etc.) that students wish to be near to, therefore our project provides custom markers for users to place on the map, alongside a duration for each. This further refines their search results and supports them in finding their ideal accommodation.


Our solution provides a responsive web application built with JavaScript library React. Users search for properties by selecting the time they wish to be from their selected university (128 UK universities supported), number of bedrooms and price. Our solution uses housing API Nestoria to return properties in the area that match the given parameters and results are passed to navigation API Mapbox. Calls are made to Mapbox, returning the duration from the university to each property and those that are within the given time requirements are presented on an interactive map. Users can add additional locations they wish to be near, which are appended to the matrix calls and only properties that match all requirements are displayed. Users can create a profile which allows them to save and load searches – both the user profiles and saved searches are facilitated using authentication and real-time databases on Google’s Firebase platform.

Scientific Research Calculator Project description

Our project was inspired by an existing web application, “The Single Case: TAU-U Calculator”. The calculator is designed to aid researchers to record and manipulate from large data sets, this application had numerus downfalls which made its use impractical. The main issue we found was that the user was unable to save their inputs and findings, as well as uploading and downloading of files. The biggest concern was the lack of error handling features.

We chose to implement this project as we felt that the project was able tie in all our previous knowledge as well as challenge our skills. We found the concept of the TAU-U likable and a great baseline for the project.

Our design is an enhanced and more complex version inspired by the TAU-U calculator, we were able to implement the features that were missing from the existing application, the biggest challenges we faced were learning about local storage in html 5 and applying it as well as manipulating JavaScript for the upload/download button.


Upon reflection of the project, our new and improved version of this web application brings many new features which have been requested by current users. The new features consist of allowing the user to locally save data, therefore, when the user reopens the application, the data is stored until its manually cleared, making it simple and convenient.

Furthermore, we have added features to allow the user to upload data in a CSV file format or manually entering data. In addition, data can be specifically selected to compare and produce visual results in the form of a graph. The application incorporates branches of JavaScript in HTML 5 (jQuery and JSON) to obtain a unique site which allows the user to have a trouble-free experience whilst using the multi-functional SCR tool.

Features such as downloading of raw and processed simplifies the process making it a user-friendly experience. Lastly, we have added additional features such as calculating of averages such as mean, median, mode, range and standard deviation to bring users much needed flexibility.