Project Profile: Farley Staines
Name: Farley Staines
Course: BSc (Hons) Computing (Data and Information Systems)
Project title: A comparative analysis of driving performance and styles across simulators and real-world scenarios
Brief overview: The project focused on creating a telemetry program that can display and overlap data from both the car simulator and real-life cars.
| Key term: Telemetry is the automated, remote collection and wireless transmission of data from sensors to a central system for monitoring, analysis, and optimization. It is widely used across aerospace, IT, healthcare, and manufacturing to track metrics like temperature, speed, or system performance, enabling real-time decision-making. [r: ibm.com] |
The project was written in Python and contains multiple user interfaces for different functionality. It supports both real-world and simulator data sources from Motec and ViGrade formats. It imports this data as a CSV and converts it into an SQLite database.
| Key term: Motec (MoTeC) and VI-grade (ViGrade) represent two different, often complementary, sides of automotive simulation and data analysis, specializing in data logging and virtual testing. * MoTeC is a world leader in motorsport data acquisition (loggers, ECUs, dash displays). Their data format is designed to record vehicle performance data in real-time. MoTeC creates proprietary “log files” (usually with .ld or .ldx extensions) generated by their i2 (Interpreted) Data Analysis software. * VI-grade is a leading company specializing in driving simulators and virtual testing solutions for the transportation industry. VI-grade provides software for offline simulation (predicting performance) and real-time simulators (driver-in-the-loop). Their formats are designed for high-performance vehicle modelling (handling, ride, NVH), enabling engineers to simulate cars and race tracks before building a physical prototype. |
The project’s program features include displaying data on various types of graphs (click below to enlarge), identifying and visualising specific laps from the data, being able to group similar data together and plotting them onto the same graph, and supporting multiple databases being loaded at the same time.
Project Conclusion: Based on the feedback received, the strengths include effectively managing multiple sources of data, custom grouping capabilities, improved workflow, all packaged in a single file.
After graduation: After graduation I aim to move into a motorsports career as a Data Engineer.
| Key term: A ‘Data Engineer’ builds and maintains a data infrastructure including the pipelines, databases, and processing computer systems, that converts raw data into actionable information. A Data Engineer ensures the data is accessible, clean, and secure, utilizing tools such as SQL, Python, and cloud platforms (AWS, Azure) to aid decision-making. |
A top tip/advice for students: Manage your work by doing little bits at a time and not leaving it right to the end.
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