Project Abstract

My research is motivated by the complexity of remote control and safety systems, as well as the rising demand for efficiency. With cloud computing’s high-performance computing resources, we can greatly improve automated vehicle systems even when they’re operating in real time. The aim is to make it easier for vehicles to do their jobs and keep people safe, both when they’re driving themselves or when they’re being controlled from afar. My work prioritises cloud computing and real-time vehicle simulation to improve the functionality of remote vehicle systems. The tool’s objective is to provide a dependable platform for data calculation and fast decision making.The methodology for this project consists of designing the system architecture on the AWS cloud platform, which will take use of the unique characteristics of AWS services. This includes leveraging Lambda for real-time data processing, S3 for data storage, and CloudWatch for data monitoring and visualisation. They are combined with the integration of the CARLA simulator, which provides a practice ground for real-world driving scenarios and serves as an evaluation system. To summarise, the key findings of the current study show that the proposed integrated system may significantly reduce latency in measurements, ensuring the accuracy of remote catching operations.

Keywords: Internet of Things (IoT), Cloud,

 Conference Details

Session: Presentation Stream 34 at Presentation Slot 3

Location: CoFo 002 at Wednesday 8th 13:30 – 17:00

Markers: Mark Jones, Galileo Sator (GTA)

Course: MSci Computer Science, Masters 4th Year

Future Plans: I’m looking for work