IMPLEMENTATION OF INFORMATION TECHNOLOGY FOR THE MODEL OF PREDICTION POTENTIAL CARS COLISION (Computer systems and information technologies, 2025)
This research focuses on developing an information technology solution capable of delivering real-time notifications about potential car accidents to Internet of Things (IoT) devices installed in vehicles. Since vehicles are mobile and frequently change location, there is a need to have stable and timely notifications. To address this, the proposed solution leverages cloud technologies, which offer scalability, low latency, and high availability for real-time data transmission.The main objective is to design and implement architecture that enables effective real-time messaging between cloud services and moving IoT devices. The system is tested across various simulated driving scenarios to evaluate its performance and reliability. A key aspect of the methodology involves measuring the time interval between when a message is sent and when it is received by the IoT device, followed by assessing whether the driver has adequate time to respond appropriately.The experimental setup is based on test cases created using Python, the BeamNG.tech simulation environment, and AWS IoT Core as the cloud service provider. The results demonstrate that the proposed technology can reliably handle real-time messaging in dynamic conditions. As a conclusion, the research confirms the potential of the developed solution for real-life applications in connected vehicle safety systems.
Keywords: Information technologies development; real-time messaging; cars accident prediction; IoT; computer vision; machine learning; artificial intelligence