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Background. Advanced artificial intelligence and IoT gateways are working together in the automotive industry to predict potential vehicle problems by analysing sensor data and optimizing quality control processes. Manufacturers can detect anomalies, improve product reliability, and eliminate manufacturing defects or malfunctions in advance. Predictive analytics also lead to improved fuel efficiency, performance and overall vehicle reliability. Objective. The purpose of this work is to develop a model for remote diagnosis of vehicle faults using a Raspberry Pi model B microcomputer and a SIM7600G-H GSM module. Configure data modules, install the necessary software and configure it, demonstrate step-by-step actions, and perform diagnostics and testing of this module for data transmission. Methods. A prototype was created on the basis of Raspberry Pi 4. and provides monitoring of machine operation in remote mode using the SIM7600E-H LTE Cat-4 4G/3G module. The design has small dimensions, easy installation, requires only initial adjustment and has a wide range of improvements. Results. This prototype uses a diagnostic OBD-II car scanner ELM327 with Bluetooth connection support, a Raspberry PI 4 model B microcomputer with 8 GB of RAM, 4 USB connectors (2 ports type USB3 and 2 ports type USB2), a Gigabit Ethernet port, a USB-C power supply port, and two micro HDMI 4K display connectors. On top of the module there are 48 pins (contacts) with which you can connect modules of different types and directions. The SIM7600G-H communication module is connected to these pins. The last element of the prototype is the SIM card of one of the telephone service providers and the micro SD card, which will act as the main memory element on which the operating system will be written and data will be stored. Conclusions. The article proposes the development of a device model using Internet of Things technologies, which is capable of providing remote diagnosis of car malfunctions. This model is based on the use of the SIM7600G-H module, which provides data transmission through the mobile network. The developed model allows you to read data from various car sensors, as well as transfer this data to a remote device for further analysis. This makes it possible to quickly detect malfunctions and make timely decisions on their correction.
Moshynska et al. (Fri,) studied this question.