Author
Listed:
- Villacis Ninasunta, Alexis Javier
- Pinargote Basurto, Mariana
Abstract
The automotive industry has seen the need to improve the comfort of the user by integrating intelligent voice-controlled systems. This aims to prevent potential distractions while driving and enhance the user experience on their journeys. Nowadays, voice assistants that interact with specific vehicle information are exclusive to high-end models or specific brands. However, there are other voice assistant alternatives available on the market such as the Echo Auto, which is designed for use in vehicles allowing access to the functionalities of the Alexa voice assistant. Conversely, its functions are limited to access to entertainment and information applications. Considering this context, this work presents the development of a system that allows extracting information from sensors of the Toyota Hilux CS 2020 vehicle, such as the status of the fuel system, ignition timing, coolant temperature and the air-fuel ratio. It also includes control of the activation of the door locks of a Mazda CX-3 vehicle. To do this, an MCP2515 CAN bus controller has been used to extract or write information from the bus and an Arduino Nano microcontroller to process it and send it to the cloud using a WIFI module. The Blynk IoT platform is responsible for receiving this data or sending it to the microcontroller and presenting it in an interface so that the user can monitor it. Through an Alexa skill programmed in Voiceflow, it is possible to access this data or modify it using voice commands given by the user. The main limitations encountered stem from the characteristics of the CAN bus in the vehicle, as not all the modules for function control are always connected to the main bus, for this reason it was necessary to use different vehicles.
Suggested Citation
Villacis Ninasunta, Alexis Javier & Pinargote Basurto, Mariana, 2025.
"Computer-to-vehicle linking system, Alexa auto,"
SAP Transport, Mobility & Society, South American Publishing.
Handle:
RePEc:cwf:tmsart:tms2025202
DOI: 10.56294/tms2025202
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