Overview
It is commonly found on modern machine tools and as an automotive diagnostic bus.
Thanks to the CAN-BUS, makers are able to hack their cars!
It adopts MCP2515 CAN-BUS controller with SPI interface and MCP2551 CAN transceiver to give you Arduino CAN-BUS capability. Default pinout is OBD-II and CAN standard pinout can be selected by switching jumpers on DB9 interface.
Moreover, it has the TF card slot for data storage and the CS pin that can be set to D4 or D5.
The INT pin can also be set to D2 or D3 by switching jumpers on the back of the shield.
CAN-BUS Shield Works perfectly with Arduino UNO (ATmega328), Arduino Mega (ATmega1280/2560) as well as Arduino Leonardo (ATmega32U4).
Features:
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Implements CAN V2.0B at up to 1 Mb/s
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Industrial standard 9 pin sub-D connector
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OBD-II and CAN standard pinout selectable.
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Changeable chip select pin
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Changeable CS pin for TF card slot
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Changeable INT pin
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Screw terminal that easily to connect CAN_H and CAN_L
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Arduino Uno pin headers
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2 Grove connectors (I2C and UART
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SPI Interface up to 10 MHz
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Standard (11 bit) and extended (29 bit) data and remote frames
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Two receive buffers with prioritized message storage
Conformities
Get Inspired
This project shows how to create a security system using the camera of an Arduino Nicla Vision board. The system automatically triggers a camera snapshot when presence is detected. Presence is detected when the system detects a sound level that exceeds a configurable threshold. The whole system is controlled by an Arduino Cloud dashboard.
Shortly after attending a recent tinyML workshop in Sao Paolo, Brazil, Joao Vitor Freitas da Costa was looking for a way to incorporate some of the technologies and techniques he learned into a useful project. Given that he lives in an area which experiences elevated levels of pickpocketing and automotive theft, he turned his attention to a smart car security system. His solution to a potential break-in or theft of keys revolves around the incorporation of an Arduino Nicla Vision board running a facial recognition model that only allows the vehicle to start if the owner is sitting in the driver’s seat. The beginning of the image detection/processing loop involves grabbing the next image from the board’s camera and sending it to a classification model where it receives one of three labels: none, unknown, or Joao, the driver. Once the driver has been detected for 10 consecutive seconds, the Nicla Vision activates a relay in order to complete the car’s 12V battery circuit, at which point the vehicle can be started normally with the ignition. Through this project, da Costa was able to explore a practical application of vision models at-the-edge to make his friend’s car safer to use. To see how it works in more detail, you can check out the video below and delve into the tinyML workshop he attended here.