M5StickV

SKU:K027

Tutorial

Choose the development platform you want to use, view the corresponding tutorial&quick-Start.

V-Function V-Training Maixpy

Description

M5Stack recently launched the new AIoT(AI+IoT) Camera powered by Kendryte K210 -an edge computing system-on-chip(SoC) with dual-core 64bit RISC-V CPU and advanced neural network processor..

M5StickV AI Camera possesses machine vision capabilities, equips OmniVision OV7740 image sensor, adopts OmniPixel®3-HS technology, provides optimum low light sensitivity, supports various vision identification capabilities. (e.g. Real-time acquisition of the size, type and coordinates of the detected target ) In addition to an OV7740 sensor, M5StickV features more hardware resources such as a speaker with built-in I2S Class-D DAC, IPS screen, 6-axis IMU, 200mAh Li-po battery, and more.

It is able to perform convolutional neural network calculations at low power consumption, so M5StickV will be a good zero-threshold machine vision embedded solution. It is in support with MicroPython, which makes your code to be more concise when you use M5stick-V for programming.

Switching operations:
Power on:Long press power button for 2 seconds
Power off: Short press power button for 6 seconds

Product Features

  • Dual-Core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal)
  • Dual Independent Double Precision FPU
  • Neural Network Processor(KPU) / 0.8Tops
  • Field-Programmable IO Array (FPIOA)
  • Dual hardware 512-point 16bit Complex FFT
  • SPI, I2C, UART, I2S, RTC, PWM, Timer Support
  • AES, SHA256 Accelerator
  • Direct Memory Access Controller (DMAC)
  • Micropython Support
  • Firmware encryption support
  • Case Material: PC + ABS

Include

  • 1x M5StickV
  • 1x USB Type-C(100cm)
  • 1x Bracket
  • 1x HEX KEY

Applications

  • Face recognition/detection
  • Object detection/classification
  • Obtaining size and coordinates of the target in real-time
  • Obtaining the type of detected target in real-time
  • Shape recognition
  • Video/Display
  • Game simulator

Specification

Resources Parameter
Kendryte K210 Dual core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal)
SRAM 8MiB
Flash 16M
Power input 5V @ 500mA
KPU Parameter size of neural network 5.5MiB - 5.9MiB
Port TypeC x 1, GROVE(I2C+I/0+UART) x 1
RGB LED RGBW x 1
Button Custom button x 2
IPS screen 1.14 TFT, 135*240, ST7789
Camera OV7740(30W pixels)
FOV 55deg
PMU AXP192
Battery 200mAh
External storage TF-card(microSD)
MEMS MPU6886
Net weight 23g
Gross weight 82g
Product Size 48*24*22mm
Package Size 144*44*43mm
Case Material Plastic ( PC )

Driver Installation

Connect the device to the PC, open the device manager to install FTDI driver for the device. Take the win10 environment as an example, download the driver file that matches the operating system, unzip it, and install it through the device manager. (Note: In some system environments, the driver needs to be installed twice for the driver to take effect. The unrecognized device name is usually M5Stack or USB Serial. Windows recommends using the driver file to install directly in the device manager (custom Update), the executable file installation method may not work properly). Click here to download FTDI driver

TF-card(microSD) test

M5StickV does not currently recognize all types of TF-card(microSD). We have tested some common TF-card(microSD). The test results are as follows.

Brand Storage Type Class Format Test Results
Kingston 8G HC Class4 FAT32 OK
Kingston 16G HC Class10 FAT32 OK
Kingston 32G HC Class10 FAT32 NO
Kingston 64G XC Class10 exFAT OK
SanDisk 16G HC Class10 FAT32 OK
SanDisk 32G HC Class10 FAT32 OK
SanDisk 64G XC Class10 / NO
SanDisk 128G XC Class10 / NO
XIAKE 16G HC Class10 FAT32 OK(purple)
XIAKE 32G HC Class10 FAT32 OK
XIAKE 64G XC Class10 / NO
TURYE 32G HC Class10 / NO

EasyLoader

EasyLoader is a concise and fast program writer, which has a built-in case program related to the product. It can be burned to the main control by simple steps to perform a series of function verification.

Download Windows Version Easyloader

Description:
Equipped with Maixpy firmware, test camera, screen graphics display function, and then press the HOME button to turn on the rear fill light.

Charging current measured value

charging current Fully charged current(Power OFF) Fully charged current(Power ON)
0.376A 0.078A 0.255A

FUNCTIONAL DESCRIPTION

KENDRYTE K210

The Kendryte K210 is a system-on-chip (SoC) that integrates machine vision. Using TSMC’s ultra-low-power 28-nm advanced process with dual core 64-bit processors for better power efficiency, stability and reliability. The SoC strives for ”zero threshold” development and to be deployable in the user’s products in the shortest possible time, giving the product artificial intelligence

  • Machine Vision
  • Better low power vision processing speed and accuracy
  • KPU high performance Convolutional Neural Network (CNN) hardware accelerator
  • Advanced TSMC 28nm process, temperature range -40°C to 125°C
  • Firmware encryption support
  • Unique programmable IO array maximizes design flexibility
  • Low voltage, reduced power consumption compared to other systems with the same processing power
  • 3.3V/1.8V dual voltage IO support eliminates need for level shifters

CPU

The chip contains a high-performance, low power RISC-V ISA-based dual core 64-bit CPU with the following features:

  • Core Count: Dual-core processor
  • Bit Width: 64-bit CPU 400MHz
  • Frequency: 400MHz
  • ISA extensions: IMAFDC
  • FPU: Double Precision
  • Platform Interrupts: PLIC
  • Local Interrupts: CLINT
  • I-Cache: 32KiB x 2
  • D-Cache: 32KiB x 2
  • On-Chip SRAM: 8MiB

OV7740

  • support for output formats: RAW RGB and YUV
  • support for image sizes: VGA, QVGA, CIF and any size smaller
  • support for black sun cancellation
  • support for internal and external frame synchronization
  • standard SCCB serial interface
  • digital video port (DVP) parallel output interface
  • embedded one-time programmable (OTP) memory
  • on-chip phase lock loop (PLL)
  • embedded 1.5 V regulator for core
  • Sophisticated Edge Rate Control Enables Filter less Class D Outputs
  • 77dB PSRR at 1kHz
  • Low RF Susceptibility Rejects TDMA Noise from GSM Radios
  • Extensive Click-and-Pop Reduction Circuitry
  • array size: 656 x 488
  • power supply: – core: 1.5VDC ± 5% – analog: 3.3V ± 5% – I/O: 1.7 ~ 3.47V
  • temperature range: – operating: -30° C to 70°C – stable image: 0° C to 50° C
  • output format: – 8-/10-bit raw RGB data – 8-bit YUV
  • lens size: 1/5"
  • input clock frequency: 6 ~ 27 MHz
  • max image transfer rate: VGA (640x480): 60 fps – QVGA (320 x 240): 120 fp
  • sensitivity: 6800 mV/(Lux-sec)
  • maximum exposure interval: 502 x tROW
  • pixel size: 4.2 μm x 4.2 μm
  • image area: 2755.2 μm x 2049.6 μm
  • package/die dimensions: – CSP3: 4185 μm x 4345 μm – COB: 4200 μm x 4360 μm

MAX98357

  • Single-Supply Operation (2.5V to 5.5V).
  • 3.2W Output Power into 4Ω at 5V
  • 2.4mA Quiescent Current
  • 92% Efficiency (RL = 8Ω, POUT = 1W)
  • 22.8µVRMS Output Noise (AV = 15dB)
  • Low 0.013% THD+N at 1kHz
  • No MCLK Required
  • Sample Rates of 8kHz to 96kHz
  • Supports Left, Right, or (Left/2 + Right/2) Output
  • Sophisticated Edge Rate Control Enables Filter less Class D Outputs
  • 77dB PSRR at 1kHz
  • Low RF Susceptibility Rejects TDMA Noise from GSM Radios
  • Extensive Click-and-Pop Reduction Circuitry

AXP192

  • Operation Voltage: 2.9V - 6.3V(AMR:-0.3V~15V)
  • Configurable Intelligent Power Select system
  • Current and voltage limit of adaptive USB or AC adapter input
  • The resistance of internal ideal diode lower than 100mΩ

MPU6886

GYROSCOPE FEATURES

  • Digital-output X-, Y-, and Z-axis angular rate sensors (gyroscopes) with a user-programmable full-scale range of ±250 dps, ±500 dps, ±1000 dps, and ±2000 dps and integrated 16-bit ADCs
  • Digitally-programmable low-pass filter
  • Low-power gyroscope operation
  • Factory calibrated sensitivity scale factor
  • lens size: 1/5"
  • Self-test

ACCELEROMETER FEATURES

  • Digital-output X-, Y-, and Z-axis accelerometer with a programmable full scale range of ±2g, ±4g, ±8g and ±16g and integrated 16-bit ADCs
  • User-programmable interrupts
  • Wake-on-motion interrupt for low power operation of applications processor
  • Self-test

SPI/I2C dual communication mode

<mark?>Note: There are two versions of M5StickV currently released by M5Stack. When programming, users need to configure differently according to their corresponding pin mapping. The specific differences are as follows.

  • In the M2StickV circuit design of the I2C single-mode (blue PCB) version, MPU6886 only supports the user to configure its communication mode to I2C, and its pin mapping is SCL-28, SDA-29.

  • In the SPI/I2C dual mode (black PCB) version of the M5StickV circuit design, MPU6886 supports the user to configure its communication mode to SPI or I2C, and its pin mapping is SCL-26, SDA-27., when using, you can switch CS Pin level to switch modes (high level 1 is I2C mode, low level 0 is SPI mode)

  • The specific pin mapping is shown below:

Schematic

K210_CAM

Learn

Detect cars and people which is blinding by drivers. You need only putting M5Stack and you aren't doing dedicated construction.
The M5Stick-V is an AIOT (AI + IOT) camera with machine vision capabilities.
"MiMaMori Alert" is automatic security camera for your home. Automatic learning without teacher images, and notify if something is visitor.
Mountable device for your Personal AI Social Distancing Alarm by detecting how far the person's face from you..... (M5StickV)
M5StickV and M5StickC with HID BT Wireless or Atomic QR-Code reader
This is a Cheering Watch using M5StickC and M5StickV. Estimate what action you are taking from this device acceleration and cheer up!!
Brownie is an AI camera app that allows you to automate your daily life with simple operation.
This project is based on the use of the development system M5StickV, for the classification of emotions.
The idea is simple, I would like to create Home Automation unit with something intelligent. So I combine M5StickV and M5StickC.
AI camera that automatically sorting out the garbage.
My posture gradually gets worse when I work on a PC. I developed ”Bad Pose Detector" using by M5StickV, it notices sound and LED.
My family has eaten the pudding I have saved! Do you have such experience? I want to keep the peace of my home. I made pudding alert-V.
Using M5stickV (UnitV)and its standard Face Detection Model.....Upgrade to enable for Web Stream using M5stickC(ESP32)
M5Stick V + Adafruit Thermal Printer + M5Stack Gray = Instant Camera Printer
This application will focus on simulating the addition and payment of goods in unmanned supermarkets.
Stickv is used to realize the AI identification of traffic signs, and stickc is used as the executive component. Thanks @CangHai
Realize the "offline cloud platform" interaction function of operation information based on mqtt information transmission technology
Converting the camera sensor feed to 0 and 1 ASCII art.
@HomeMadeGarbage The goldfish tank monitoring system has become a form, and it is an application of the edge AI of this subject.
The model will help learn / associate the items/phrases commonly used by a user (autistic/semi-verbal); so that they can communicate.
Thank @沧海 for his contribution We choose wechat jump, a classic little game, as a carrier of target detection test.

V-Training

Version Change

Release Date Product Change Note:
2019.7 Initial public release /
2020.3 The circuit supports configuring MPU6886 to use SPI or I2C protocol for communication.I2C pin change SCL (28=>26), SDA (29=>27) Program to drive the chip select pin CS for modification, high level 1 is I2C mode, low level 0 is SPI mode.
2020.3 Add with Microphone /
2020.4 Standard package add with bracket /