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mmWave Vehicle Occupancy Detection EVM Kit (BM201-VOD) (Worldwide Shipping)

$ 184.27

Availability: 100 in stock
  • Item must be returned within: 30 Days
  • Refund will be given as: Money Back
  • MPN: BM201-VOD
  • Condition: New
  • Restocking Fee: No
  • All returns accepted: Returns Accepted
  • Return shipping will be paid by: Buyer
  • Motherboard Brand: Batman

    Description

    Immediately Ship -Worldwide Shipping Available
    mmWave Sensor Evaluation Solution
    Batman BM201-VOD mmWave EVM Kit
    mmWave Vehicle Occupancy Detection (VOD)

    Vehicle Occupancy Detection (VOD)
    For plotting a Range-Azimuth-Heatmap with a 64 x 48 Grid Matrix covering: Range of 3 meter / 64 row (approx. 0.047 meter per row) x Azimuth of 108 degree / 48 column (approx. 2.3 degree /column). Subsequently a programmer may write code to group the Grid(s) into Zone(s) for detecting whether the particular Zone(s) is occupied by Target(s); suitable for vehicle occupancy detection or for occupancy detection for an area of around 3 meter x 3 meter.
    Attention:
    ● Batman BM201 mmWave EVM Kit supports Raspberry Pi4 (not for versions below) and NVIDIA Jetson Nano
    ● Raspberry Pi4 and / or NVIDIA Jetson Nano not included within this EVM Kit (must be purchased separately).
    Please check their respective websites for purchasing info
    ● Make sure you are using the correct power supply of 5 V, >2.0 A with a Micro USB connection
    Python SDK
    Available on GitHub
    /bigheadG/mmWave
    (Note: Please refer to README.md file first for proper configuration)
    mmWave Solution bridges Hardware & Software World together with Simplicity
    Joybien Batman BM201 mmWave EVM Kit is a Texas Instruments (TI) IWR6843 ASIC based millimeter-wave (mmWave) Kit with Frequency-Modulated Continuous Wave (FMCW) radar technology capable of operation in the 60GHz to 64GHz band with up to 4 GHz continuous chirp, using 3 Transmission Antennas and 4 Receiving Antennas, for sensing target object’s range, velocity, and angle parameters.
    Batman BM201 mmWave EVM Kit is with a small and compact mmWave Module (with low-power, self-monitored, ultra-accurate, and lighting condition independent versatilities), along with a Pi-Hat Board for simple and direct connectivity to a Raspberry Pi or NVIDIA Jetson Nano computer, suitable for various applications including: Education, Engineering, Science, Industrial, Medical, and Business & Consumer.
    Applications
    ● Education’s Practical Radar Introduction
    ● Engineering & Science’s Motion Detection, Displacement, etc.
    ● Industrial sensor for Displacement & Safe Guard, Factory Automation, Robotics, etc.
    ● Building Automation sensor for Occupancy Detection, Proximity & Position sensing, People Counting, Security and Surveillance
    ● Business’ Traffic Monitoring, and Proximity Advertisement
    *** Specifications subject to change without notice
    Features
    Operating Frequency
    60GHz ~ 64GHz coverage
    with 4GHz continuous bandwidth
    Antenna
    3 Tx and 4 Rx Antennas on Module, with:
    TX Power: 10 dBm
    RX Noise Figure: 14 dB
    Processors
    ARM R4F based MCU and C674x DSP
    for advanced signal processing
    On-Chip Memory
    1.75MB
    •Internal Memories
    ECC
    •Input Power
    3.3Vdc, 2.1A
    Specifications mmWave Sensor Evaluation Module
    mmWave ASIC
    TI IWR6843 Single Chip mmWave Sensor
    FMCW Transceiver
    Integrated PLL, Transmitter, Receiver, Baseband, and A2D
    60GHz to 64GHz Coverage With 4GHz Continuous Bandwidth
    Four Receive Channels
    Three Transmit Channels
    Ultra-Accurate Chirp Engine Based on Fractional-N PLL
    TX Power: 10 dBm
    RX Noise Figure: 14 dB
    Phase Noise at 1 MHz: –92 dBc/Hz
    Antenna Type : ISK Antenna
    Built-in Calibration and Self-Test (Monitoring)
    ARM® Cortex® -R4F-Based Radio Control System
    Built-in Firmware (ROM)
    Self-calibrating System Across Frequency and Temperature
    DSP
    C674x DSP for Advanced Signal Processing
    On-Chip Memory
    1.75MB
    MCU
    ARM R4F Microcontroller for Object Detection, and Interface Control
    Joybien mmWave Protocol (Per configuration)
    I/O
    Up to 6 ADC Channels (low sample rate monitoring)
    Up to 2 SPI Ports
    Up to 2 UARTs
    I2C – GPIOs
    Power Management
    Built-in LDO Network for Enhanced PSRR
    I/Os Support Dual Voltage 3.3 V/1.8 V
    Clock Source
    40MHz
    Antenna Orientation
    4 receive(RX) 3 transmit (TX) antenna with 108° azimuth field of view (FoV) and 44° elevation FoV
    Input Power
    3.3VDC, 2.1A source
    Operating Temperature
    & Humidity
    0° to 40° degree Celsius
    10 ~ 85% Non-Condensing
    Dimensions & Weight
    67mm x 46mm x 2mm ; 15 grams net
    Raspberry Pi-Hat Board /Jetson Nano carrier board
    Connector
    Matching mmWave Module Female Connector
    Matching Raspberry Pi GPIO Female Connector
    Micro USB Power Connector
    Jumpers for Bluetooth Tx/Rx or Raspberry Pi Tx/Rx Selection
    Jumper for mmWave Raw Data or Key Data Selection
    Bluetooth (optional)
    Joybien JBT24M Bluetooth Low Energy Module
    Micro USB Input Power
    5VDC, 2Amp.
    (Note: Power Adapter and Micro USB Cable NOT included)
    Operating Temperature
    Operating Humidity
    0° to 40° degree Celsius
    10 ~ 85% Non-Condensing
    Dimensions & Weight
    65.3mm x 56.3mm
    30 grams with JBT24M Bluetooth
    Python SDK
    Python SDK
    Available on GitHub
    Note: Please refer to README.md file first for proper configuration
    /bigheadG/mmWave
    (BM201-VOD)
    Vehicle Occupancy Detection
    /bigheadG/mmWave/tree/master/VOD
    (BM201-LPD)
    Long-Range People Detection
    /bigheadG/mmWave/tree/master/LPD
    (BM201-PC3)
    People Counting & Detection
    /bigheadG/mmWave/tree/master/PC3
    (BM201-TMD)
    Traffic Monitoring Detection
    /bigheadG/mmWave/tree/master/TMD
    (BM201-VSD)
    Vital Signs Detection
    /bigheadG/mmWave/tree/master/VSD
    (BM201-HAM)
    High Accuracy Measurement
    /bigheadG/mmWave/tree/master/HAM
    (BM201-DRN)
    Drone Radar Navigation
    /bigheadG/mmWave/tree/master/DRN
    (BM201-FDS)
    Fall Detection Sensing
    Python SDK upon purchasing BM201-FDS EVM Kit via email
    .
    Appendix: Joybien mmWave EVM Kit Application Solution Selection
    (BM201-VOD)
    Zone Occupancy Detection
    For plotting a Range-Azimuth-Heatmap with a 64 x 48 Grid Matrix covering: Range of 3 meter / 64 row (approx. 0.047 meter per row) x Azimuth of 108 degree / 48 column (approx. 2.3 degree /column). Subsequently a programmer may write code to group the Grid(s) into Zone(s) for detecting whether the particular Zone(s) is occupied by Target(s); suitable for vehicle occupancy detection or for occupancy detection for an area of around 3 meter x 3 meter.
    (BM201-LPD)
    Long-Range People Detection
    For a contactless and wearableless Long-Range People Detection (LPD) of 1 meter ~ 50 meters (about 3 ~ 164 feet), for various applications that require people sensing or counting without privacy invasion.
    (BM201-PC3)
    People Counting & Detection
    For a wireless People Counting & Detection in 6 x 6 meter or 36 square meter area (or about 387.5 square feet), for various applications that require people sensing, people counting, or people occupancy density estimation without privacy invasion.
    (BM201-TMD)
    Traffic Monitoring Detection
    For detecting moving objects (such as vehicles) in 5m ~ 50m with FOV of approx. +/- 54 degrees with Position X&Y, Velocity X&Y info. And based on the detected data, a programmer may write a program to define virtual Zones, for mapping objects (vehicles) moving in and out of certain Zones for traffic monitoring applications.
    (BM201-VSD)
    Vital Signs Detection
    For a contactless and wearableless human Vital Signs Detection (VSD) with real-time Heartbeat Rate & Respiration Rate data, for range of 30cm ~ 90cm (about 1~3 feet); along with Status Indicator for sensing the presence of a person, as well as the measurement stability, and whether the person is present but without Vital Signs.
    (BM201-HAM)
    High Accuracy Measurement
    For a wireless High Accuracy Measurement (HAM) of an object distance with range of 30cm ~ 3 meters (about 1~10 feet), having millimeter measurement resolution.
    (BM201-FDS)
    Fall Detection Sensing
    For wireless sensing of people-fall-detection along with people movement & tracking in 3-Dimensional region covering 6m x 6m area without privacy invasion. The sensed people behavior data are with Position X/Y/Z, Velocity X/Y/Z, and Acceleration X/Y/Z parameters suitable for people movement analysis such as standing, sitting, lying down or falling down positions.
    Note:
    NVIDIA logo, and Jetson Nano are trademarks and/or registered trademarks of NVIDIA Corporation.ducation’s Practical Radar Introduction
    Raspberry Pi logo and Raspberry Pi 4 are trademarks and/or registered trademarks of Raspberry Pi Foundation.
    "Python" is a registered trademark of the PSF.
    This EVM Kit does not include Raspberry Pi computer, nor NVIDIA Jetson Nano computer.