True
Product Image

People Counting Machine

₱ 2,799.00 ₱ 2,799.00

People Counting Machine

Create a new review

With TinyML running right on the ATSAMD51 powered Wio Terminal, we can train a machine learning model on distance patterns to recognize when people move in or out of a room.
With some additional programming to keep count and using the Wio Terminal's onboard WiFi & Bluetooth, we can quickly build a cloud-connected application to monitor room occupancy remotely with IoT platforms like Azure IoT Central.

1

₱ 2,799.00 ₱ 2,799.00 2799.0 PHP

₱ 2,799.00

(0% Off)
Days
:
Hours
:
Mins
:
Secs

    This combination does not exist.

    Add to Cart
    SKU:
    N/A
    Share :

    Seeed Studio

    Seeed has been serving the global developer community since 2008, by providing open technology and agile manufacturing services, with the mission to make hardware more accessible and lower the threshold for hardware innovation. With Shenzhen’s vast resources, and trusted technology and distribution partners around the world, Seeed strives to be the most integrated platform for creating hardware solutions for IoT, edge AI applications.


    • 30-day money-back
    • 7-day returns
    • Shipping: 2-3 Days

     
     

    An ordinary ultrasonic ranger can easily measure changes in distance to obstacles, but what about complex real-world tasks like people counting?


    Well, with TinyML running right on the ATSAMD51 powered Wio Terminal, we can train a machine learning model on distance patterns to recognize when people are moving in or out of a room!


    With some additional programming to keep count and using the Wio Terminal's onboard WiFi & Bluetooth, we can quickly build a cloud-connected application to monitor room occupancy remotely with IoT platforms like Azure IoT Central!


    Ultrasonic Distance Sensor is an ultrasonic transducer that utilizes ultrasonic waves to measures distance. It can measure from 3cm to 350cm with an accuracy of up to 2mm. We can use the ultrasonic sensor to determine the direction of objects. What if you want to train a model to detect walk-in and walk out of the room? Let's create a new project on Edge Impulse Dashboard and prepare to get the data. Since we don't need a very high sampling frequency for gathering the data, we can use a data forwarder tool from edge-impulse-cli. 


    Upload the ei_people_counter_data_collection.ino script (Please follow up this guide and upload the script in the article) to Wio Terminal – to learn more about how to set up edge-impulse-cli and data forwarder protocol, watch the first video of the TinyML series.


    You might need to set this value lower or higher for your application, depending on the setup. Then start walking.

    Features

    • Powered by TinyML, train machine learning model on distance patterns

    • Build system and learn TinyML quickly with step by step tutorial

    • Plug and Play Grove Sensors

    • Gather the data through Edge Impulse 

    • Use continuous inference examples to make sure not to miss any critical data.

    • Store the room occupancy data in the cloud and visualize it on a PC

    • Connect to Azure IoT Central, watch the detailed progress feedback on the Serial Terminal

    Continuous Inference

    We can also use continuous inference examples to make sure we are not missing any critical data. Clone Seeed studio example sketches repository and open people_counting_continious.ino sketch with Arduino IDE, change the name of the Edge Impulse library to one matching your project name, choose Wio Terminal as your board, install Grove Ultrasonic sensor library and upload the sketch.

    Azure IoT Central Integration

    Your model works! However, it is not suitable for actually applying it in the real world without visualization. Let's add two elements to make it into a full-fledged application – a simple GUI and data upload to the cloud with pretty graphs. We will use LVGL library for creating the graphical user interface and Microsoft Azure IoT Central service for sending data to and visualization. It is much more fun and valuable to combine Azure and Edge Impulse work.

    This is a preview of the recently viewed products by the user.
    Once the user has seen at least one product this snippet will be visible.

    Recently viewed Products

    To install this Web App in your iPhone/iPad press and then Add to Home Screen.