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On this page
  • Installing dependencies
  • Connecting to Edge Impulse
  • Next steps: building a machine learning model
  • Deploying back to device
  • Connect to the LoraWAN® Network
  • Configure your model on the SenseCap Mate

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  1. Edge AI Hardware
  2. Production-ready

Seeed SenseCAP A1101

PreviousAdvantech ICAM-540NextIndustry reference design - BrickML

Last updated 2 months ago

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- LoraWAN Vision AI Sensor is an image recognition AI sensor designed for developers. SenseCAP A1101 - LoRaWAN Vision AI Sensor combines TinyML AI technology and LoRaWAN long-range transmission to enable a low-power, high-performance AI device solution for both indoor and outdoor use.

This sensor features Himax high-performance, low-power AI vision solution which supports the Google LiteRT (previously Tensorflow Lite) framework and multiple TinyML AI platforms.

It is fully supported by Edge Impulse which means you will be able to sample raw data from the camera, build models, and deploy trained machine learning models to the module directly from the studio without any programming required. SenseCAP - Vision AI Module is available for purchase directly from .

Installing dependencies

To set A1101 up in Edge Impulse, you will need to install the following software:

  1. On Linux:

    • GNU Screen: install for example via sudo apt install screen.

Problems installing the Edge Impulse CLI?

Connecting to Edge Impulse

With all the software in place, it's time to connect the A1101 to Edge Impulse.

1. Update BL702 chip firmware

BL702 is the USB-UART chip which enables the communication between the PC and the Himax chip. You need to update this firmware in order for the Edge Impulse firmware to work properly.

  1. Connect the A1101 to the PC via a USB Type-C cable while holding down the Boot button on the A1101.

  2. Open previously installed Bouffalo Lab Dev Cube software, select BL702/704/706, and then click Finish

  3. Go to the MCU tab. Under Image file, click Browse and select the firmware you just downloaded.

  4. Click Refresh, choose the Port related to the connected A1101, set Chip Erase to True, click Open UART, click Create & Download and wait for the process to be completed .

You will see the output as All Success if it went well.

If the flashing throws an error, click Create & Download multiple times until you see the All Success message.

2. Update Edge Impulse firmware

A1101 does not come with the right Edge Impulse firmware yet. To update the firmware:

  1. Connect the A1101 again to the PC via USB Type-C cable and double-click the Boot button on the A1101 to enter mass storage mode

  2. After this you will see a new storage drive shown on your file explorer as SENSECAP. Drag and drop the firmware.uf2 file to SENSECAP drive

Once the copying is finished SENSECAP drive will disappear. This is how we can check whether the copying is successful or not.

3. Setting keys

From a command prompt or terminal, run:

edge-impulse-daemon

This will start a wizard which will ask you to log in, and choose an Edge Impulse project. If you want to switch projects run the command with --clean.

4. Verifying that the device is connected

Device connected to Edge Impulse correctly!

Next steps: building a machine learning model

With everything set up, you can now build and run your first machine learning model with these tutorials:

Collecting data from Seeed SenseCAP A1101

Frames from the onboard camera can be directly captured from the studio:

Finally, once a model is trained, it can be easily deployed to the A1101 – Vision AI Module to start inferencing!

Deploying back to device

Drag and drop the firmware.uf2 file from EDGE IMPULSE to SENSECAP drive.

When you run this on your local interface:

edge-impulse-daemon --debug

it will ask you to click a URL, then you will see a live preview of the camera on your device.

Compile Edge Impulse firmware from source

Connect to the LoraWAN® Network

Since our focus here is on describing the model training process, we won't go into the details of the cloud platform data display. But if you're interested, you can always visit the SenseCAP cloud platform to try adding devices and viewing data. It's a great way to get a better understanding of the platform's capabilities!

How to Select a LoRaWAN Gateway

LoRaWAN® network coverage is required when using sensors, there are two options.

Seeed provides:

Configure your model on the SenseCap Mate

  1. Open SenseCAP Mate and login

  2. Under Config screen, select Vision AI Sensor

  3. Press and hold the configuration button on the SenseCap A1101 for 3 seconds to enter bluetooth pairing mode

  4. Click Setup and it will start scanning for nearby SenseCAP A1101 devices- Go to Settings and make sure Object Detection and User Defined 1 is selected. If not, select it and click Send

  5. Go to General and click Detect, you'll see the actual data here.

  6. Click Connect button. Then you will see a pop up on the browser. Select SenseCAP Vision AI - Paired and click Connect

  7. View real-time inference results using the preview window!

The cats are detected with bounding boxes around them. Here "0" corresponds to each detection of the same class. If you have multiple classes, they will be named as 0, 1, 2, 3, 4 and so on. Also the confidence score for each detected object (0.72 in above demo) is displayed!

.

Download the latest

See the guide.

(tinyuf2-sensecap_vision_ai_X.X.X.bin.)

Download the latest and extract it to obtain firmware.uf2 file

Alternatively, recent versions of Google Chrome and Microsoft Edge can collect data directly from your A1101, without the need for the Edge Impulse CLI. See for more information.

That's all! Your device is now connected to Edge Impulse. To verify this, go to , and click Devices. The device will be listed here.

..

.

Looking to connect different sensors? The lets you easily send data from any sensor into Edge Impulse.

After building the machine learning model and downloading the Edge Impulse firmware from Edge Impulse Studio, deploy the model uf2 to SenseCAP - Vision AI by following steps 1 and 2 under

If you want to compile the Edge Impulse firmware from the source code, you can visit and follow the instructions included in the README.

The model used for the official firmware can be found in this .

In addition to connecting directly to a computer to view real-time detection data, you can also transmit these data through LoraWAN® and finally upload them to the or a third-party cloud platform. On the SenseCAP cloud platform, you can view the data in a cycle and display it graphically through your mobile phone or computer. The SenseCAP cloud platform and SenseCAP Mate App use the same account system.

You can get more information on .

for Helium network

for standard LoraWAN® network

Download

to open a preview window of the camera stream

Edge Impulse CLI
Bouffalo Lab Dev Cube-All-Platform
Installation and troubleshooting
Get the latest bootloader firmware
Edge Impulse firmware
this blog post
your Edge Impulse project
object detection
Object detection with centroids (FOMO)
Data forwarder
this GitHub repo
public project
SenseCAP cloud platform
how to use SenseCAP A1101 here
SenseCAP M2
SenseCAP M2 Multi-Platform
SenseCAP Mate
Android
iOS
Click here
Update Edge Impulse firmware
Seeed SenseCAP A1101
Seeed Studio Bazaar
Seeed SenseCAP A1101
Device connected to Edge Impulse