Meraki License Plate Detector

Description

This project integrates Meraki MV Cameras, MT Sensors and Plate Recognizer software to detect when a garage door is opened to take a snapshot, and detect vehicle license plates.

Workflow

The workflow will be the following:

Before start: What do you need

1. Access to a Meraki Dashboard (and its API key) with an MV Camera and an MT20 Sensor.

2. An AWS Account.

3. A Webex account. You will need it to create a Bot and grab its Access Token. You'll find instructions on how to do it here.

4. A Plate Recognizer account. Free tier available (2500 API calls/month).

Usage

1. Clone this repo to your local machine by typing on your terminal:

https://github.com/agmanuelian/Meraki_License_Plate_Detector.git

2. Install the required dependencies specified in the requirements.txt file:

pip3 install requirements.txt

3. On you AWS account, set up your Lambda Function. When it's time to upload your code, zip the lambda_module directory, and upload the .zip file. Before you do this, be sure to update all your credentials in the lambda_module/main_plate.py file.

Lambda Setup - Step 1

Here you will find an example workflow on how to setup you Lambda function. Replace "facemask" with a relevant name for this project i.e "plate_recognizer"

After you do this, increase the execution time up to 15 seconds, under the Configuration tab.

Lambda Setup - Step 2

4. On you AWS account, set up your API Gateway. Once deployed, grab its public address. You will need it on the next step.

API Gateway Setup - Step 1

Here you will find an example workflow on how to setup you API Gateway. Replace "facemask" with a relevant name for this project i.e "plate_recognizer"

API Gateway Setup - Step 2

5. On your Meraki Dashboard, set up a new Webhook receiver (Network-Wide -> Alerts) with the public address you got on the previous step.

6. Set up a new Alert profile for your MT20 sensor, with a notification set to the recently added Webhook receiver. Don't forget to add this Alert profile to the sensor.

7. Add your recently created bot to a Webex room. The bot access token and the Room ID should be already configured on the lambda_module/main_plate.py file.

8. You are done! When the alert is triggered by the sensor, you will receive a Webex message with the analysis results.

Output

These are the results of the image analysis posted into a Webex Room.

Links to DevNet Learning Labs

Meraki Learning Lab

Related Sandbox

Meraki Always On Sandbox

Meraki Enterprise Sandbox