Example project using the Serverless Framework, Python, AWS Lambda and AWS IoT Core Wireless (LoRaWAN) to interface between the LoRa Edge(TM) Tracker Reference Design and a cloud-based geolocation solver. This code utilizes the API will and if present it convert the ROSE-encoded stream into data sources or will store the stream to the data sources. These data sources include WiFi and GNSS scans which can be passed back to cloud server for position computation. While this example is developed for AWS Lambda using AWS IoT Core Wireless functions, it could be simply adapted to other platforms or environments as required.
Secrets are injected into your functions using environment variables. By
defining variables in the provider section of the serverless.yml you add
them to the environment of the deployed function. From there, you can reference
them in your functions as well.
A specific variable that will be required is the token used to access cloud solver.
provider:
environment:
DAS_KEY: ${env:DAS_KEY}to your serverless.yml, and then you can add DAS_KEY to your environment
variables to be deployed with your function.
*. Create AWS credentials including the following IAM policies: AWSLambdaFullAccess, AmazonAPIGatewayAdministrator, AWSCloudFormationFullAccess, and iotwireless:SendDataToWirelessDevice. For logging: logs:CreateLogGroup, logs:CreateLogStream, and logs:PutLogEvents
The cloud solver has been licensed to premier cloud partners including the AWS Iot Core Device Location, AICDL service and Traxmate Cloud for LoRaWAN.
