Transformer Service

A Go-based microservice that consumes LoRaWAN device data from MQTT topics via RabbitMQ, calculates device locations using RSSI-based trilateration algorithms, and publishes transformed data.

Features

• MQTT Consumer: Consumes device data from RabbitMQ MQTT topics
• Location Calculation: Supports 1, 2, 3, and multiple gateway trilateration
• RSSI-based Distance Estimation: Uses path loss models to estimate distances
• Data Transformation: Converts raw LoRaWAN data to standardized format
• Configurable: YAML and environment variable configuration
• Docker Support: Containerized deployment ready

Architecture

The service is built using:

• RabbitMQ AMQP: Message queue consumer for MQTT topics
• Viper: Configuration management
• Cobra: CLI interface
• Gonum: Mathematical computations for trilateration

Data Flow

LoRaWAN Device → MPA Service → EMQX → RabbitMQ → Transformer Service → Output Topic

1. Input: Consumes from device/data topic via RabbitMQ
2. Processing: Calculates device location using gateway RSSI data
3. Output: Publishes transformed data to transformed/device/location topic

Installation

Prerequisites

• Go 1.24.4 or later
• Docker (optional)

Local Development

1. Clone the repository

2. Install dependencies:

   make deps

3. Run the service:

   make run

Docker

1. Build the Docker image:

   make docker-build

2. Run the container:

   make docker-run

Configuration

The service can be configured via:

1. configs/config.yaml (default configuration)
2. Environment variables
3. Create a .env file with the following example settings:

# Server Configuration
SERVER_LOG_LEVEL=info

# AMQP Configuration
AMQP_BROKER_URL=amqp://admin:password@rabbitmq:5672/
AMQP_EXCHANGE=amq.topic
AMQP_QUEUE=transformer_device_queue
AMQP_ROUTING_KEY=device.data
AMQP_OUTPUT_TOPIC=transformed/device/location
AMQP_CONSUMER_TAG=transformer-service
AMQP_PREFETCH_COUNT=10
AMQP_AUTO_ACK=false

# Raw Data Logging Configuration
RAW_DATA_LOG_DIR=logs/raw_data
RAW_DATA_ENABLE_FILE_LOG=true
RAW_DATA_ENABLE_JSON_LOG=true
RAW_DATA_MAX_FILE_SIZE=104857600

Configuration Options

server:
  log_level: "info"

amqp:
  broker_url: "amqp://admin:password@rabbitmq:5672/"
  exchange: "device_exchange"
  queue: "device_data"
  routing_key: "device.data"
  output_topic: "transformed/device/location"
  consumer_tag: "transformer-service"
  prefetch_count: 10
  auto_ack: false

raw_data_log:
  log_dir: "logs/raw_data"
  enable_file_log: false
  enable_json_log: false
  max_file_size: 104857600  # 100MB

Raw Data Logging

The service supports logging raw data for training and debugging purposes. Configure via environment variables:

RAW_DATA_LOG_DIR="logs/raw_data"           # Directory for log files
RAW_DATA_ENABLE_FILE_LOG=true              # Enable file logging
RAW_DATA_ENABLE_JSON_LOG=false             # Enable JSON stdout logging
RAW_DATA_MAX_FILE_SIZE=104857600           # 100MB file size limit

Log Management with Logrotate

To prevent raw logs from consuming too much disk space, use the included logrotate configuration:

1. Install logrotate configuration:

   sudo cp logrotate.conf /etc/logrotate.d/transformer-raw-logs

2. Test configuration:

   sudo logrotate -d /etc/logrotate.d/transformer-raw-logs

3. Manual rotation:

   sudo logrotate -f /etc/logrotate.d/transformer-raw-logs

The logrotate configuration:

• Rotates logs daily
• Keeps 7 days of logs
• Compresses old files (saves ~90% disk space)
• Handles active log files safely with copytruncate

Message Formats

Input Message (from MPA Service)

{
  "uplink_message": {
    "rx_metadata": [
      {
        "location": {
          "latitude": 10.762622,
          "longitude": 106.660172
        },
        "rssi": -80,
        "snr": 9.5
      }
    ],
    "settings": {
      "frequency": 923200000
    },
    "f_cnt": 123,
    "f_port": 1
  },
  "end_device_ids": {
    "dev_eui": "1234567890ABCDEF",
    "application_ids": {
      "application_id": "my-app"
    }
  },
  "received_at": "2023-01-01T12:00:00Z"
}

Output Message (Transformed)

{
  "device_eui": "1234567890ABCDEF",
  "location": {
    "latitude": 10.762622,
    "longitude": 106.660172,
    "accuracy": "triangulated"
  },
  "timestamp": "2023-01-01T12:00:00Z",
  "organization": "example-org",
  "source": "transformer-service",
  "metadata": {
    "frequency": 923200000,
    "gateways": [
      {
        "rssi": -80,
        "snr": 9.5,
        "location": {
          "latitude": 10.762622,
          "longitude": 106.660172
        }
      }
    ],
    "frame_counter": 123,
    "port": 1
  }
}

Location Calculation

The service supports different trilateration methods based on the number of available gateways:

1. Single Gateway: Returns gateway location
2. Two Gateways: Circle intersection method
3. Three Gateways: Linear system solving
4. Multiple Gateways: Least squares optimization

The distance estimation uses the path loss model:

d = d0 * 10^((PL - PL_d0) / (10 * n))

Where:

• d: estimated distance
• d0: reference distance (1m)
• PL: path loss (TX_power - RSSI)
• PL_d0: path loss at reference distance
• n: path loss exponent (4.0)

Development

Available Make Commands

• make build: Build the binary
• make test: Run tests
• make clean: Clean build artifacts
• make deps: Download dependencies
• make run: Build and run the service
• make fmt: Format code
• make lint: Lint code (requires golangci-lint)
• make security: Security scan (requires gosec)

Testing

Unit Tests

make test

Local Linting & Security Checks

• Tooling (once):

  go install github.com/golangci/golangci-lint/v2/cmd/golangci-lint@v2.4.0
  go install github.com/securego/gosec/v2/cmd/gosec@master

• Transformer service:

  cd transformer-service (optional)
  golangci-lint run
  gosec ./...

Project Structure

├── cmd/transformer/          # Application entry point
│   ├── cmd/                 # CLI commands
│   └── main.go             # Main function
├── internal/               # Private application code
│   ├── config/            # Configuration management
│   ├── handlers/          # HTTP handlers
│   ├── logger/            # Logging setup
│   ├── models/            # Data models
│   └── services/          # Business logic
├── configs/               # Configuration files
├── bin/                   # Built binaries
└── Dockerfile             # Docker configuration

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Run make test and make lint
6. Submit a pull request

License

Licensed under the Apache License, Version 2.0
See the LICENSE file for details.