Influx-to-Website

npm install @influxdata/influxdb-client

Next Steps

Feature Requests

1. Allow custom x-axis, to plot sensor value against another value
2. [completed] Overlay of graphs (Influxdb graph viewer supports natively)
3. Pull units from InfluxDB and display on the graph

Testing setup - with Python script and docker Influx - HZ

1. clone https://github.com/Western-Formula-Racing/car_to_influx
2. The relevant Python script here is readCAN3batchSender.py
3. Make sure to set the correct TOKEN in the script

Docker - Influx

1. Install Docker
2. in cmd:

sudo docker run -d \
  --name influxwfr \
  -p 8086:8086 \
  -v ~/influxdb/data:/var/lib/influxdb2 \
  -v ~/influxdb/config:/etc/influxdb2 \
  -e DOCKER_INFLUXDB_INIT_MODE=setup \
  -e DOCKER_INFLUXDB_INIT_USERNAME=myuser \
  -e DOCKER_INFLUXDB_INIT_PASSWORD=mypassword123 \
  -e DOCKER_INFLUXDB_INIT_ORG=WFR \
  -e DOCKER_INFLUXDB_INIT_BUCKET=ourCar \
  influxdb:2

In the address bar at the top, type: http://localhost:8086

You should see a login screen

Log in using:

• Username: myuser
• Password: mypassword123

Then:

1. Find API Key
2. Create an organization called WFR
   1. click your profile icon, then click Create Organization
3. Create a new bucket in Influx: call it "ourCar" <- you can change this in the python script, just make sure it matches.
   1. Consider changing the data retention policy to 1 hour to keep it clean for every testing session

Now, start running the Python code and use the graph viewer to view the testing data:

If you want something that's constantly moving:

ourCar-canBus-sensorReading-M166_Current_info-166-INV_Phase_A_Current

Query Data Processing Pipeline

1. Query Execution (executeQuery function):

   • Takes a Flux query as input
   • Makes a POST request to InfluxDB's API endpoint with:
     • URL: ${influxConfig.url}/api/v2/query?org=${influxConfig.org}
     • Authentication: Token-based via headers
     • Request format: Flux query language (application/vnd.flux)
     • Response format: CSV (application/csv)
   • Checks for successful response (response.ok)
   • Converts response to text (CSV format)
   • Passes CSV to parseInfluxResponse

2. CSV Parsing (parseInfluxResponse function):

   Input Validation:

   if (!csvData || csvData.trim() === '') {
     return [];
   }

   • Checks if data exists and isn't empty

   Data Structure Analysis:

   const lines = csvData.trim().split('\n');
   if (lines.length < 2) {
     return [];
   }

   • Splits CSV into lines
   • Ensures there's at least a header and one data row

   Header Processing:

   const headers = lines[0].split(',');
   const timeIndex = headers.findIndex(h => h === '_time');
   const valueIndex = headers.findIndex(h => h === '_value');

   • Extracts column headers
   • Locates critical columns: '_time' and '_value'

   Data Transformation Pipeline:

   return lines.slice(1)
       .filter(line => line.trim() !== '')
       .map(line => {
         const values = line.split(',');
         return {
           _time: values[timeIndex],
           _value: parseFloat(values[valueIndex])
         };
       })
       .filter(point => !isNaN(point._value));

   1. slice(1): Skips header row
   2. First filter: Removes empty lines
   3. map: Transforms each line into an object with _time and _value
   4. Second filter: Removes entries with invalid numerical values

The final output is an array of objects, each containing:

• _time: Timestamp from InfluxDB
• _value: Numerical value (sensor reading)

Example transformation:

Input CSV:
_time,_value,_field,_measurement
2024-02-09T12:00:00Z,23.5,temperature,sensors
2024-02-09T12:00:01Z,24.0,temperature,sensors

Output:
[
  { _time: "2024-02-09T12:00:00Z", _value: 23.5 },
  { _time: "2024-02-09T12:00:01Z", _value: 24.0 }
]

Future Development: On the live monitor dashboard, the x-axis of the plot should be -60s to 0s (current), instead of absolute time.

Hosting

Install Docker

sudo apt update
sudo apt upgrade -y
sudo apt-get install apt-transport-https ca-certificates curl software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
sudo apt-get update

sudo apt-get install docker-ce
sudo docker run hello-world

Set up Docker/Influx

1. Export local docker: docker tag influxdb:latest myusername/influxdb:latest

docker push myusername/influxdb:latest

🚀 Step 1: Pull the Latest InfluxDB Image

sudo docker pull influxdb:2

---

🚀 Step 2: Create Directories for Persistent Storage

Create directories on your Lightsail instance to store InfluxDB data and configurations:

mkdir -p ~/influxdb/data
mkdir -p ~/influxdb/config

Give Docker permission to access them:

sudo chown -R 1000:1000 ~/influxdb

🚀 Step 3: Run the InfluxDB Container with the Correct Settings

Now, run the container using your updated configuration:

sudo docker run -d \
  --name influxwfr \
  -p 8086:8086 \
  -v ~/influxdb/data:/var/lib/influxdb2 \
  -v ~/influxdb/config:/etc/influxdb2 \
  -e DOCKER_INFLUXDB_INIT_MODE=setup \
  -e DOCKER_INFLUXDB_INIT_USERNAME=myuser \
  -e DOCKER_INFLUXDB_INIT_PASSWORD=mypassword123 \
  -e DOCKER_INFLUXDB_INIT_ORG=WFR \
  -e DOCKER_INFLUXDB_INIT_BUCKET=ourCar \
  influxdb:2

🚀 Step 4: Verify the Container is Running

Check the status:

sudo docker ps -a

​ • If STATUS is Up, the container is running. ✅

​ • If it exits, check logs:

sudo docker logs influxwfr

🚀 Step 5: Test the Connection

1️⃣ Check if InfluxDB is listening inside the container:

sudo docker exec -it influxwfr influx ping

Expected output:

OK

2️⃣ Test the API on your Lightsail instance:

curl -i http://localhost:8086/ping

Expected output:

HTTP/1.1 204 No Content

3️⃣ Test from your local machine:

curl -i http://YOURIP:8086/ping

You can also try to access the GUI through http://YOURIP:8086

If this fails, double-check AWS Lightsail Firewall Rules to allow inbound traffic on port 8086.

🚀 Step 6: Retrieve Your InfluxDB Token

Run:

sudo docker exec influxwfr influx auth list

Copy the admin token, as you’ll need it for your Python script.

🚀 Step 7: Update Your Python Script (readCANxxx.py)

Modify your script to use the correct InfluxDB credentials:

influx_url = "http://YOURIP:8086"
token is saved in a seperate txt

Run the script:

python readCAN3batchSender.py

Set Auto Start on Ubuntu for Docker

sudo docker update --restart unless-stopped influxwfr

sudo systemctl enable docker

Check if it works:

sudo reboot

sudo docker ps

Authentication System

This project now includes a comprehensive authentication system using MongoDB and JWT (JSON Web Tokens).

Features

• User authentication with JWT tokens
• Protected routes for authorized access
• MongoDB integration for user storage
• Role-based access control (admin users)

Setup

1. Make sure MongoDB is properly configured with your connection string in .env file: DATABASE_URI=mongodb+srv://your_username:your_password@your_cluster_url/?retryWrites=true&w=majority JWT_SECRET=your_jwt_secret

2. Create an admin user by running:

cd backend
node scripts/setup-admin.js
npm install
npm install -g nodemon
nodemon index.js

3. Default admin credentials:

• Username: admin
• Password: admin123

Usage

• Login via the login page to receive a JWT token
• Protected routes will automatically check for valid authentication
• The token is stored in localStorage and will persist until logout
• Admin users have additional privileges to manage other users

lap.py Lap Detector

## 🚀 API: `GET /api/track`

1. 📍 Location Data

• Query: ?type=location
• Description: Returns the most recent GPS coordinate (latitude and longitude) of the vehicle.
• Response:

{
  "location": {
    "lat": 42.06648123,
    "lon": -84.24137456
  }
}

• Example Usage:

curl "http://127.0.0.1:8050/api/track?type=location"

fetch("http://127.0.0.1:8050/api/track?type=location")
  .then(res => res.json())
  .then(data => console.log(data.location));

---

2. 🏁 Last Completed Lap

• Query: ?type=lap
• Description: Returns the latest completed lap with GPS path and start/end timestamps.
• Response:

{
  "lap": {
    "points": {
      "lats": [42.0664, 42.0665, ...],
      "lons": [-84.2413, -84.2412, ...]
    },
    "start_time": 1711931802.745823,
    "end_time": 1711931823.462191
  }
}

• Example Usage:

curl "http://127.0.0.1:8050/api/track?type=lap"

import requests
res = requests.get("http://127.0.0.1:8050/api/track?type=lap")
lap = res.json()["lap"]
print(lap["start_time"], lap["end_time"])

---

3. ❌ Invalid Request

• If an unsupported type is passed, the response will be:

{
  "error": "Invalid request type"
}

• HTTP Status: 400 Bad Request

---

📘 Summary

Endpoint	Type	Description	Response Key
/api/track?type=location	location	Returns latest GPS point	location
/api/track?type=lap	lap	Returns last completed lap	lap

Influx CLI User Management

InfluxDB 2.x User Management Notecard

1. Creating a New User

To create a new user (e.g., “admin”) within the organization “WFR”, use:

sudo docker exec -it influxwfr influx user create \
  --name admin \
  --password pwd \
  --org WFR

Note: The --role flag is not supported in the current CLI version.

---

2. Changing a User’s Password

To update the password for a user (e.g., “admin”), run:

sudo docker exec -it influxwfr influx user password --name admin

You will be prompted to enter the new password interactively.

---

3. Deleting a User

To delete a user, first list users to retrieve the user’s ID:

sudo docker exec -it influxwfr influx user list

Then delete the user using its unique ID (for example, 0eaa6d2e8865b000):

sudo docker exec -it influxwfr influx user delete --id 0eaa6d2e8865b000

Note: The delete command requires the --id flag—not --name.

Frontend Deployment

The React frontend is automatically deployed to the production server using GitHub Actions.

Live Application

• Production URL: http://3.98.181.12:8060
• Auto-deployment: Triggers on every push to main branch

🛠️ Development Setup

Local Development

cd my-react-app
npm install
npm run dev  # Runs on http://localhost:5173