IoT Monitoring Dashboard Development
Budget: ₹400 – ₹750 INR
I’m building a live remote-monitoring dashboard that ingests MQTT messages from a teltonikak rtu 901 gateway along with temperature, pressure, and oxygen sensors and many other parameters from a controller. The stack I have in mind runs on DigitalOcean or AWS and is driven by Python on the back-end and JavaScript on the front-end, but I’m happy to discuss refinements if you can justify them.
Current status
• Devices is yet to publish raw readings over MQTT.
• No cloud pipeline, storage layer, or UI exists yet.
What I need next
• A lightweight yet secure ingestion service (Python is preferred) that subscribes to the topics, validates payloads, and writes them to a scalable store on DigitalOcean.
• A real-time dashboard in JavaScript that shows live values, historical charts, and simple alerting rules.
• Clean, well-documented code plus peer reviews/pull-request feedback as we move.
Acceptance criteria
1. Data arrives end-to-end in under two seconds on a basic Droplet test.
2. Dashboard auto-refreshes without a manual reload and renders at least 7-day history.
3. Deploy scripts spin everything up on a fresh DigitalOcean account in one pass.
4. Codebase passes linting and unit tests (>90 % coverage).
If this aligns with your experience in MQTT, Python, JavaScript, and cloud deployment workflows, let’s talk roadmap and timelines.
Current status
• Devices is yet to publish raw readings over MQTT.
• No cloud pipeline, storage layer, or UI exists yet.
What I need next
• A lightweight yet secure ingestion service (Python is preferred) that subscribes to the topics, validates payloads, and writes them to a scalable store on DigitalOcean.
• A real-time dashboard in JavaScript that shows live values, historical charts, and simple alerting rules.
• Clean, well-documented code plus peer reviews/pull-request feedback as we move.
Acceptance criteria
1. Data arrives end-to-end in under two seconds on a basic Droplet test.
2. Dashboard auto-refreshes without a manual reload and renders at least 7-day history.
3. Deploy scripts spin everything up on a fresh DigitalOcean account in one pass.
4. Codebase passes linting and unit tests (>90 % coverage).
If this aligns with your experience in MQTT, Python, JavaScript, and cloud deployment workflows, let’s talk roadmap and timelines.
Related categories:
JavaScript
Python
Linux
Node.js
MQTT
Web Development
Data Visualization
DevOps
API Development
DigitalOcean