IoT & Hardware Integration Guide
Comprehensive documentation for integrating ML models with industrial IoT sensors and hardware systems
Overview
This documentation series provides a complete guide for integrating our water quality ML models with industrial IoT systems, specifically designed for compatibility with Neilsoft's plant engineering and industrial automation services.
Target Client: Neilsoft
- Website: https://neilsoft.com
- Key Services: Plant & Factory Engineering, Industrial Automation & IoT, BIM for Plants
- Integration Focus: STP/ETP monitoring, SCADA systems, PLC integration
Documentation Index
| # | Document | Description |
|---|---|---|
| 01 | Architecture Overview | System architecture and data flow |
| 02 | Hardware Sensors | Recommended sensors and devices |
| 03 | Software Stack | IoT platforms and middleware |
| 04 | Protocol Adapters | MQTT, OPC-UA, Modbus integration |
| 05 | API Integration | REST/WebSocket endpoints for IoT |
| 06 | Edge Deployment | Edge computing and local inference |
| 07 | Data Pipeline | Real-time data streaming architecture |
| 08 | Neilsoft Integration | Client-specific integration guide |
| 09 | Implementation Roadmap | Phase-wise implementation plan |
| 10 | Testing & Simulation | Sensor simulation and testing |
Our ML Models
| Model | Purpose | Key Parameters |
|---|---|---|
| Prediction Model | Water reusability prediction with CPCB compliance | BOD, COD, TSS, TDS, pH, flow rate |
| Treatment Model | Treatment stage recommendation | pH, TSS, Turbidity, BOD, COD, NH4-N |
| Twin Engine | Combined reusability + treatment analysis | All parameters |
| Adaptive Optimizers | Real-time simulation with anomaly detection | Continuous sensor streams |
Quick Start
Prerequisites
- Node.js 18+ / Python 3.10+
- MQTT Broker (EMQX/Mosquitto)
- Docker & Docker Compose
- Access to sensor hardware or simulator
Installation
# Install IoT dependencies
npm install mqtt node-opcua modbus-serial
# Install edge inference dependencies
pip install tensorflow-lite onnxruntime
# Start MQTT broker (development)
docker run -d --name emqx -p 1883:1883 -p 8083:8083 emqx/emqx:latest
Architecture Preview
┌─────────────────────────────────────────────────────────────────┐
│ ML MODELS (Next.js API) │
│ Prediction | Treatment | Twin Engine | Adaptive Optimizers │
└─────────────────────────────────────────────────────────────────┘
▲
│ REST API / WebSocket
│
┌─────────────────────────────────────────────────────────────────┐
│ IoT MIDDLEWARE LAYER │
│ Node-RED | Apache Kafka | AWS IoT Greengrass | Azure IoT Edge │
└─────────────────────────────────────────────────────────────────┘
▲
│ MQTT / OPC-UA / Modbus
│
┌─────────────────────────────────────────────────────────────────┐
│ EDGE GATEWAY LAYER │
│ Siemens IOT2050 | Kepware KEPServerEX | Ignition Edge │
└─────────────────────────────────────────────────────────────────┘
▲
│ 4-20mA / Modbus RTU / HART
│
┌─────────────────────────────────────────────────────────────────┐
│ SENSOR LAYER │
│ pH | BOD | COD | TSS | TDS | Flow | Temperature | DO │
└─────────────────────────────────────────────────────────────────┘
Key Benefits for Neilsoft Clients
- Real-time Monitoring: Live water quality predictions from sensor data
- CPCB Compliance: Automated compliance checking and alerts
- Treatment Optimization: AI-driven treatment recommendations
- Cost Reduction: Optimized chemical dosing based on predictions
- Predictive Maintenance: Anomaly detection for early warning
- Digital Twin: Integration with BIM models for 3D visualization
Support
For integration support, contact the development team or refer to individual documentation files for detailed implementation guides.
Last Updated: December 2024