The Rise of Edge Computing in Industrial IoT
The Industrial Internet of Things (IIoT) continues to evolve, and one of the most transformative trends in this space is the rise of edge computing.
As factories and industrial environments generate increasing amounts of data, processing that information close to where it is created — rather than sending everything to the cloud — is becoming essential.
Why Edge Matters in IIoT
Traditional cloud-based models have limitations when it comes to real-time decision-making.
For mission-critical systems such as quality control, utility automation, or production line monitoring, latency and intermittent connectivity can seriously impact performance.
Edge computing addresses these challenges by enabling:
- Real-time decision-making through rule-based logic and automation running directly on edge hardware
- Reduced data bandwidth costs by transmitting only critical information to the cloud or central platforms
- Improved system resilience, allowing operations to continue even during network outages
Real Industrial Impact
In a manufacturing environment, an edge-enabled system can immediately respond to anomalies such as deviations in product weight or unexpected machine temperature changes without waiting for cloud-based validation.
This immediate response capability increases operational uptime, reduces risk, and improves overall quality assurance across production processes.
As IIoT deployments continue to expand across manufacturing, energy, utilities, and infrastructure sectors, edge computing is increasingly becoming the foundation of modern industrial automation.
Automated Water Level Monitoring & Valve Control for Industrial Storage Tanks
Industry
Water Level Monitoring & Utility Automation
Solution Type
Industrial IoT | Edge Automation | Custom Hardware + Web Application
Client Challenge
A water level monitoring industry manages multiple large-capacity storage tanks used for industrial water management.
Challenges faced:
- No reliable real-time visibility of water levels
- Manual valve operation caused overflow and wastage
- Lack of historical data for analysis and reporting
- Need for both automatic and manual control
The client required a local, reliable, and automated IoT system to monitor water levels and control valves without depending on cloud connectivity.
Aceomation’s Solution
Aceomation designed a custom Industrial IoT solution that combines:
- Custom-built water level sensing hardware
- Wireless data communication
- Edge-based automation using Raspberry Pi
- Web-based monitoring and control dashboard
All logic runs locally, ensuring fast response and high reliability.
System Architecture Overview
Tank Sensors → Wi-Fi Hardware Modules → Raspberry Pi (Edge Server) → Valve Control Hardware → Web Dashboard
How the System Works
Step 1: Water Level Data Collection
Aceomation built custom water level measurement hardware for each tank
Each tank’s hardware:
- Measures water level in liters
- Sends data via Wi-Fi
Data from both tanks is transmitted simultaneously to a central system
Step 2: Central Data Processing (Edge System)
A Raspberry Pi running Linux OS acts as the main controller
A Node.js backend:
- Receives real-time water level data
- Stores current and historical readings
- Evaluates control rules using scheduled checks
Step 3: Automated Valve Control Logic
To prevent overflow and ensure efficient water usage, Aceomation implemented automatic valve control.
Control Logic Example
When Tank 1 reaches specific liters:
- A scheduled backend process (cron job) evaluates the water level
- If the threshold is reached:
- The backend sends a control signal to the valve hardware
- The valve is automatically enabled or disabled as configured
The same automation logic is implemented for Tank 2
This ensures consistent, rule-based control without manual intervention.
Manual & Automatic Valve Control
Aceomation developed a React.js-based valve control interface.
Users can:
- Switch between Automatic and Manual modes
- Open or close valves instantly
- Monitor valve status in real time
- Override automation when required
This dual-control approach provides operational flexibility.
Monitoring & Reporting Dashboard
Real-Time Visualization
- Live water level for both tanks
- Clear visual indicators of tank status
- Valve open/close state display
Data Management
- Historical water level tracking
- Newly added water level records
- Export data as Excel reports for analysis and audits
Deployment & Reliability
Frontend (React.js) and Backend (Node.js) are deployed on the Raspberry Pi
Applications are managed using PM2 for:
- 24/7 uptime
- Automatic restarts
The web application is accessible from:
- Raspberry Pi local interface
- Another computer via a separate IP address within the network
Custom Hardware Built by Aceomation
- Water level sensing hardware
- Wi-Fi-based data transmission modules
- Valve control interface hardware
- Designed for continuous industrial operation
