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
Industrial IoT | Edge Automation | Custom Hardware & Web Application
Overview
An industrial water management company operating multiple large-capacity storage tanks required a reliable and automated system to monitor water levels and control valves efficiently. The organization depended on manual supervision, which often resulted in overflow incidents, water wastage, and a lack of operational visibility. The client sought a fully automated, edge-based IoT solution capable of providing real-time monitoring, intelligent valve control, and historical data tracking — without relying on cloud connectivity.
The Challenge
The company faced several operational challenges in managing its storage tanks. There was no real-time visibility into current water levels, making it difficult to make timely decisions. Manual valve operation increased the risk of overflow and resource wastage. Additionally, the absence of historical data limited the ability to analyze usage patterns and generate reports for operational planning. The client required a local, high-reliability system capable of performing both automated and manual valve control while ensuring continuous operation within the industrial environment.
Aceomation’s Solution
Aceomation designed and deployed a custom Industrial IoT system combining purpose-built water level sensing hardware, wireless communication modules, edge-based automation using Raspberry Pi, and a web-based monitoring dashboard. All processing and automation logic were executed locally on the edge device, ensuring fast response times, high reliability, and zero dependency on external cloud infrastructure.
System Architecture
The solution architecture was designed for seamless integration and industrial reliability: Tank Sensors → Wi-Fi Communication Modules → Raspberry Pi (Edge Server) → Valve Control Hardware → Web Dashboard
How the System Works
Real-Time Water Level Data Collection
Aceomation developed custom hardware installed in each tank to measure water levels in liters with high accuracy. Each tank is equipped with a dedicated sensing module that transmits data wirelessly via Wi-Fi. Data from multiple tanks is sent simultaneously to a centralized edge system for processing and control.
Aceomation developed custom hardware installed in each tank to measure water levels in liters with high accuracy. Each tank is equipped with a dedicated sensing module that transmits data wirelessly via Wi-Fi. Data from multiple tanks is sent simultaneously to a centralized edge system for processing and control.
Central Edge Processing
A Raspberry Pi running Linux OS serves as the main controller and edge server. A Node.js backend application receives real-time water level data, stores both current and historical readings, and evaluates control rules using scheduled background processes. This ensures instant decision-making without cloud latency.
A Raspberry Pi running Linux OS serves as the main controller and edge server. A Node.js backend application receives real-time water level data, stores both current and historical readings, and evaluates control rules using scheduled background processes. This ensures instant decision-making without cloud latency.
Automated Valve Control Logic
To prevent overflow and optimize water usage, Aceomation implemented intelligent rule-based automation. When a tank reaches a predefined water level threshold, the backend automatically evaluates the condition through scheduled checks. If the threshold is met, the system sends a control signal to the valve interface hardware, enabling or disabling the valve as configured. The same automation logic is applied independently to each tank, ensuring consistent and reliable operation without manual intervention.
To prevent overflow and optimize water usage, Aceomation implemented intelligent rule-based automation. When a tank reaches a predefined water level threshold, the backend automatically evaluates the condition through scheduled checks. If the threshold is met, the system sends a control signal to the valve interface hardware, enabling or disabling the valve as configured. The same automation logic is applied independently to each tank, ensuring consistent and reliable operation without manual intervention.
Manual & Automatic Control Modes
To provide operational flexibility, Aceomation developed a React.js-based valve control interface hosted on the edge device. Operators can switch between automatic and manual modes at any time. In manual mode, valves can be opened or closed instantly, while the system continues to display real-time tank levels and valve status. This dual-mode functionality ensures that automation can be overridden whenever required for maintenance or operational adjustments.
To provide operational flexibility, Aceomation developed a React.js-based valve control interface hosted on the edge device. Operators can switch between automatic and manual modes at any time. In manual mode, valves can be opened or closed instantly, while the system continues to display real-time tank levels and valve status. This dual-mode functionality ensures that automation can be overridden whenever required for maintenance or operational adjustments.
Monitoring & Reporting Dashboard
The web-based dashboard provides complete visibility into system performance. Operators can view live water levels for all tanks, clearly identify tank status, and monitor valve open/close conditions in real time. The system also maintains historical water level records, enabling performance analysis and audit reporting. Water level data can be exported as Excel reports for documentation, analysis, and compliance purposes.
Deployment & Reliability
Both frontend (React.js) and backend (Node.js) applications are deployed directly on the Raspberry Pi edge device. The system is managed using PM2 to ensure 24/7 uptime, automatic restarts, and uninterrupted operation. The web interface can be accessed locally from the Raspberry Pi or remotely from another computer within the same network using a dedicated IP address.
Custom Industrial Hardware
Aceomation engineered and deployed specialized hardware components tailored for industrial conditions. This included custom water level sensing devices, Wi-Fi data transmission modules, and valve control interface hardware. All hardware components were designed for continuous operation in demanding industrial environments, ensuring stable communication, accurate measurement, and long-term durability.
Results
- Real-time water level visibility
- Automated overflow prevention
- Reduced water wastage
- Flexible manual and automatic valve control
- Complete historical data tracking
- Reliable 24/7 edge-based operation
Conclusion
Aceomation transformed a manual, error-prone water management process into an intelligent, automated Industrial IoT system. By combining custom hardware, edge computing, and real-time automation, the client achieved improved efficiency, resource optimization, and operational reliability. Intelligent monitoring. Automated control. Reliable performance.
