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 Weight Validation & QR-Based Traceability for Copper Wire Manufacturing
Industry
Wire & Cable Manufacturing
Solution
Industrial IoT | Edge-Based Automation | Custom Hardware & Software Integration
Overview
A leading copper wire manufacturer producing multiple wire specifications required a highly accurate, automated validation system to eliminate manual errors during packaging. The company manufactures wires in various configurations, including different wire sizes (e.g., 0.75 sq.mm), lengths (e.g., 40 meters), and insulation classes (e.g., Class 2, FR). During production, individual wire coils are first packed into smaller boxes, which are then consolidated into larger master cartons. Each master carton carries a QR code containing detailed wire specifications. However, ensuring that every master carton met strict weight tolerances based on its configuration was a critical operational challenge.
The Challenge
Each master box was required to meet a predefined weight range depending on its wire specifications. For example, a box with an expected weight of 30.6 kg had an allowed tolerance range between 28.6 kg and 32.6 kg. Manual verification processes led to frequent errors. Incorrectly packed boxes occasionally moved forward to dispatch, creating compliance risks and quality issues. There was no reliable digital traceability system to track validation history, and operators lacked real-time visibility into pass/fail decisions. The client needed a fully automated, high-accuracy validation system that could operate directly on the shop floor without dependency on cloud connectivity.
Aceomation’s Solution
Aceomation designed and implemented a custom Industrial IoT system powered by edge computing. The solution combined purpose-built hardware, intelligent validation logic, and an on-device web application to ensure real-time decision-making. All processing was performed locally on an edge device, ensuring high-speed performance, uninterrupted operation, and zero reliance on internet connectivity.
System Architecture
The system architecture was designed for seamless factory-floor integration: QR Scanner and Custom Weight Calibration Hardware → Raspberry Pi (Edge Processing System) → Printer and Operator Dashboard
How the System Works
QR Code Identification
Each master box carries a QR code containing its wire specifications, including size, length, and insulation class. As the box reaches the validation station, the QR scanner reads the code and transmits the data via Ethernet to the edge system.
Each master box carries a QR code containing its wire specifications, including size, length, and insulation class. As the box reaches the validation station, the QR scanner reads the code and transmits the data via Ethernet to the edge system.
Real-Time Weight Acquisition
Aceomation developed custom hardware to interface directly with the existing weight calibration machine. The actual weight of the box is transmitted to the system through USB communication and captured in real time.
Aceomation developed custom hardware to interface directly with the existing weight calibration machine. The actual weight of the box is transmitted to the system through USB communication and captured in real time.
Intelligent Edge Validation
A Node.js backend running on a Raspberry Pi (Linux OS) performs instant validation. The system retrieves the permissible weight range from the local database based on QR specifications and compares it with the actual measured weight. Within milliseconds, the system determines whether the box passes or fails.
A Node.js backend running on a Raspberry Pi (Linux OS) performs instant validation. The system retrieves the permissible weight range from the local database based on QR specifications and compares it with the actual measured weight. Within milliseconds, the system determines whether the box passes or fails.
Automated Machine Control & Rejection Logic
To prevent incorrect boxes from progressing further, Aceomation integrated machine-level control directly into the production line. If a box fails validation, the custom hardware sends a control voltage signal to the PLC, which immediately activates the rejector mechanism and physically ejects the box from the conveyor line. If the box passes validation, no rejection signal is triggered, and the box proceeds to the printing and final packing stage.
Automated Print ID Generation
For every validated (passed) box, the system automatically generates a unique print ID, such as A0000001. The print data is transmitted directly to the printer via USB, ensuring proper labeling before final packaging. Failed boxes are rejected automatically and do not receive a print ID.
Data Storage & Digital Traceability
All validation records—both passed and failed—are securely stored in a local SQLite database. Each record includes QR data, actual weight, pass/fail status, print ID (for passed boxes), and timestamp. This enables complete traceability, audit readiness, and production analytics without cloud dependency.
Operator Dashboard & Control
Aceomation developed a React.js-based web application hosted directly on the Raspberry Pi. Operators can monitor real-time pass/fail results, view live weight data, update QR specifications, and access historical validation records. Backend services built with Node.js handle QR ingestion, weight data processing, validation logic, and database storage. The system runs continuously using PM2 to ensure 24/7 operational reliability in factory environments.
Custom Industrial Hardware
Aceomation engineered specialized hardware components to ensure stable and accurate data communication on the shop floor. This included weight calibration interface modules, USB communication systems, and industrial-grade signal handling circuits designed for harsh factory conditions. This hardware integration ensured precise data capture, stable system communication, and long-term operational reliability.
Results
- Zero manual validation errors
- Fully automated pass/fail decisions
- Real-time machine-level rejection control
- Complete digital traceability
- Reliable 24/7 edge-based operation
Conclusion
With a single intelligent edge system, Aceomation transformed a manual validation process into a fully automated, high-precision industrial workflow. By combining custom hardware, edge computing, and real-time automation, the manufacturer achieved accurate weight validation, operational efficiency, and zero dispatch errors. One system. One decision. Zero errors.
