#arm edge controller

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ARM Edge Controller and ThingsBoard Edge: Building an Intelligent Production Equipment Status Monitoring System

In the wave of industrial digital transformation, real-time monitoring and intelligent management of production equipment have become key drivers for enterprises to enhance efficiency and reduce costs. While traditional cloud-based monitoring offers robust functionality, it faces limitations in real-time performance, reliability, and bandwidth consumption. With the rise of edge computing, the integration of ARM edge controllers and ThingsBoard Edge provides an efficient, flexible, and highly scalable solution for production equipment status monitoring. This approach shifts computational resources to the edge, enabling local intelligent processing alongside cloud collaboration, and empowers businesses to build a resilient industrial IoT ecosystem.

Architecture Design

The solution employs a dual-layer architecture of "edge controller + edge IoT platform" to ensure seamless data acquisition, processing, and management:

ARM Edge Controller BL370 Series

Deployed on-site in production environments, it directly collects equipment runtime data (e.g., temperature, current, vibration, RPM).

Supports multiple industrial protocols (Modbus, OPC UA, MQTT, CAN, etc.), enabling seamless integration with diverse devices.

Features built-in local computing capabilities for data preprocessing, anomaly detection, and filtering, significantly reducing the upload of redundant data and improving transmission efficiency.

ThingsBoard Edge

Deployed on the edge controller or local servers as an on-site IoT platform.

Provides device management, telemetry data collection, rule engines, and local visualization features, including real-time dashboards and report generation.

Synchronizes data with the cloud-based ThingsBoard Server, supporting centralized cross-factory management and advanced big data analytics.

Application Scenarios

Real-Time Status Monitoring: Equipment operational status can be viewed locally in the workshop, ensuring full transparency in the production process.

Anomaly Alerts: The edge rule engine instantly detects deviations (e.g., overheating or abnormal vibration) and triggers local or cloud-based notifications.

Data Buffering and Resumable Uploads: During network disruptions, the edge node automatically caches data, resuming seamless synchronization to the cloud upon recovery to maintain data integrity and continuity.

Layered Management: On-site ThingsBoard Edge handles device connectivity and initial processing, while the cloud platform focuses on cross-factory data aggregation, analysis, and reporting.

Advantages Analysis

Low-Latency Response: Local processing and alerting mechanisms meet the high real-time demands of industrial scenarios, achieving millisecond-level responses.

High Reliability: Even if cloud services are unavailable, the edge layer operates independently, ensuring uninterrupted monitoring and alerts.

Flexible Scalability: ARM controllers allow dynamic interface configuration based on device types; ThingsBoard Edge supports modular rule and visualization extensions, adapting to evolving production environments.

Cost Optimization: Dramatically reduces cloud computing loads and storage needs, minimizing bandwidth usage for more economical digital deployments.

Future Outlook

As demands for on-site intelligence continue to grow in industrial settings, the fusion of ARM edge controllers and ThingsBoard Edge will expand its application boundaries:

Predictive Maintenance: Integrating edge AI models for real-time data analysis to forecast potential failures in advance, extending equipment lifespan.

Energy Optimization: Monitoring equipment energy patterns and leveraging cloud algorithms to implement energy-saving strategies, advancing green manufacturing.

Cross-Industry Expansion: Beyond manufacturing, it extends to sectors like energy, power, and transportation, fostering universal innovation in the Industrial IoT.

Conclusion

The collaborative architecture of ARM edge controllers and ThingsBoard Edge infuses production equipment status monitoring with a potent blend of real-time capability, reliability, and scalability. It not only elevates the intelligence of production sites but also lays a solid foundation for enterprise digital transformation. Looking ahead, this solution will thrive across more industries, propelling the Industrial IoT toward an era of greater intelligence and autonomy.

ARM Edge Controller and ThingsBoard Edge: Production Monitoring System

The collaborative architecture of ARM edge controllers and ThingsBoard Edge infuses production equipment status monitoring with a potent ble

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ARM Edge Controllers in Three-Color Light Monitoring for CNC Machining Production Lines

In the wave of intelligent manufacturing, CNC machining production lines are progressively advancing toward digitalization and visualization management. The three-color light, as a traditional tool for indicating equipment status, is simple yet essential. By introducing ARM architecture-based edge controllers, three-color light signals can be transformed into collectible, analyzable, and remotely manageable data resources, thereby building an efficient and intelligent production line monitoring system.

Application Background and Challenges

CNC machining equipment is typically equipped with three-color lights to indicate running (green), standby (yellow), and fault (red) states. However, traditional three-color lights only provide local visual prompts and cannot achieve remote monitoring, data statistics, or intelligent responses, which hinders the transparency and automation level of production lines.

Key challenges include:

Inability to remotely acquire equipment status;

Inability to store and analyze status data;

Delayed fault responses, impacting production line efficiency.

Solution Architecture

The ARM edge controller BL335 Series serves as a bridge connecting physical devices and digital systems, offering advantages such as low power consumption, high performance, rich interfaces, and robust protocol support. Its core roles in the three-color light monitoring solution are as follows:

Signal Acquisition

Collect three-color light status signals via GPIO, RS485, IO modules, and other methods;

Support industrial-grade acquisition methods such as level triggering and photoelectric isolation.

Edge Processing

The controller runs embedded Linux or RTOS with built-in status recognition logic;

Enable local status display (e.g., via LCD, LED, or Web HMI);

Implement status change logging, anomaly detection, and local alarms.

Data Upload and Integration

Support protocols such as MQTT, Modbus, and OPC UA;

Integrate with CNC control systems, MES, and SCADA platforms;

Enable remote equipment status monitoring, statistical analysis, and fault tracing.

Typical Application Scenarios

The three-color light status controller can respond to backend processing based on different signals:

Green (Running): Record running time to update utilization rates and production statistics;

Yellow (Standby): Track idle duration to analyze bottlenecks and optimize scheduling;

Red (Fault): Trigger local buzzers and remote alarms to notify maintenance personnel and generate fault reports.

Additionally, the controller can be extended to collect data on temperature, vibration, current, and more, enabling multi-dimensional status monitoring and predictive maintenance.

Solution Advantages

Strong Real-Time Performance: Edge processing avoids cloud latency, achieving second-level responses to equipment status changes;

Flexible Deployment: Supports DIN rail mounting, PoE power supply, wireless communication, and other methods;

High Compatibility: Adapts to various CNC brands and three-color light models;

Robust Visualization: Supports Qt graphical interfaces, Web Dashboards, and mobile viewing.

Conclusion

ARM edge controllers empower three-color light monitoring, not only enhancing the visualization and responsiveness of CNC machining production lines but also laying a solid data foundation for intelligent manufacturing. In the future, this solution can further integrate AI analysis and industrial vision to achieve higher levels of production line intelligence.

ARM Edge Controllers in CNC Machining Production Lines

ARM edge controllers empower three-color light monitoring, not only enhancing the visualization and responsiveness of CNC machining producti

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ARM Edge Controller in Distribution Automation System (DAS)

In modern smart grids, the Distribution Automation System (DAS) serves as a critical component for ensuring power supply reliability and energy quality. With the increasing complexity of distribution networks and the growing integration of distributed energy resources, traditional centralized control architectures fall short in meeting real-time response and self-healing requirements. The ARM edge controller emerges as an efficient, autonomous solution, significantly enhancing the intelligence of the system.

System Architecture and Functions

The ARM edge controller BL370 Series is deployed at key nodes in the distribution network (such as switching stations, ring main units, and sectionalizers), handling on-site monitoring, control, and communication. Leveraging integrated local AI and edge computing capabilities, the controller independently manages data acquisition, event analysis, and action execution, enabling rapid responses without reliance on the central master station.

Key functions include:

Equipment Monitoring: Real-time collection of critical parameters such as current, voltage, temperature, and position status from distribution switches, ring main units, sectionalizers, and other devices, ensuring transparent operational visibility.

Fault Detection and Localization: AI algorithms identify anomalies like short circuits, ground faults, and overloads, while precisely locating the faulty section to improve diagnostic efficiency.

Automatic Isolation and Power Restoration: Upon fault detection, the controller swiftly actuates sectionalizing switches for isolation and dynamically reconfigures power paths, achieving system self-healing.

Communication and Remote Management: Supports protocols including IEC 60870-5-104, Modbus, and MQTT for seamless integration with dispatch master stations and cloud platforms.

Data Analysis and Edge Intelligence: Local storage of historical data with operational trend analysis, providing intelligent decision support for maintenance.

Technical Advantages

High-Performance, Low-Power ARM Architecture: Suitable for long-term stable operation in outdoor power environments, reducing energy consumption and enhancing reliability.

Edge AI for Rapid Response: Enables millisecond-level fault detection and control actions, surpassing traditional system speeds.

Modular I/O Design: Flexibly accommodates various power equipment and sensors for easy on-site expansion and customization.

Multi-Protocol Interoperability: Compliant with industry-standard communication protocols, facilitating high-compatibility system integration.

Local Autonomy with Cloud Collaboration: Operates independently during communication outages to ensure power continuity, while supporting cloud-based data sharing.

Typical Application Scenarios

Urban Ring Main Unit Automation and Self-Healing System: Real-time monitoring and rapid fault recovery for urban distribution networks, enhancing power resilience.

Industrial Park Distribution Monitoring and Zonal Management: Fine-grained zonal control to optimize industrial load distribution and minimize outage impacts.

Rural Distribution Line Intelligent Switch Control: Ideal for remote areas, enabling remote smart operations and reducing maintenance costs.

Intelligent Reconstruction of Distribution Networks with Distributed Power Integration: Dynamically adapts to renewable sources like photovoltaics and wind power, enabling grid reconfiguration and balance.

Conclusion

The deployment of ARM edge controllers propels DAS from manual monitoring to intelligent autonomy, dramatically improving power supply reliability and response speed. This provides a robust foundation for smart power systems and the energy Internet of Things.

ARM Edge Controller in Distribution Automation System (DAS)

ARM Edge controllers propels DAS from manual monitoring to intelligent autonomy, dramatically improving power supply reliability and respons

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ARM-Based Edge Controller for Injection Molding Machines

Case Details

Injection molding machines play a pivotal role in manufacturing plastic components for diverse industries, including automotive parts, home appliances, consumer electronics, and medical devices. Conventional control systems, typically based on Programmable Logic Controllers (PLCs) or proprietary hardware, often struggle with limitations in energy efficiency, precision control, and seamless integration with contemporary manufacturing ecosystems.

In the era of smart manufacturing and Industrial Internet of Things (IIoT), integrating an ARM-based edge controller into injection molding machines addresses these challenges. This solution enables real-time monitoring, intelligent automation, and robust connectivity to cloud platforms, paving the way for enhanced operational excellence.

Functions of the ARM Edge Controller BL370 Series

The ARM edge controller serves as a versatile, high-performance hub that elevates machine capabilities through advanced data handling and automation. Below are its core functions:

Real-Time Data Acquisition

Captures critical operational parameters, including barrel temperature, mold temperature, injection pressure, screw rotation speed, clamping force, and energy consumption.

Interfaces with diverse hardware via analog inputs, RS485/Modbus protocols, CANopen, and digital I/O for comprehensive sensor integration.

Intelligent Process Control

Employs PID (Proportional-Integral-Derivative) algorithms for precise barrel heating and cooling management.

Dynamically optimizes injection speed profiles, holding pressure, and cycle times to ensure consistent output.

Leverages predictive algorithms to minimize defects, enhance product uniformity, and adapt to varying production demands.

Connectivity and Remote Monitoring

Facilitates seamless data transmission over Ethernet, Wi-Fi, or 4G networks to Manufacturing Execution Systems (MES), Supervisory Control and Data Acquisition (SCADA), or cloud platforms.

Supports remote diagnostics, instant alarm notifications, and on-the-fly parameter adjustments.

Provides intuitive data visualization dashboards to track Overall Equipment Effectiveness (OEE) and enable predictive maintenance scheduling.

Energy Efficiency

Monitors motor and hydraulic pump power usage in real time for proactive optimization.

Utilizes edge AI algorithms to fine-tune machine performance dynamically, reducing waste and improving sustainability.

Integrates effortlessly with servo drives and Variable Frequency Drives (VFDs) to achieve significant energy savings without compromising productivity.

Value and Benefits

✅ Improved Product Quality and Precision: Enhanced control algorithms ensure tighter tolerances and fewer rejects, leading to superior end-products.

✅ Reduced Energy Consumption and Operational Costs: Intelligent optimization cuts power usage by up to 20-30% (depending on application), lowering utility bills and environmental impact.

✅ Smart Factory Integration and Digital Transformation: Enables IIoT connectivity for end-to-end visibility, fostering agile and data-driven decision-making.

✅ Extended Equipment Lifecycle with Predictive Maintenance: Early detection of anomalies prevents breakdowns, extending machine uptime and reducing downtime-related losses.

Summary

In summary, the ARM-based edge controller revolutionizes injection molding by bridging the gap between traditional machinery and modern smart manufacturing paradigms. By enabling real-time data acquisition, intelligent control, robust connectivity, and energy-efficient operations, it not only boosts productivity and product quality but also drives cost savings and sustainability. Manufacturers embracing this technology can achieve a competitive edge through digital transformation, ultimately turning conventional injection molding machines into agile, connected assets that support long-term innovation and efficiency in high-volume production environments.

ARM-Based Edge Controller for Injection Molding Machines

ARM-based Edge controllers can improve productivity and product quality while also advancing the injection molding process by enabling real-

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ARM Edge Logic Controller in Multi-Effect Distillation (MED) Systems

Case Details

Seawater desalination is a critical solution to global water scarcity. Multi-Effect Distillation (MED) is widely used in coastal areas and islands for its high energy efficiency and operational stability. The MED system involves components such as evaporators, condensers, heaters, vacuum pumps, and circulation pumps, requiring precise control and real-time data acquisition to ensure efficiency and water quality.

Role of ARM Edge Logic Controller BL350 Series

The ARM edge logic controller serves as the core control unit of the MED system, integrating real-time data acquisition, edge computing, and remote monitoring to meet the demands of complex operational environments.

Data Acquisition and Monitoring

Temperature: Monitors temperatures in evaporators, condensers, and inlet/outlet pipelines.

Pressure/Vacuum: Tracks pressure conditions in evaporation and condensation chambers.

Flow: Measures circulation pump and product water flow rates.

Conductivity/TDS: Ensures product water quality through real-time monitoring.

Logic Control

Steam Flow Regulation: Automatically adjusts heating steam flow to optimize temperature gradients in evaporators.

Vacuum Pump Control: Maintains a low-pressure evaporation environment for enhanced efficiency.

Pump Logic Switching: Intelligently switches between circulation and feedwater pumps to prevent dry running.

Energy Efficiency Optimization

Utilizes edge computing to analyze thermal energy efficiency and dynamically adjust operating conditions.

Reduces steam and electricity consumption, improving overall system efficiency.

Safety and Alerts

Issues alerts for overtemperature, overpressure, or pump anomalies.

Employs local redundant logic during network disconnections to ensure safe operation.

Remote Operation and Maintenance

Supports 4G/Ethernet connectivity to SCADA systems or cloud platforms.

Provides VPN and secure encrypted channels for remote maintenance and parameter optimization.

Application Value

Enhanced System Stability: Ensures continuous and stable operation of the MED process.

Reduced Maintenance Costs: Remote operation minimizes the need for on-site personnel.

Improved Energy Efficiency: Edge computing optimizes thermal energy utilization, reducing energy consumption.

Assured Water Quality: Real-time conductivity/TDS monitoring guarantees high-quality freshwater output.

Summary

The ARM edge logic controller significantly enhances the efficiency and stability of MED systems through integrated data acquisition, logic control, energy optimization, and remote maintenance. Its edge computing capabilities reduce energy consumption, remote monitoring lowers operational costs, and real-time water quality monitoring ensures safe freshwater output, providing an efficient and reliable solution for seawater desalination.

ARM Edge Logic Controller in Multi-Effect Distillation (MED) Systems

Real-time water quality monitoring using an ARM edge logic controller ensures safe freshwater output, providing an efficient and reliable so

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Cortex-A55 ARM Edge Controllers for Hydroponic Farming Monitoring

Case Details

Hydroponic agriculture uses nutrient solutions instead of soil for crop cultivation, enabling high yield, water efficiency, and controlled production. With the development of smart agriculture, real-time monitoring and precise management of hydroponic systems have become increasingly important. This article introduces the use of ARM Edge Controllers as the core platform for hydroponic system monitoring and control, enabling environmental data acquisition, intelligent control, and remote management to ensure healthy crop growth and improve production efficiency.

Background and Application Value

Traditional hydroponic agriculture mainly relies on manual inspection and adjustment of nutrient solutions and environmental parameters, which faces several challenges:

Large fluctuations in environmental parameters can affect crop growth;

Manual inspection is labor-intensive and inefficient;

Data is not recorded, making traceability and optimization difficult.

Using ARM Edge Controllers BL410 allows for:

Real-time monitoring of pH, EC, dissolved oxygen (DO), temperature, humidity, light intensity, etc.;

Automatic control of circulation pumps, fertilization pumps, aerators, LED lighting, and climate control devices;

Edge computing for fast data processing and local intelligent decision-making;

Remote management with cloud monitoring, alert notifications, and historical data analysis.

System Architecture

Sensor Layer: Environmental and water quality sensors (pH, EC, DO, temperature, humidity, PAR light, water level), on-site cameras.

Actuator Layer: Circulation pumps, aerators, fertilization pumps, solenoid valves, LED grow lights, fans, heating/cooling units.

Edge Control Layer: ARM Edge Controller as the core, responsible for data acquisition, real-time control, anomaly detection, and local alarms.

Communication Layer: Field buses (Modbus, RS485/RS232), Ethernet or wireless network to upload data to the cloud platform.

Cloud Platform & Operations Terminal: Remote monitoring, data analytics, alerts, and operational records.

Core Functions and Monitoring Indicators

IndicatorFunctionRecommended SamplingNotespHAcid-base balance control1–5 minOptimal range 5.5–6.5EC / Nutrient solution concentrationMonitor nutrient levels1–10 minAdjust per growth stageDissolved Oxygen (DO)Water oxygenation1–5 minMaintain ≥5 mg/LWater TemperatureRegulate water temperature1 minAffects root absorption efficiencyLight (PAR)Control supplemental lighting5 minAdjust with natural lightWater Level / FlowPump and circulation controlReal-timePrevent pump dry-run or blockage

Control Strategies

pH Regulation: PID-based control of acid/alkali pumps to avoid overshoot and frequent operation.

Nutrient Solution Management: Adjust watering and fertilization based on EC and water level, optimized for crop growth stage.

Oxygen Management: Activate aerators and increase circulation when DO is below threshold.

Light & Temperature: Control LED lighting and climate according to crop growth stage and natural conditions.

Fail-Safe Strategy: In case of communication or cloud downtime, ARM controller executes local safety control.

Edge Computing and Data Processing

Anomaly Detection: Detect sensor drift or environmental fluctuations using historical trends and thresholds.

Image Monitoring: Analyze leaf color, density, and early signs of disease using on-site cameras.

Data Analytics: Calculate daily water and nutrient consumption, energy use, and generate maintenance recommendations.

Alerts and Operations

Tiered Alerts: Info, warning, critical levels sent via SMS, WeChat, or email.

Automated Actions: Exceeding critical thresholds triggers safety operations like backup pump activation or aeration.

Sensor Maintenance: Regular calibration of pH, EC, and DO sensors ensures accuracy.

Remote Operations: Support OTA updates, remote strategy adjustments, and historical data retrieval.

Deployment and Testing

Requirement analysis and scenario planning;

Device selection and wiring;

Sensor calibration and integration;

Simulation and PID tuning;

On-site trial run (7–14 days) to observe data stability;

Acceptance and delivery of operational and maintenance manuals.

Advantages and Prospects

Increased crop yield and consistency;

Reduced labor and resource consumption;

Data traceability supports optimization and predictive modeling;

Expandable to multi-site management for industrial hydroponic agriculture.

Conclusion

ARM Edge Controller, with their low power consumption, industrial reliability, and rich interfaces, are ideal for smart monitoring and control of hydroponic agriculture. Combined with edge intelligence and cloud integration, they enable real-time, automated, and traceable production management, improving efficiency and reducing costs, while laying the foundation for future smart agriculture applications.

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Cleanroom Monitoring Solution Based on ARM Edge Controller

Case Details

Cleanrooms, as highly controlled environments, are widely used in industries such as semiconductor manufacturing, biopharmaceuticals, and medical device production, where stringent requirements for environmental cleanliness and safety are paramount. In particular, real-time, precise data collection and rapid response mechanisms are critical for leak detection and access control in cleanrooms. Traditional centralized monitoring systems often suffer from data transmission delays and insufficient device integration, making them inadequate for meeting the demands of modern cleanrooms for efficient and intelligent management.

With the advancement of Industrial Internet of Things (IIoT) and edge computing technologies, ARM-based edge controllers have emerged as key devices for enhancing environmental safety and intelligent management in cleanrooms.

Solution Architecture

Core Device: ARMxy Edge Computing Controller

The ARMxy series edge controller is equipped with a high-performance ARM processor and versatile interfaces (e.g., Ethernet, RS485/RS232, DI/DO/AIO), supporting multiple industrial communication protocols to accommodate diverse field devices. This controller not only enables local data acquisition and real-time control but also seamlessly integrates with central control systems via network connectivity for remote monitoring and management.

Key Sensor Modules

Liquid Leak Sensors: Real-time detection of liquid leaks on the cleanroom floor or at critical equipment, ensuring environmental safety.

Temperature and Humidity Sensor Modules: Continuous monitoring of cleanroom environmental parameters to ensure compliance with process standards.

Access Control Card Readers: Enable secure and organized personnel access management for cleanroom entry and exit.

Communication Protocols and Data Transmission

Field devices communicate with the ARM edge controller using standard protocols such as Modbus RTU (serial) or Modbus TCP (Ethernet). The controller preprocesses data, performs alarm logic judgments, and transmits the processed data to upper-level central control systems (e.g., SCADA, DCS, or cloud platforms) via the network.

Specific Functions and Advantages

Real-Time Environmental Data Acquisition and Monitoring The ARM edge controller periodically collects data from liquid leak sensors and environmental sensors, displaying real-time environmental conditions. Upon detecting anomalies (e.g., excessive leaks or deviations in temperature/humidity), it immediately triggers local alarms (e.g., audible-visual alarms) and synchronously notifies the central control system for rapid response.

Automated Logic Control The controller features flexible logic programming, allowing automated control strategies to be configured based on site-specific process requirements. For example, in the event of a leak alarm, it can automatically close relevant valves or activate exhaust systems to minimize risks.

Access Control Management Integrated with access control card readers, the controller monitors cleanroom access status in real-time, logs personnel entry/exit records, and supports hierarchical access authorization. Access event data is uploaded to the central system via standard protocols for security auditing and tracking.

Remote Monitoring and Centralized Data Management As an intelligent on-site node, the edge controller aggregates environmental and access data, transmitting it via Ethernet or wireless networks. Combined with upper-level platforms, it enables unified monitoring and historical data analysis, supporting continuous optimization of cleanroom environments.

Application Case Study

In a semiconductor cleanroom project, the ARMxy edge controller was deployed to connect over 20 liquid leak sensors, 10 temperature and humidity modules, and multiple access control card readers. The system successfully achieved real-time multi-point data acquisition, automated alarms, and access control management, significantly enhancing the cleanroom’s safety and operational efficiency.

Conclusion

The cleanroom leak detection and access control solution based on the ARM edge controller, with its high integration, reliability, and scalability, enables intelligent management of cleanrooms, ensuring environmental safety and production continuity. It represents a vital technological approach for modern cleanroom management.

Cleanroom Monitoring Solution Based on ARM Edge Controller

Cleanroom leak detection and access control solutions based on ARM edge controllers can achieve intelligent cleanroom management and ensure

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ARM IIoT Edge controller in Temperature Monitoring of Beverage Factory Cold Storage

Case Details

During beverage production and storage, the stability of cold storage temperature directly impacts product quality and shelf life. To achieve efficient cold storage temperature management, a beverage factory implemented an ARM-based Industrial Internet of Things (IIoT) edge controller for remote temperature monitoring and management.

System Architecture and Functions

The ARM remote controller connects directly with temperature sensors to collect real-time temperature data from multiple cold storage units. Equipped with multi-protocol conversion capabilities, the controller converts analog or digital signals into standard industrial communication protocols (e.g., Modbus, MQTT) and securely transmits the data to the factory’s control center via Ethernet or 4G/WiFi networks.

The system supports parallel monitoring of multiple storage units, with temperature data displayed in real-time on the control center’s monitoring interface. It also allows setting temperature threshold alarms. If an anomaly is detected, the system immediately triggers audible, visual, or SMS alerts to notify on-duty personnel for prompt action.

Application Advantages

Multi-point Collection and Centralized Management: Simultaneously monitors multiple cold storage units, improving management efficiency.

Real-time Transmission and Alerts: Provides second-level data updates and instant notifications for temperature anomalies.

Remote Maintenance: Enables managers to access the system from the office or remotely via the network, reducing inspection frequency and labor costs.

Data Traceability: Supports historical data storage and analysis, facilitating quality tracking and operational optimization.

Conclusion

The adoption of the ARM IIoT Edge controller has significantly enhanced the intelligence and automation of cold storage temperature monitoring in the beverage factory. It ensures stable product quality during storage, delivering substantial economic benefits and management advantages to the enterprise.

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