The Challenge of IoT Integration
Implementing IoT solutions in industrial environments presents complex technical challenges: heterogeneous devices communicating through different protocols, the need to integrate legacy systems with modern cloud platforms, and the demand for rapidly developing intuitive user interfaces for non-technical operators. In this context, the ability to quickly prototype and orchestrate complex data flows becomes a key competitive advantage.
AIknow has developed specific expertise in using tools that address these challenges with agile approaches, significantly reducing development time and implementation costs for clients. Our experience has enabled us to develop consolidated methodologies for assessing when and how to use visual orchestration solutions in complex industrial contexts.
Node-RED: Visual Orchestration for IoT
Node-RED is a flow-based development environment that allows you to connect hardware devices, APIs, and online services in innovative ways. Its strength lies in the ability to transform complex logic into intuitive graphical representations, accelerating both development and solution maintenance.
In the projects developed by AIknow, when technical analysis suggests it as the optimal approach, Node-RED is evaluated as a potential central orchestration layer, capable of simultaneously managing data collection from industrial sensors, real-time information processing, and distribution to operational dashboards and cloud systems. This architectural choice enables the creation of complete IoT solutions while drastically reducing traditional code complexity and improving long-term maintainability.
AIknow’s key competence lies in the ability to recognize when Node-RED is the most appropriate technological choice compared to alternative approaches, considering factors such as project complexity, maintenance team skills, and specific performance requirements.
Universal Connectivity: HTTP, MQTT, and WebSocket
One of Node-RED’s most relevant features is its native ability to handle major IoT communication protocols without the need for complex external libraries. Immediate support for HTTP REST APIs, MQTT pub/sub, and WebSocket enables fast and reliable integrations.
In a recent industrial monitoring project developed by AIknow, we implemented a system that collects data from PLCs via Modbus protocols, standardizes it through Node-RED flows, and sends it to cloud platforms via MQTT/SPARKPLUG, storing it in timeseries databases (such as TigerData / InfluxDB). Connection error handling and retry mechanisms were implemented graphically, making the resilience logic immediately understandable and editable by the client’s team.
Integration with external web services via HTTP is just as straightforward: REST calls for notification services, email sending, or synchronization with enterprise ERPs require only simple configuration of dedicated nodes. AIknow’s expertise allows for optimizing these integrations by considering critical aspects such as authentication management, rate limiting, and automatic failovers.
Extension Ecosystem: Beyond Basic Functionality
The Node-RED marketplace offers over 4,000 additional nodes that extend the system’s basic functionality. This richness allows for the rapid integration of specific technologies without custom development, but requires expertise in selecting and evaluating the available options.
AIknow has developed a methodical approach to strategically leverage this ecosystem in client solutions. For projects requiring image processing from industrial cameras, we assess and integrate specialized nodes for OpenCV. For integration with specific databases such as InfluxDB, MongoDB, or proprietary systems, we select optimized nodes that automatically manage connection pooling and batch operations.
Our distinctive competence lies in the ability to critically evaluate available nodes: we analyze code maturity, update frequency, compatibility with future versions, performance under high load scenarios, and community support. This expertise ensures clients make solid and sustainable technology choices over time, avoiding dependencies on poorly maintained components or those incompatible with future system evolutions.
Intelligent State Management: Flow and Project Scope
Node-RED implements a sophisticated variable management system that allows information to be shared across different flows while maintaining isolation when needed. Flow-scoped variables are accessible to all nodes within the same flow, whereas project-scoped variables are shared across multiple flows within the project.
This architecture is particularly strategic in the industrial projects developed by AIknow, where configuration information (machine parameters, alarm thresholds, access credentials) must be shared across the data acquisition, processing, and presentation flows. We have developed standardized patterns for state management that ensure data consistency and facilitate debugging and maintenance by client teams.
An example of our methodology: in a production monitoring system, work shift information is loaded at startup into project-scoped variables and used by various flows to calculate specific KPIs, generate automatic reports, and customize operational dashboards based on the current shift. This architecture enables centralized configuration changes with automatic propagation to all dependent components.
Architecture and Governance: Avoiding the “Kraken”
The main risk when using Node-RED lies in the temptation to create overly complex and interconnected flows. Without strict architectural discipline, there’s a danger of creating a “kraken” of nodes and links that quickly becomes unmanageable and costly to maintain.
AIknow has developed specific methodologies, consolidated through years of experience, to prevent this critical drift:
Modularity by Function: Flows are organized by specific responsibilities (acquisition, processing, presentation) with strictly defined interfaces between modules. This separation facilitates testing, debugging, and selective maintenance.
Message Standardization: We define common schemas for the payloads of messages that pass between nodes, facilitating debugging and allowing component reuse across different projects.
Systematic Testing: We use specialized nodes to implement automated tests that verify the behavior of critical flows, integrating these tests into deployment processes and quality assurance procedures.
Integrated Technical Documentation: Each flow includes structured comment nodes that explain the implemented logic, external dependencies, and required configurations, creating always up-to-date documentation directly accessible within the development environment.
Version Control and Governance: Projects are managed using version control systems, enabling controlled rollbacks, collaborative development, and complete audit trails of implemented changes.
This methodological discipline is a distinguishing element of the AIknow approach, ensuring that solutions remain maintainable and scalable even after years of evolution.
Security and Deployment in Production Environments
Implementing Node-RED in production environments requires special attention to security and operational robustness. AIknow has developed specific expertise for enterprise-grade deployments, including multi-level authentication, encrypted communications, and strict instance isolation.
For enterprise projects, we implement architectures based on Docker containerization with dedicated orchestrators, allowing horizontal scalability, automatic resilience, and simplified application lifecycle management. Sensitive configurations (database credentials, SSL certificates, API keys) are managed through dedicated secrets management, never embedded in development flows.
Our experience includes implementing multi-stage environments (development, testing, production) with automated deployment pipelines that ensure consistency and reduce the risk of operational errors during production releases.
Dashboard and User Interface Development
Node-RED includes a powerful dashboard system that allows the creation of responsive web interfaces without specific frontend skills. This capability is particularly strategic for providing industrial operators with immediate monitoring and control tools, significantly reducing the cost and time required for user interface development.
AIknow systematically leverages this functionality to develop operational dashboards that display real-time plant status, enable the configuration of production parameters, and show historical trends through interactive charts. The integration is completely native: data flowing through Node-RED feeds the visual components automatically, with no need for separate frontend development or complex synchronization.
Our specific expertise includes designing user-friendly interfaces for non-technical operators, implementing established usability patterns, and customizing the user experience based on the client’s specific operational workflows. A significant use case involved the creation of a production line control system where operators can monitor overall efficiency, receive predictive maintenance alerts, and modify operational parameters through intuitive interfaces developed entirely in Node-RED.
Case Study: Complete Integration of a Production Plant
A recent project developed by AIknow perfectly illustrates the potential of our methodological approach with Node-RED. A manufacturing company needed to integrate various types of machines exposing different data through heterogeneous protocols, collect real-time production information, and synchronize it with the company’s management system.
Architecture Implemented by AIknow:
- Data collection through direct connections to the machines’ proprietary databases
- Automatic reading of CSV and TXT files generated by control systems
- Acquisition and processing of images from industrial vision systems
- Standardization of data formats and real-time calculation of production KPIs
- Local storage on PostgreSQL database to ensure offline resilience
- Synchronization to a custom-developed cloud system for advanced analytics
- Custom operational dashboards for production supervisors
- Structured REST APIs for integration with the existing SAP ERP
Results Achieved Through AIknow’s Approach:
- 50% reduction in development time compared to traditional approaches
- Extremely easy extension of data reading logic for newly introduced entities
- Ability to connect new machines with minimal effort thanks to the modular architecture
- Complete elimination of manual data collection, reducing operational errors
The architectural flexibility of the Node-RED implementation enabled extremely fast iterations during the development phase, adapting the solution to specific operational needs that emerged during pilot tests. Particularly significant was the system’s ability to easily extend to include new types of machines and data flows without impacting existing components.
Conclusion: When and How to Choose Node-RED
AIknow’s proven experience shows that Node-RED is an optimal choice for IoT projects characterized by:
- Rapid Prototyping: The need to quickly demonstrate the feasibility of complex integrations and gather immediate operational feedback
- Heterogeneous Integration: Connecting devices and legacy systems using completely different protocols and interfaces
- Operational Flexibility: Requirements that may significantly evolve during the development or operation of the solution
- Maintainability: Enabling client teams to understand, modify, and extend the implemented logic autonomously
However, our expertise also includes the ability to recognize when Node-RED is not the optimal choice. For applications with extreme performance requirements, particularly complex algorithmic logic, or the need for granular memory management, we evaluate and propose more appropriate architectural approaches.
AIknow’s distinctive competence lies in the ability to accurately assess when Node-RED is the optimal technological choice for the client’s specific context, and how to implement it to maximize benefits while minimizing architectural risks. Our proven methodology and deep knowledge of the ecosystem allow clients to fully leverage the potential of this tool, achieving robust, scalable, and easily maintainable IoT solutions over time.
The difference between a successful Node-RED implementation and an unmanageable “kraken” lies entirely in architectural expertise and the methodological discipline applied during development. AIknow ensures this competence through years of consolidated experience and a systematic approach to the design and implementation of industrial IoT solutions.
Big News Coming Soon
AIknow is currently working on a very special initiative in the Node-RED world: an innovative solution that will dramatically lower the barriers to IoT adoption and significantly accelerate the development time of industrial applications. This initiative stems from a collaboration with a major hardware manufacturer preparing to launch a cutting-edge technology to the market, making IoT solutions even more accessible and enabling companies to implement complete projects in record time. Don’t miss our upcoming updates — the announcement is imminent…
To learn how AIknow can support your next IoT project with Node-RED or help you evaluate the most suitable technological approach for your specific needs, contact us for a preliminary consultation. Our expertise will help you unlock the full value of visual orchestration technologies, avoiding typical architectural pitfalls and delivering robust, scalable solutions.
