What are the different key layers of IoT architecture? part 2

This second part of the FAQ discusses the three upper layers of the IoT architecture, which extend beyond the physical and network layers. The middleware layer processes and manages raw IoT data from connected devices. The application layer provides user interfaces and visualization tools. The business layer converts technical capabilities into actionable business outcomes.

Part 1 covered the five-layer IoT architecture and explained why it is a commonly used framework. This first part focuses on the first two layers.

What is the middleware layer in IoT architecture, and what does it do?

The middleware layer sits between the network and application layers in IoT systems. It is the central system that takes raw data from connected devices through the network layer. This layer then handles, processes, analyzes, and stores this data before sending it to the application layer in a usable format.

Figure 1 shows a visual representation of the IoT middleware layer. Positioned in the center of the architecture, it connects the device layer on the left with user access on the right.

The middleware layer contains several key functional components represented as blue boxes, including data management, security and privacy, fault tolerance, context awareness, availability, and scalability. These components work together as a “Cluster of Microservices” with Inter-Service Communication connecting them.

Figure 1. Cross-section of IoT system architecture with focus on middleware services. (Image: SpringerLink)

The gateway manager collects data and commands from sensors and actuators and passes this information to the middleware layer for processing. After processing, the middleware layer provides service interfaces that client applications can access through service calls, receiving results back.

The layer typically operates in cloud data centers but can also utilize edge computing. It manages several key tasks: storing large amounts of different data types from IoT devices, cleaning and standardizing this data, analyzing it using methods like machine learning, managing the complete lifecycle of connected devices, and watching data streams to trigger actions based on specific conditions.

Without this layer, the raw data from IoT devices would be too messy and overwhelming to be useful for applications and users. It turns scattered bits of information into organized insights that power smart decisions.

What are the main technologies used in the middleware layer?

The following are the key components and technologies used:

IoT platforms: Cloud-based service packages from major providers (like AWS IoT Core, Microsoft Azure IoT Hub, Google Cloud IoT Platform) that include many middleware functions such as device connection, messaging, data processing, storage, analysis, and device management.
Databases: different database types are used based on data needs. Options include SQL databases, NoSQL databases (such as MongoDB or Cassandra), and Time-Series Databases (like InfluxDB or TimescaleDB), which are designed for handling time-stamped sensor data. Data Lakes (using Hadoop HDFS or cloud storage like Amazon S3) often store raw, unstructured data.
Analysis tools: include big data processing systems (like Apache Spark, Apache Hadoop), machine learning platforms (such as TensorFlow, PyTorch, Azure ML, AWS SageMaker), and stream processing systems for real-time analysis of continuous data (like Apache Flink, Apache Kafka Streams, Azure Stream Analytics, Google Cloud Dataflow, AWS Kinesis).
Device management systems: Special software or services focused on managing devices throughout their lifecycle. These are often part of larger IoT platforms.
APIs provide clear interfaces that allow the application layer to safely access processed data, check system status, and send commands to devices.

What is the function of the application layer, and what are its responsibilities?

The application layer connects the IoT system directly with end-users. Users may be individuals working with software or other systems that utilize IoT data. This layer presents processed data and insights from lower layers to deliver services tailored to each IoT use case, such as smart home control, industrial monitoring, health tracking, or fleet management.

This layer presents information. It provides simple interfaces for users to monitor and control connected devices. It also integrates IoT system capabilities into specific applications or workflows.

Figure 2. Architectural breakdown of application layer showing protocol support for binary, JSON, and GBP. (Image: ResearchGate)

Figure 2 shows the application layer structure, with services positioned at the top. Below are the IoT applications and device management. The layer utilizes data formats (Binary, JSON, and GBP) and REST APIs to interface with the middleware layer. This shows how the application layer sits at the top of the IoT stack, linking users to the system.

What are the key components of the application layer?

The following are the key components of the application layer:

Web applications/Portals: browser-based interfaces showing dashboards, reports, and control features. Business and industrial settings often use these.
Mobile applications: apps for smartphones and tablets offering remote monitoring and control. These benefits are for both consumers and field staff.
Dashboards: visual displays that show KPIs, real-time data, alerts, and system status summaries in a clear and readable format.
APIs: connections that allow the application layer or middleware layer to work with other business software, external services, or custom applications. This expands the use of IoT data and functions.
Analytics and visualization tools: software elements that create charts, graphs, reports, and visuals. These help users understand patterns and insights from IoT data.

How did the business layer find its relevance to IoT implementation success?

When discussing IoT architecture, many focus on sensors and networks, but overlook the need for a structured approach to convert data into actionable business results. The business layer fills this gap by managing how IoT insights are transformed into actual business value.

The business layer handles the business logic that controls the IoT system. It:

Monitors system performance against business goals.
Integrates IoT data into existing workflows.
Supports planning and decision-making.
Manages IoT-enabled business models.
Oversees data governance and privacy rules.

This layer acts as the brain, making sense of all the information from IoT devices and informing the business on how to utilize it.

Figure 3 illustrates the layered architecture approach, which is similar to what is commonly seen in IoT systems. Notice how the business layer is strategically positioned, connecting business logic with data sources and external systems. While this illustrates a web application context, the principles also apply to IoT architectures, where the business layer bridges technical capabilities and business functions.

Figure 3. Visualization of a multi-tier web architecture with client-side, business layer, and data layer components. (Image: Peerbits)

The flow demonstrates how data moves from user interactions through security layers (firewall, proxy), into service layers, ultimately connecting with business logic components. The connections between business logic and enterprise information systems highlight the integration capabilities discussed for linking IoT systems with core business applications.

What tools make up the business layer?

The business layer consists of four main components that work together:

Business intelligence tools, such as Tableau, Power BI, and Qlik, transform IoT data into reports and dashboards for business users.
Enterprise system integration — connectors that link IoT systems with core business applications like ERP, CRM, supply chain management, and manufacturing systems.
Business process management Software: tools that help model and improve business processes that use IoT data.
Decision support systems — applications that help managers make better strategic choices by analyzing complex IoT datasets.

These tools work together to make IoT investment pay off in real business results.

Summary

The middleware, application, and business layers collaborate in an IoT architecture, each handling specific functions in data processing and system operations. Middleware transforms raw device data into structured information, while the application layer creates interfaces for users to interact with IoT systems.

The business layer connects technical capabilities with organizational goals, ensuring IoT implementations provide measurable value through enterprise system integration and decision-support tools. This structured approach enables organizations to utilize IoT data for practical business applications.