5 Layer Architecture of IoT

Internet of Things Ecosystem is certainly some times overwhelming to understand due to the fact that it includes different verticals into it and that is when the understanding of the Architecture of IoT really makes the concept lucid.

Here we will try to understand the 5 layered Architecture – one the  popular Architectures of IoT .

The 5 layer architecture model of the Internet of Things (IoT) is an extension and a more detailed version of the 3 Layered Architecture. The 5 layer architecture is considered to be the “The best-proposed Architecture of IoT”. The 5 layers are: 

  1. Perception Layer

  2. Network Layer

  3. Processing Layer

  4. Application Layer

  5. Business Layer

5 Layer Architecture of IoT
  1. Perception Layer: Perception, as the name suggests, means to perceive. Its functions are analogous to the eyes, nose, ears of a human body. So the perception layer is also called the sensor layer.

    A sensor is a device or a module that detects changes in the surroundings and sends the data captured to other electronic devices or a microcomputer or a microcontroller. It converts the physical quantities captured and converts it into analog or digital signals for further processing.

    There are a wide range of sensors available to capture data including location, temperature, orientation, movement, vibration, acceleration, humidity, etc. Some of the most common sensors used in various IoT applications are:
  • Temperature Sensors: We use temperature sensors every day for temperature control in buildings, water temperature regulation, and to control refrigerators. Temperature sensors are also vital in many other applications such as consumer, medical, and industrial electronics. Each application may have a different temperature sensing need.
  • Humidity Sensor: A humidity sensor is also found as part of home heating, ventilating and air conditioning systems (HVAC systems). These are also used in offices, cars, humidors, museums, industrial spaces and greenhouses and are also used in meteorology stations to report and predict the weather.
  • Pressure Sensor: Pressure sensor applications consist of altimeters, barometers, sensing printer ink levels, air flow rate in equipment, IT center/ computer cooling systems, semiconductor process equipment, and laser measurement, as well as clean room monitoring devices.
  • Proximity Sensor: Proximity sensors are used in smartphones to detect if a user is holding their phone near their face. Used on automated production lines for object detection, position, inspection and counting.
  • Level Sensor: Level sensors are used primarily in the manufacturing and automotive industries, but they can be found in many household appliances as well, such as ice makers in refrigerators.
Sensor TypeDIY Sensor ExampleIndustrial Sensor Example
Temperature SensorsLM35 SensorThermo Sensors and RTD
Humidity SensorsDHT11 SensorSilicon Labs- SI7021
Pressure SensorsBMP280 ModulePressure Sensor – Honeywell
Proximity SensorsIR Proximity Sensor 
Level SensorsAllegro- A1356NivoGuide- NG 8100/8200, Float Sensor
Accelerometers

MPU 6050 Module

Silicon Labs- EQ-TR-VBT1A4
GyroscopesMPU 6050 ModuleSTMicroelectronics- I3G4250D
Gas SensorsMQ2 ModuleSiro-CO2 Module
InfraRed SensorsPIR SensorMLX90614 Module

2. Network Layer: As the name suggests, it connects the perception layer and the processing layer. The data which is captured and collected by the sensors from the perception layer are passed to the processing layer using networking technologies like 3G, 4G, UTMS, WiFi, NFC, RFID, infrared, etc. Another name for this layer is the communication layer or transmission layer because it is responsible for communication between perception and the processing layer. All the transfer of data done securely. The connectivity between the physical layer and the cloud is achieved in two ways:

  • Using TCP or UDP/IP stack;
  • Via Gateways — Hardware or Software Modules performing translation between different protocols as well as encryption and decryption of IoT data.

The communications between devices and gateways involve different networking technologies.
For example:

  • Ethernet connects stationary or fixed IoT devices like security and video cameras, permanently installed industrial equipment, etc.
  • WiFi, the most widely used technology of wireless networking, is a great fit for IoT solutions that are easy to recharge and operate within a small area.
  • NFC (Near Field Communication) enables simple and secure data sharing between two NFC-enabled devices over a distance of 10cm or less.
  • Bluetooth is widely used by wearables and fitness devices for short-range communications and in order to meet the needs of low-power IoT devices, the Bluetooth Low-Energy (BLE) standard was designed. It transfers only small portions of data and doesn’t work for large files.
  • LPWAN (Low-power Wide-area Network) was created specifically for IoT devices. It provides long-range wireless connectivity on low power consumption with a battery life of 10+ years. Sending data periodically in small portions, the technology meets the requirements of smart cities, smart buildings, and smart agriculture (field monitoring).
  • ZigBee is a low-power wireless network for carrying small data packages over short distances. The outstanding thing about ZigBee is that it can handle up to 65,000 nodes. Created specifically for home automation, it also works for low-power devices in industrial, scientific, and medical sites.

Once parts of the IoT solution are networked, they still need messaging protocols to share data across devices and with the cloud. The most popular protocols used in the IoT ecosystems are DDS, AMQP, CoAP, MQTT, etc.

  • DDS (the Data Distribution Service) which directly connects IoT things to each other and to applications addressing the requirements of real-time systems;
  • AMQP (the Advanced Message Queuing Protocol) aiming at peer-to-peer data exchange between servers;
  • CoAP (the Constrained Application Protocol), a software protocol designed for constrained devices — end nodes limited in memory and power (for example, wireless sensors). It feels much like HTTP but uses fewer resources;
  • MQTT (the Message Queue Telemetry Transport), a lightweight messaging protocol built on top of TCP/IP stack for centralized data collection from low-powered devices.

3. Processing Layer: The Processing Layer has some advanced features like storage, computation, processing, action taking capabilities, analysis, etc. It stores all the data-sets transferred by the perception layer through the network layer and based on the device address and name it gives appropriate data to that device. It can also take decisions based on the processing and analysis/calculations done on a data-set obtained from sensors.

All these tasks are commonly handled via IoT platforms and include two major stages:

  • Data accumulation stage: The real-time data is captured via an API and put at rest to meet the requirements of non-real-time applications. The data accumulation component stage works as a transit hub between event-based data generation and query-based data consumption. Also, it characterizes whether information is pertinent to the business necessities and where it should be put.
  • Data abstraction stage: Here, data preparation is finalized so that consumer applications can use it to generate insights. The entire process involves the following steps:

a. Combining data from different sources, both IoT and non-IoT devices.

b. Reconciling multiple data formats; and

c. Aggregating data in one place or making it accessible regardless of location through data virtualization.

4. Business Layer: The Business Layer is the place where all the business/domain logic, i.e. rules that are particular to the problem that the application has been built. Business logic is defined as any application logic that is concerned with the retrieval, processing, transformation, and management of application data; application of business rules and policies; and ensuring data consistency and validity.

The information generated at the previous layers brings value if only it results in a problem-solving solution and achieving business goals. New data must initiate collaboration between stakeholders who in turn introduce new processes to enhance productivity

5. Application Layer: An application layer is also known as an Abstraction Layer. It specifies the shared communications protocols and interface methods used by hosts in a communications network. The application layer is what the user interacts with.

It delivers application specific services to the user and defines all applications in which IoT has been deployed. It is the interface between the end IoT devices and the network.
It has the authority to provide services to the applications. The services may be different for each application because of services based on the information collected by sensors. It is applied through a dedicated application at the device end.

Such as for a computer, the application layer is applied by the browser. The application layer in the Internet is typically based on HTTP protocol. However, HTTP is not suitable in a resource constrained environment because it is extremely heavyweight and thus incurs a large parsing overhead. So, there are many alternate protocols that have been developed for IOT environments. Some of the popular IOT application layer protocols are as follows – MQTT, SMQTT, CoAP, DDS, XMPP, AMQP, RESTful HTTP, MQTT-SN, etc.

 

For example: The hospital management system organizes the stable functioning of daily tasks and interactions. This is a special tool to support the smooth operating of the software components that are vital for the clinic administration. The hospital records management software keeps a track of all the operations, stores the users’ data, performs its analysis and generates the reports.

In the manufacturing segment,  the business logic would be around Overall equipment effectiveness(OEE), predictive maintenance (PDM), KPI. A manufacturing KPI or metric is a well-defined measurement to monitor, analyze and optimize production processes regarding their quantity, quality as well as different cost aspects. 

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