Nowadays companies are aggressively incorporating internet of things into their existing IT infrastructures. However, planning to shift to IoT is one thing; an effective implementation is an entirely different ball game. Several considerations are required to develop IoT application. For starters, you need a robust and dependable architecture which can help with the implementation. Organizations have adopted a wide range of architectures along the years but the four layers and seven layer architecture are especially notable. Here is how they work.
Four Layer Architecture
The four-layer architecture is composed of the following four layers.
1. Actuators and Sensors
Sensors and actuators are the components of IoT devices. Sensors collect and gather all the necessary data from an environment or object. It is then processed and becomes meaningful for the IoT ecosystem. Actuators are those components of IoT devices which can modify an object’s physical state. In standard four-layer architecture, data is computed at all the layers including in sensors and actuators. This processing depends upon the processing limits of the IoT equipment.
2. The Internet Gateway
All the data which is collected and stored by sensors fall into the analog data category. Thus, a mechanism is required which can alter it and translate it into the relevant digital format. For this purpose, there are data acquisition systems in the second layer. They connect with the sensor’s network, perform aggregation on the output, and complete the analog-to-digital conversion. Then this result goes to the gateway which is responsible for routing it around Wi-Fi, wired LANs, and the Internet.
For example, suppose there is a pump which is integrated with many sensors and actuators; they send data to an IoT component so it can aggregate it and convert it into digital format. Subsequently, a gateway can process it and perform the routing for the next layers.
Preprocessing plays an important role in this stage. The sensor data produce voluminous amounts of data within no time. This data includes vibration, motion, voltage, and similar real-world physical values to create datasets with ever-changing data.
3. Edge IoT
After the conversion of data into a digital format, it cannot be passed onto data centers before you can perform additional computation on it. At this phase, edge IT systems are used for the execution of the additional analysis. Usually, remote locations are selected to install them—mostly those areas which are the closest to the sensors.
Data in IoT systems require heavy consumption of resources such as the network bandwidth in the data centers. Hence, edge systems are utilized for analytics which decreases the reliance on computing resources. Visualization tools are often used in this phase to monitor data with graphs, maps, and dashboards.
If there is no need for immediate feedback and data must go under more strenuous processing, then a physical data center or cloud-based system routes the data. They have powerful systems that analyze, supervise, and store data while ensuring maximum security.
It should be noted that the output comes after a considerable period of time; however, you do get a highly comprehensive analysis of your IoT data. Moreover, you can integrate other data sources with actuators and sensors’ data for getting useful insights. Whether on-premises, cloud, or a hybrid system is used, there is no change in the processing basics.
Seven Layer Architecture
Following are the layers of the seven-layer architecture.
1. Physical Devices
Physical equipment like controllers falls into the first layer of the seven layer architecture. The “things” in “internet of things” is referred to these physical devices as they are responsible for sending and receiving data. For example, the sensor data or the device status description is associated with this type of data. A local controller can compute this data and use NFC for transmission.
Following tasks are associated with the second layer.
- It connects with the devices of the first layer.
- It implements the protocols according to the compatibility of various devices.
- It helps in the translation of protocols.
- It provides assistance in analytics related to the network.
3. Edge Computing
Edge computing is used for data formatting which makes sure that the succeeding layer can make sense of the data sets. To do this, it performs data filtering, cleaning, and aggregation. Other tasks include the following.
- It is used for the evaluation so data can be validated and computed by the next layer.
- It assists in the data reformat to ease up high-level and complex processing.
- It provides assistance in decoding and expanding.
- It provides assistance in the data compression, thereby decreasing the traffic workload on the network.
- It creates event alerts.
4. Data Accumulation
Sensor data is ever changing. Hence, it is the fourth layer which is responsible for the required conversion. The layer ensures that data is maintained in such a state that other components and module of IoT can easily access it. When data filtering is applied in this phase, a significant part of data is eliminated.
5. Data Abstraction
In this layer, the relevant data is processed for adhering to specific properties pertaining to the stored data. Afterward, data is provided to the application layer for further processing. The primary purpose of the data abstraction layer is data rendering keeping in mind its storage and using an approach through which IoT developers are easily able to code applications.
The purpose of the application layer is data processing so all the IoT modules can access data. Software and hardware layer are linked with this later. Data interpretation is carried out for generating reports, hence business intelligence comprises a major part of this layer.
In this layer, response or action are offered to provide assistance for the given data. For instance, an action may be the actuator of an electromechanical device following a controller’s trigger.