Read this article on privacy, security, and ethical concerns with integrating IoT in the business intelligence cycle. As the section overview states, IoT is a collection of different technologies working together. Still, it is also an amalgamation. This article will help you understand in a detailed discussion how IoT fits into everyday life and its potential from both the technological and sociological perspectives. How can the connected devices you own be utilized with others?
IoT architecture and technologies
The IoT architecture consists of five important layers that defines all the functionalities of IoT systems. These layers are perception layer, network layer, middleware layer, application layer, business layer. At the bottom of IoT architecture, perception layer exists that consists of physical devices i.e. sensors, RFID chips, barcodes etc., and other physical objects connected in IoT network. These devices collects information in order to deliver it to the network layer. Network layer works as a transmission medium to deliver the information from perception layer to the information processing system. This transmission of information may use any wired/wireless medium along with 3G/4G, Wi-Fi, Bluetooth etc. Next level layer is known as middleware layer. The main task of this layer is to process the information received from the network layer and make decisions based on the results achieved from ubiquitous computing. Next, this processed information is used by application layer for global device management. On the top of the architecture, there is a business layer which control the overall IoT system, its applications, and services. The business layer visualizes the information and statistics received from the application layer and further used this knowledge to plan future targets and strategies. Furthermore, the IoT architectures can be modified according to the need and application domain. Besides layered framework, IoT system consists of several functional blocks that supports various IoT activities such as sensing mechanism, authentication and identification, control, and management. Figure 6 illustrates such functional blocks of IoT architecture.
Fig. 6
A generic function module of IoT system
There are several important functional blocks responsible for I/O operations, connectivity issues, processing, audio/video monitoring, and storage management. All these functional block together incorporates an efficient IoT system which are important for optimum performance. Although, there are several reference architectures proposed with the technical specifications, but these are still far from the standard architecture that is suitable for global IoT. Therefore, a suitable architecture is still needsvk to be designed that could satisfy the global IoT needs. The generic working structure of IoT system is shown in Fig. 7. Figure 7 shows a dependency of IoT on particular application parameters. IoT gateways have an important role in IoT communication as it allows connectivity between IoT servers and IoT devices related to several applications.
Fig. 7
Working structure of IoT
Scalability, modularity, interoperability and openness are the key design issues for an efficient IoT architecture in a heterogenous environment. The IoT architecture must be designed with an objective to fulfil the requirements of cross domain interactions, multi-system integration with the potential of simple and scalable management functionalities, big data analytics and storage, and user friendly applications. Also, the architecture should be able to scaleup the functionality and add some intelligence and automation among the IoT devices in the system.
Moreover, increasing amount of massive data being generated through the communication between IoT sensors and devices is a new challenge. Therefore, an efficient architecture is required to deal with massive amount of streaming data in IoT system. Two popular IoT system architectures are cloud and fog/edge computing that supports with the handling, monitoring, and analysis of huge amount of data in IoT systems. Therefore, a modern IoT architecture can be defined as a 4 stage architecture as shown in Fig. 8.
Fig. 8
Four stage IoT architecture to deal with massive data
In stage 1 of the architecture, sensors and actuators plays an important role. Real world is comprised of environment, humans, animals, electronic gadgets, smart vehicles, and buildings etc. Sensors detect the signals and data flow from these real world entities and transforms into data which could further be used for analysis. Moreover, actuators is able to intervene the reality i.e. to control the temperature of the room, to slow down the vehicle speed, to turn off the music and light etc. Therefore, stage 1 assist in collecting data from real world which could be useful for further analysis. Stage 2 is responsible to collaborate with sensors and actuators along with gateways and data acquisition systems. In this stage, massive amount of data generated in stage 1 is aggregated and optimized in a structured way suitable for processing. Once the massive amount of data is aggregated and structured then it is ready to be passed to stage 3 which is edge computing. Edge computing can be defined as an open architecture in distributed fashion which allows use of IoT technologies and massive computing power from different locations worldwide. It is very powerful approach for streaming data processing and thus suitable for IoT systems. In stage 3, edge computing technologies deals with massive amount of data and provides various functionalities such as visualization, integration of data from other sources, analysis using machine learning methods etc. The last stage comprises of several important activities such as in depth processing and analysis, sending feedback to improve the precision and accuracy of the entire system. Everything at this stage will be performed on cloud server or data centre. Big data framework such as Hadoop and Spark may be utilized to handle this large streaming data and machine learning approaches can be used to develop better prediction models which could help in a more accurate and reliable IoT system to meet the demand of present time.