As a result of open architectures, distributed applications, edge analytics, and data pre-processing and filtering, edge computing has emerged as part of the favorable and essential options for users from diverse sectors, including industries and government firms. In defining what Edge computing IoT means, it has different meanings to different people. It is an acronym that means Internet of Things. Traditionally, the internet has been designed as a network of equipment and computing devices. Examples include printers, Bluetooth devices, CDs, etc. It features a network of devices which are all connected to the internet.
In the process of connecting the physical objects with the internet, businesses can track all of them 24/7, analyze how they’re being used, and have better control over them so that they can offer more valuable outcomes to their users in the form of more efficient services, enhanced experience via the collaboration of things that have autonomous dimensions. Thanks to this cycle, the administrators and manufacturers can leverage real-time insights with real-time locations of the client, which will help to monetize value-added services around product usage and have the opportunity to enhance its future products.
What is Edge Computing IoT?
Edge computing IoT refers to a location that is used for storing data, after which they are processed and computed to satisfy the need of the user. This is possible with the aid of different networks such as the internet. IOT method of transferring data is considered the most helpful and commonly relied upon in order to maintain this storage activity and processing without increasing the threats of cyber-attack or data theft or any such issues that may arise as a result of network trafficking.
In the broad sense of it, we can characterize the Internet of Things into 3 things. Below are some examples of IoT Edge Computing you should know.
This comprises smart homes, pet and personal monitoring, regular items such as door locks, kitchen appliances, etc. all of which can be connected.
Several machines in a given factory can also be connected together. Additionally, if we have a wind farm that is located in a very remote area, then we can monitor those wind turbines if there’s access to edge computing IoT and the internet.
Smart public services such as transportation including several sea and road routes or railway networking. Also, it can include a water supply system in the house or even an electricity grid in a state or city. All things which deal with the public are categorized under this category.
IoT and edge computing
In the ground stage, the components that are responsible for producing data have been fixed.
In the Next stage, gateways are mounted, sending all the data that they have received from components that produce data to the centralized system (cloud). Usually, they don’t possess any processing capability in ideal IoT architectures.
In the third stage, the cloud is mounted. At this level, the data is stored, processed, analyzed, and based on this, the manufacturers can make different decisions.
Edge Computing IoT and other Technologies
In the technical sense, edge computing IoT describes the convergence of several technologies that have been existent for some time now such as actuators or sensors for monitoring and controlling things more precisely and efficiently or smartphones which enable the users to work remotely. Other convergence sources are also needed for Edge computing IOT to help the user. Some of them include:
- Artificial Intelligence
- Single Board Computers (SoCs)
- Embedded programming
- Big Data
- Intelligent Devices
- Cloud Computing
Benefits of Edge Computing
The primary objective of Edge Computing is to completely address certain critical failure points that are inherent in centralized networks. The usefulness of Edge Computing can be seen in the following aspects
The propagation of devices that generate vast data streams at the edge of the network is a cause of major network challenges. It is not possible for edge IoT devices, autonomous devices, security cameras, and video games to transmit their entire data to centralized facilities. It is now becoming necessary for pre-processing, analysis, and compression for IoT edge computing at edge nodes to be deployed much closer to the source.
Data security is a significant issue for modern operations, and the increased global emphasis on the protection of consumer data rights demands for strong security for edge computing devices. This is generally handled at the application layer or OS on the particular edge devices (laptops, phones, etc…) Security issues are passed down from the central cloud to the device of the user, thereby minimizing network strain and reducing the quantity of personal data being transferred back to the central cloud.
Latency simply refers to a measure of network distance between the client and the compute node. As businesses are increasingly developing and relying on hyper-responsive or real-time applications, they must have access to reduced latency edge cloud platforms in order for them to be successful.
A number of industries, including security, gaming, and self-driving cars, are dependent on edge Artificial Intelligence for processing data in real-time and making split-second updates to apps. When there is great distance between the network edge node and the centralized cloud region, these apps are bound to fail. Edge clouds can manage data processing on local devices so as to limit latency and transmit back the data crucial for application performance.
Video & Media
We all rely on visual mediums for communication, particularly with the tremendous growth of streaming services. On-demand streaming services, including Twitch, Netflix, and Google Stadia, transmit a great amount of data per second over user networks. The use of a distributed edge network to manage data processing localizes the burden of performance, consequently ensuring that users in any part of the world have a smooth experience.
IoT and edge devices
Initially, IoT edge devices are some of the servers that were deported or placed at the end of the nodes, for instance during the provision of remote services in a hospital or hotel with the aid of network base stations. Different devices are designed to control and manage the different networking, computing, and storage resources. According to Infosys, “edge computing IoT devices are such end-to-end servers with an encrypted description that majorly focuses on various network functions with a wider view such as connecting the edge deployment to the larger network and acting as a firewall and that firewall is a part of edge computing IoT under the transfer of data”.
Challenges facing IoT
There are a plethora of challenges being faced in the usage of these IOTs by both the manufacturers and users. Some of these challenges include:
- Huge Data Volumes (Data-Intensive)
- Real-time actionable insights
- Over the air upgrades
- Standardization has not kept pace with the growth.
In this article, we have covered different dimensions and aspects of edge computing IoT; the meaning of edge computing IoT and how it is being used in the world today, its systematic working structure. In addition, this article has attempted to shed more light on both edge computing and IoT devices, the concept of edge analytics in IoT, Edge computing in IOT-based manufacturing, and different IoT edge computing platforms. While we have shared the benefits and importance of Edge Computing IoT, we however further discussed the limitation aspect of edge computing and the IoT.