Edge computing in IoT is rapidly gaining popularity across industries such as healthcare, manufacturing, logistics, and transportation. By reducing latency and ensuring faster response times, edge computing gateways enables organizations to make critical decisions in real-time based on analyzed data.
What is Edge computing in IoT?
Edge computing in the Internet of Things (IoT) is the procedure of gathering, examining, and processing data closer to the data’s source, at the network’s edge. In contrast to conventional cloud computing models, which send data to a centralised cloud infrastructure for processing and analysis, this strategy uses distributed cloud computing.
Edge computing eliminates the need to send data to a distant server for processing by allowing IoT devices to collect and analyse data instantly. This enables quicker reaction times and more effective network bandwidth usage. Additionally, the data can be processed and analysed locally, which is important in circumstances with weak or unstable network connectivity.
Edge servers, IoT gateways, and other hardware located at the network’s edge can all be used to implement edge computing in the IoT. These gadgets make it possible for data to be collected and processed decentralizedly, which lowers latency and boosts the effectiveness of the IoT system.
Why choose a Edge computing gateway?
Edge computing gateways operate on the same principles as standard IoT gateways, including data gathering, processing, and transmission. However, edge computing gateways have several distinctive qualities that draw both device integrators and gateway developers to them:
You may also be interested in What is an IoT Gateway (Complete Guide 2023): Definition, Examples, Functions
Processing Power
Compared to common IoT gateways, EDGE computing gateways often have more processing power. While Common IoT Gateways concentrate on data collection and transmission, ERFORM Local Data Processing and Analysis.
Local Data Storage
Unlike standard IoT gateways, edge computing gateways may include local storage capabilities for storing and processing data locally.
Data processing capabilities
Compared to standard IoT gateways, edge computing gateways have more sophisticated data processing capabilities. This enables them to carry out difficult data processing tasks, including machine learning and AI, at the network’s edge.
Network Connectivity
To provide dependable and resilient data transfer, edge computing gateways may have a variety of network connectivity choices, including Ethernet, Wi-Fi, and cellular networks. There may not be many network connectivity options for common IoT gateways.
Security
Compared to standard IoT gateways, edge computing gateways often include higher security measures. This is due to the fact that edge computing gateways process and store sensitive data locally, necessitating the adoption of more sophisticated security mechanisms to prevent cyberattacks.
Edge computing means faster and more stable services at lower cost. For users, edge computing means a faster and more consistent experience. For enterprises and service providers, the edge means low-latency, high-availability applications with real-time monitoring.
Edge computing application
Edge computing enables processing and storage capabilities to benefit industries involving the IoT. Here are some classic use cases:
Automatic driving
One of the initial use cases for autonomous vehicles could be platooning of truck fleets. In this instance, a convoy of trucks follows one another to conserve gasoline and ease traffic. With edge computing, all vehicles save the one in front of them could operate without a driver since they could communicate with each other in real time. The control of self-driving automobiles is significantly influenced by the edge computing gateway.
Self-driving car sensor and camera data can be gathered, processed, and analysed. For example, picture data can be transformed into a processable format, impediments can be detected and identified using algorithms, the location and speed of the car can be calculated, and so on. Edge computing gateways can raise the security and dependability of autonomous cars by reacting quickly and making quick judgements and controls.
In addition, edge computing gateways can offer security protection by encrypting data and preventing unauthorised access to self-driving car systems via authentication and other security procedures.
Agriculture
Edge computing gateways can help farmers better manage soil and crops to improve agricultural productivity and yields. For example, in large-scale farming, edge computing gateways can analyze soil and environmental parameters such as temperature, humidity, and light intensity to optimize irrigation, fertilization, and harvesting processes. In home farming, edge computing gateways can provide real-time information and advice to help farmers better manage crops and animals.
The growing popularity of technologies such as the Internet of Things and artificial intelligence is a key factor in developing connected greenhouses in the coming years. Dusun DSGW-030 edge computing gateway has powerful performance and has helped greenhouses successfully realize IoT-based LED greenhouse lights Greenhouse monitoring system.
You may also be interested in IoT Based Greenhouse Monitoring and Control System for Smart Agriculture
Retail
In retail, edge computing gateways can provide businesses with a better customer experience, increased sales, and reduced costs. Taking coffee shops as an example, edge computing gateways can help coffee shops provide better services and management. First, edge computing gateways can collect and analyze customer data, such as purchase history, shopping behavior, and preferences. Through these data, coffee shops can provide more personalized services, such as providing customized coffee, pastries and drinks for specific customers.
Second, the edge computing gateway can also monitor in-store traffic and shelf inventory to help coffee shops optimize layout and replenishment. By analyzing in-store customer flow data, edge computing gateways can help coffee shops optimize seating layouts and service processes to increase customer satisfaction and sales. At the same time, the edge computing gateway can also monitor the shelf inventory and remind the store staff to replenish the goods when necessary, so as to avoid out-of-stock and waste of goods.
You may be interested in IoT Asset Management Solutions for Coffee Shops
Medical
In the medical field, edge computing gateways can help medical institutions provide better diagnosis and treatment services, and improve medical efficiency and quality. Suppose a hospital uses an edge computing gateway to manage patient monitoring data. In this case, the edge computing gateway can connect various sensor devices, such as electrocardiogram machines, blood pressure monitors and thermometers, etc., and collect and analyze physiological data of patients.
By using distributed computing and analysis technology, the edge computing gateway can process and analyze these data in real time, and generate detailed reports and alerts to help doctors quickly diagnose and treat conditions.
In addition, edge computing gateways can also improve the efficiency and reduce medical costs of medical institutions. For example, edge computing gateways can automatically monitor the health of medical equipment and send alerts to technicians to prevent equipment failures in advance. At the same time, the edge computing gateway can also optimize the utilization of hospital resources, such as optimizing the process of patient queuing and examination, thereby improving the efficiency and quality of the hospital.
You may also be interested in Remote Cardiac Monitoring Using Edge Computing Gateway
Industrial manufacturing
Edge computing gateways are frequently employed in the realm of industrial manufacturing. It can aid manufacturing facilities in implementing intelligent manufacturing, increasing output effectiveness and product quality. Industrial equipment data, such as vibration, temperature, and pressure characteristics, can be collected and analysed by edge computing gateways.
These gateways can also monitor and alter industrial equipment in real time. Edge computing gateways can assist plant engineers and technicians in quickly identifying and resolving equipment issues, minimising downtime and increasing production efficiency.
Edge computing gateways can also forecast equipment breakdowns and maintenance requirements. Edge computing gateways analyse past data and equipment operating conditions to forecast potential failures and maintenance requirements. They do this using machine learning algorithms and data analysis methodologies.
In order to prevent equipment breakdown and production halts, this enables plant engineers and technicians to take preventative action. In order to enhance product quality and streamline the production process, the edge computing gateway may also gather and analyse data about the production line, including information about materials, energy use, and quality control. Edge computing gateways can assist manufacturers with inventory management and logistics process optimisation, lowering manufacturing costs and increasing productivity.
You may be also interested in Optimizing Efficiency with Edge computing gateway in Warehouse
Dusun edge computing gateway
The edge computing gateway supports real-time processing and analysis of large-scale data, can quickly process and analyze massive data, and output accurate results. This can help businesses better understand market and customer needs, leading to more effective business decisions.
Dusun IoT is a company that focuses on edge computing of the Internet of Things. Our edge computing gateway adopts an open design and can be adapted to different hardware and software platforms. At the same time, the Dusun edge computing gateway also provides a wealth of APIs and SDKs, so that developers can customize IoT hardware development according to their own needs to meet the needs of various application scenarios.
Dusun edge computing gateway adopts cloud management and configuration technology, which can realize rapid deployment and centralized management of devices through the cloud platform. At the same time, Dusun edge computing gateway also supports automatic discovery and configuration, which can reduce the workload of manual operation and configuration, and improve the efficiency and accuracy of operation and maintenance.
Secondly, the Dusun edge computing gateway adopts a variety of security technologies, including encryption, authentication, access control and data isolation, etc., to ensure the safety of devices and data. At the same time, Dusun edge computing gateway also supports remote upgrade and management, which can update security patches and firmware in time to maintain the security and stability of devices and systems.
Dusun edge computing gateway adopts distributed computing and caching technology, which can quickly process and respond to data requests. This can reduce the delay of data transmission, improve the application response speed and user experience.
Please don’t hesitate to contact us via the side form or chat. Professional engineers will recommend you the edge computing gateway suitable for your project.
Edge computing in IoT
What does the IoT edge layer entail?
The physical hardware of your devices, the embedded operating system that controls the processes on your device, and the device firmware—the software and instructions pre-loaded on your IoT devices—make up the edge layer of your IoT workload.
What distinguishes an Internet of Things (IoT) edge from a gateway?
The main distinction is that since protocol gateway is a cloud feature, your device must at the very least be able to send messages to the cloud for protocol translation, regardless of the protocol it uses. The IoT Edge, as its name implies, is a component of edge computing and is situated closer to the device.
What does the IoT edge layer entail?
The physical hardware of your devices, the embedded operating system that controls the processes on your device, and the device firmware—the software and instructions pre-loaded on your IoT devices—make up the edge layer of your IoT workload.