AI-Based Edge Computing Devices For Smart Industry: Benefits And Examples Of Use

YOGYAKARTA Smart industry integrates advanced technologies such as the Internet of Things (IoT), big data analytics, and artificial intelligence (AI) to improve efficiency, improve product quality, and gain competitive advantages. The use of AI-based edge computing devices for smart industry allows decision making and optimization in real-time directly at the nearest point of manufacturing networks.

AI-based Edge computing refers to implementing AI algorithms and AI models directly on local edge devices such as sensors or IoT devices, which allow real-time data processing and analysis without a constant dependence on cloud infrastructure.

This approach not only reduces latency and improves data privacy, but also helps manufacturers take advantage of AI power directly from sources where data is generated.

Artificial intelligence-based edge computing devices have been widely established in various industrial sectors, from the manufacturing to retail industries.

In the manufacturing sector, the AI edge can detect product defects or anomaly in just seconds.

To better understand it, see examples of using AI-based edge computing devices for industry smarts below:

In the manufacturing industry, AI-based edge computing allows instant quality control processes through computer vision systems that can detect product defects or anomalies in just milliseconds, quoted from Fabrity.

In the property industry sector, especially for smart city development, AI-based edge computing can be used to process sensor data in real time in order to create more responsive urban infrastructure, such as traffic management and environmental monitoring.

In the health sector, wearable sensors are able to analyze patient data directly, allowing for faster medical action. An example is an insulin pump connected to a glucose monitor, although it is not a substitute for centralized computing, this technology replaces patient's manual monitoring of blood sugar levels.

An example of the use of AI-based edge computing devices for the most prominent smart industry is seen in the transportation industry.

In this regard, autonomous transportation technology relies heavily on edge computing to process complex sensor data. With this capability, driverless vehicles can make independent and fast navigation decisions, maintaining passenger safety in every situation.

In the retail industry sector, the use of AI-based edge computing can create innovations that make online shopping activities on e-commerce platforms more enjoyable, for example, pick and go services, smart shopping carts, and smart checkouts.

This innovation was created thanks to the use of AI-based edge technology. This is to improve the experience of shopping for customers in online stores.

AI's edge technology offers many advantages for smart industry, including:

As data is processed locally, the response of the system becomes faster, ideal for real-time applications such as automachine controls.

Sensitive data does not need to be sent to the cloud, so the risk of information leakage can be suppressed.

By reducing dependence on central servers, IT's network costs and infrastructure become more efficient.

The system can continue even if the internet connection is disrupted, as processing is carried out on site.

AI allows devices to predict and maintain predictive maintenance to prevent production disruption.

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