Devices are getting smarter, from your phone understanding your voice to self-driving cars navigating traffic in real-time. A big reason this is becoming possible is because of edge AI.

Instead of processing data in the cloud, there’s an increase in building AI smarts right where the data is created — your devices. And it's making things faster, more private, and more reliable in many new ways.

What is Edge Artificial Intelligence (Edge AI)?

Imagine giving your devices their own built-in brain. That’s essentially what Artificial Intelligence, or Edge AI, is.

While traditional AI models rely on sending data to a remote, centralized cloud computing center or a data center for analysis and processing, edge AI does that computation directly at the source, analyzing data collected by devices in their immediate environment.

This means the computational processing of data happens in your smartphone, factory sensor, security camera, or whichever intelligent device you use.

Advantages of Edge Artificial Intelligence

There are many good reasons why edge AI is becoming increasingly popular:

• Low Latency

With edge AI, the time it takes to analyze data and react is significantly reduced. It enables real-time processing by analyzing data directly on the device, so there are no delays in transmitting information to the cloud.

Faster response times are important for applications that require efficiency, such as industrial robots performing tasks or autonomous cars making driving decisions.

• Privacy

Edge AI offers a more secure and private way to handle data. Since the cloud is not necessary anymore, there’s no constant need to transmit information back and forth over networks.

By keeping data on the device, the risks of data breaches during transit and exposure of personal or confidential information are minimized.

• Reduced Bandwidth Requirements

Processing data locally on devices means only relevant insights or summaries, rather than raw data streams, need to be transmitted.

Lower data volume reduces network congestion and the costs of cloud bandwidth consumption, especially for applications with numerous data-generating endpoints.

• Reliability

Even when network connectivity is interrupted or unstable, edge AI ensures continuous operation. Because edge devices don’t rely on a constant connection to a remote server, they can operate independently.

Specific applications like safety-critical systems, remote monitoring, or industrial automation benefit significantly from uninterrupted functionality.

• Energy Efficiency

Edge AI conserves energy by minimizing the power needed to send and receive large volumes of data with cloud servers.

Specialized AI chips designed for edge devices are often optimized for power efficiency, too. They can perform sophisticated AI tasks with lower energy consumption.

Applications of Edge Artificial Intelligence

You can find Edge AI making a difference in a wide range of industries:

• Industrial Automation

The ability to perform real-time monitoring and data analysis directly on the factory floor lets you immediately spot anomalies, predict maintenance needs, and optimize workflows.

This leads to less downtime, higher efficiency, reduced waste, and improved product quality.

• Retail 

Edge AI is changing how retail works. For example, smart shelves monitor inventory in real-time and automatically trigger restock warnings.

You can also analyze shopper behavior so retailers can offer personalized customer service, optimize product placement, and understand customer preferences.

• Autonomous Vehicles

For self-driving cars, edge AI processes information in real-time for safe navigation. The vehicle itself analyzes data from its sensors (cameras, radar, and lidar) to understand its surroundings and make safe and immediate driving decisions.

This on-the-spot processing is essential for reacting instantly to changing road conditions and potential hazards.

• Healthcare

Any second could be a difference between life or death in the healthcare industry. Edge AI computing system provides immediate insights and analysis at the point of care.

Wearable devices, such as smart watches, monitor health in real-time and detect red flags in vital signs so healthcare professionals can act quickly if needed.

Edge AI also speeds up medical image analysis on devices, leading to faster diagnosis and treatment and, ultimately, better patient outcomes.

• Smart Cities

In smart cities, edge AI helps make everyday life easier and more efficient. For example, traffic lights that adjust based on real-time congestion or security cameras that identify incidents without relying on a distant control center.

Moreover, edge AI enables real-time energy monitoring and environmental data analysis, so cities are empowered to make smarter, sustainable choices.

Future Outlook of the Edge AI Industry

AI is shaking up the tech world — and it’s just the beginning. Major players like Microsoft and Google are pushing hard to create advanced AI that can understand different types of information.

Meanwhile, companies like NVIDIA and AMD are dominating the cloud AI computing chip market. As the core technology for these advanced AI systems continues to improve, AIGC is sparking a revolution in applications.

Artificial intelligence is starting to power all sorts of new apps and tools. It’s an inevitable trend that large models will be deployed on the edge and mobile devices.

BRAV Product Series from JHCTECH

The Edge AI industry has three layers: upstream carrier suppliers, midstream operation service providers, and downstream industry users.

Upstream suppliers are manufacturers of basic hardware infrastructure such as edge AI chips, computing modules, edge gateways, servers, and controllers. They also develop foundational software, including AI algorithms, OS, platforms, and security.

The BRAV series

As a leading provider of edge AI computing systems and controller equipment, JHCTECH offers powerful solutions like the BRAV series, a robust lineup of industrial-grade edge AI GPU computers.
Our BRAV embedded computers are built for speed with AI accelerator cards to process information rapidly and a large storage capacity for edge AI applications.We offer two main architectures to meet diverse user needs: NVIDIA Jetson™ Platform and Intel x86 Architecture.

NVIDIA Jetson™ Platform delivers AI performance in a compact, energy-efficient design. This makes it perfect for robotics and smart cameras, where space and power are often limited.

Intel x86 Architecture boasts high versatility and raw processing power, making them compatible with a wide range of software ecosystems. They are built for complex computations and multitasking.

These edge AI GPU computers are perfect for various applications, including automated guided vehicles, autonomous vehicles, ETC license plate recognition, and pure AI computing applications (image and video analytics, deep learning, machine vision, data mining, etc.).

The BRAV-7720, for instance, is a workstation-grade Edge computing system powered by Intel's latest and most powerful processor. It’s ideal for demanding edge applications like communicating with vehicles on highways, guiding unmanned vehicles, and enabling high-precision machine vision systems.

Built on an MEC system, the BRAV7134 MEC System is an excellent fit for intelligent vehicles and logistics. With its multi-core ARM CPU and high-performance GPU, it's built for demanding edge deployments.

JHCTECH: Your Edge AI Advantage

Edge AI is quickly transforming industries by bringing powerful capabilities closer to the data source. The benefits are clear — low latency, enhanced privacy, and improved reliability.

JHCTECH's BRAV series stands at the forefront of this technological wave, providing stable and high-performance industrial computers for many demanding applications.

The future of intelligent applications is at the edge. Explore the possibilities with JHCTECH. Reach out today to discuss your specific needs.