What is Edge AI and Why Is It Critical for Next-Generation IoT?

AI can make the IoT more responsive and intelligent, but only if devices can keep up with the data processing needs of next-generation IoT applications, like the voice and vision systems that are changing the way humans and machines interact both at home and in industrial settings. For IoT devices that need to process high volumes of data, securely, in near real time, without dependency on the cloud, Edge AI brings intelligent data processing capabilities to the edge of the network.

Data Processing at the Edge of the Network

Benefits of Edge AI for IoT

With connectivity closer to the source, data does not need to travel to the cloud and back, enhancing processing speeds, reducing latency, lowering bandwidth costs and maintaining closer control of data security. This is critical in situations where many IoT devices work together to process massive amounts of data, like surveillance cameras, or where data privacy and security is imperative, like a robot or cobot in a hospital setting that needs to send patient data.

Faster processing speeds
Lower bandwidth usage
Reduced latency
Increased data security & privacy

Why Integrate Edge AI?

Integrating Edge AI into IoT device design, creates new possibilities for demanding use cases that require heavy IO and reliable embedded AI processing, such as mobile robotics, voice and vision systems, handheld devices, industrial PCs and more.

Process High Volumes of Data E.g. Use automated optical inspection (AOI) to automate quality assurance and process improvement.	Rely on Real-Time Responsivity E.g., Trust that a robot surgeon sewing up a patient will not encounter latency.	Work Without Needing the Cloud E.g., Decrease a device’s time to market by not needing cloud infrastructure built in to every region.
Manage Sensitive Data Securely E.g., Update patient charts within hospitals settings without having to share with the cloud.	Lower Power Consumption E.g., Avoid maintenance on streetlights or cameras in remote areas by extending battery life.	Lower Costs E.g. Constantly scan faces at an airport without paying for bandwidth.

The Future Is at the Edge

Edge AI supports smart societies of the future where humans and robots interact more closely than ever before. For example, autonomous vehicles rely on vision systems to monitor the road and make split-second decisions about where to steer; in this case, what would happen if latency was encountered as a child ran into the street? Voice and vision systems will play an increasingly important role as cobots support our day-to-day activities, enhancing our eyes and ears with facial recognition and audio recognition and translation. These use cases require connectivity at the edge of the network to achieve the desired design goals.

Get inspired: Did you know Edge AI powers these innovative IoT solutions all around you?

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How to Implement Edge AI in Your IoT Product Design

New IoT devices can integrate Edge AI in the product design stage using an Edge-Ai-enabled chipset, or operate with a smart hub to connect and process data from multiple sensors that may not have built-in AI, adding an intelligent layer between basic IoT devices and the cloud.

Get inspired: How to solve the top design challenges of next-generation IoT

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Get Empowered with MediaTek Genio

Manufacturers of consumer, enterprise and industrial devices can innovate confidently and bring leading-edge IoT devices to market faster with the MediaTek Genio. MediaTek Genio incorporates Edge AI to intelligently process data locally. The CPU, GPU and AI Processing Unit (APU) in each Genio chipset work together to enhance intelligent autonomous capabilities at the edge and support high-quality displays, cameras and more.

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