Putting Power First - The Power Management Behind AI Vision

With Michael Uyttersprot

Cameras running machine learning models can perform real-time analysis of live video. This may be as simple as motion detection, or as complex as facial recognition and behaviour analysis. AI vision systems can drastically improve the effectiveness of surveillance solutions. Part of the success of these systems rests with efficient and reliable power subsystems. Solutions that operate 24 hours a day, seven days a week, must consider reliability and the total cost of operation.

Power efficiency is crucial for AI-enabled security cameras, particularly for systems that are located outside or in remote locations. For obvious reasons, this describes a large percentage of deployments.

To be a truly effective deterrent, surveillance systems must run 24/7 and able to analyse vast amounts of high-definition, full colour video information, in real-time. The use of AI is rapidly gaining traction in this sector. Avnet Silica is actively working with supplier partners and customers to develop advanced AI-based video systems that provide analysis at the camera.

Camera with AI Vision detecting people

The adoption of AI is indicative of how the security market is always looking to stay one step ahead of the bad actors it protects against. Using AI is another, hugely powerful tool that it can employ in the battle. However, AI is also complex and processor-intensive. The goal is to deliver better results, faster. AI can do that, at the cost of processing horsepower.

Machine learning models and neural networks are software-based, so of course they can run in standard architectures. But the mathematical complexity of the models puts pressure on the resources of standard processor architectures. AI accelerators are hardware-based subsystems specifically designed to execute complex math faster. For many applications, using an AI accelerator is practically a prerequisite. But these accelerators can also be power-intensive.

Some security systems may run from power supplies that are unstable or have limited capacity, relying on batteries and possibly even solar power for systems in very remote locations. Energy efficiency for any system running 24/7 is important, but this is amplified when using AI, coupled with the need for continuous surveillance.

Power is the critical factor

It’s not surprising that the power-related and power-intensive components contribute considerably to the complexity and total costs of an AI-based video security system. These include the cost of purchasing and the ongoing operational cost.

The semiconductor industry, Avnet Silica and its supplier partners are addressing this. Power is now a critical factor for any application. There is no doubt that the general trend is a net increase in the amount of power we consume. This is balanced by the development of more energy-efficient solutions.

AI is already being seen as contributing to the trend for more power. Fortunately, we are working hard to develop solutions for Edge AI that consume less power. Running machine learning at the edge is being supported with new processor and microcontroller solutions, and the supplier focus is on both performance and power.

At a higher level, the total system power still needs to be managed. As the power requirement continues to rise, manufacturers are looking to deliver more power in the same or even less space. Power density, as it is known, is a challenge, not least because power supplies tend to generate heat. By using more efficient power solutions, the amount of heat (which is wasted energy) can be minimised and the need for forced air cooling (another power-consumption) better managed.

This industry-wide imperative is being addressed with the development of advanced wide bandgap materials for power solutions. The key technologies here are Silicon Carbide (SiC) and Gallium Nitride (GaN). Power semiconductors fabricated in these materials offer benefits over traditional silicon.

Wide bandgap power semiconductors are proven to be more efficient. In applications with high power requirements, moving to SiC or GaN can deliver better energy efficiency and higher power density.

Power is a differentiator

OEMs developing AI-enabled security cameras now see power supply design as a product differentiator. Efficient power management supports longer time in service, but with more power available it can also allow more sophisticated AI features to be integrated. This may include edge-based analytics or other value-added capabilities that might be optional for the customer and generate more revenue for the OEM.

Power efficiency is moving higher up the priority list for business owners and consumers selecting video surveillance equipment. Operational cost of power cannot be ignored in any application that operates 24/7. And reliability of power is essential for surveillance equipment that is relied on for operational safety.

Avnet Silica is a leader in power, with power engineering specialists around Europe and supplier partners offering the latest in SiC, GaN, silicon MOSFET and IGBT solutions. If you would like to discuss your power requirements with one of our specialists, please contact your Avnet Silica representative.

About Author

 

Michael Uyttersprot
Michaël Uyttersprot

Michaël Uyttersprot is Market Segment Manager for AI/ML and Vision at Avnet Silica, which is continuing to develop and add more products to their off-the-shelf range of kits to enable a wide choice of advanced embedded vision solutions.

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