transfer and cloud-based computation, edge computing can also lower the operational costs associated with bandwidth and cloud storage fees.
Improved data privacy and security: Since data is processed locally at the edge, less sensitive information is transmitted to centralised servers, lowering the risk of data breaches or unauthorised access. This is particularly beneficial in industries like healthcare and finance. Scalability and flexibility: Edge computing allows AI to be deployed in a wide range of environments, from urban areas to remote or industrial locations. This makes it easier to scale AI powered devices and services without overwhelming cloud infrastructure.
Leveraging AI edge computing to improve sustainability Energy efficiency: Edge computing reduces the reliance on large-scale, energy-intensive data centres by distributing computing tasks across edge devices. Processing data locally requires much less energy than transmitting and processing it in centralised cloud servers, thus reducing overall energy consumption. Lower carbon emissions: By minimizing data transmission and the need for constant cloud-based processing, AI edge computing can help lower the carbon footprint associated with large data centres, which consume significant amounts of electricity and contribute to greenhouse gas emissions. Localized resource use: Edge devices typically require less power than large cloud infrastructures. Moreover, they often operate on renewable energy sources or energy-efficient hardware, further reducing environmental impacts.
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A greener future
Cloud computing remains vital for large-scale data processing and storage, while AI edge computing offers a greener solution for real-time, localized tasks. By combining the two, organisations can reduce energy consumption, cut carbon emissions, and decrease dependence on large, centralised data centres, thus supporting eco-friendly computing. This integration allows edge computing to handle immediate tasks more efficiently, with cloud resources augmenting as needed, creating a more sustainable and scalable system for modern applications.
Implementing AI at the edge
If you’re planning to integrate AI into your next product, Anglia is here to provide expert assistance. Our engineering teams possess extensive experience in applying artificial intelligence across a diverse array of sectors. This enables us to seamlessly integrate advanced AI features into a wide range of applications tailored to meet your needs. We collaborate with some of the world’s leading semiconductor and embedded module companies, including industry giants like STMicroelectronics, Telit Cinterion, and Digi International, who are at the forefront of the AI revolution. These strategic partnerships empower us to bring cutting-edge products to the market. Examples of our innovative offerings include vision, motion, and bio-sensors that are equipped with sophisticated Machine Learning (ML) cores, as well as cellular communication modules enhanced with edge intelligence. Additionally, our microcontroller (MCU) and microprocessor (MPU) units come with integrated AI capabilities, ensuring optimal performance for your applications. We also provide comprehensive toolchains and development ecosystems designed to accelerate your product’s
time-to-market, giving you a competitive edge. By offering complete support throughout the development process, we ensure that your product launch is not only successful but also impactful. Whether you’re looking to enhance functionality through AI or streamline communication using intelligent modules, Anglia has the expertise and resources necessary to help you stay ahead in the rapidly evolving AI landscape. Let us partner with you on this exciting journey into the future of technology.
Discover how Anglia can power your next design with sustainable AI solutions. Contact us today at
www.anglia-live.com or simply scan the QR code to get started.
Components in Electronics November 2024 11
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