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AI-powered app aims to optimize smartphone battery life

AI-powered app aims to optimize smartphone battery life

Market news |
By Rich Pell



The app – called EOptomizer – will be demonstrated to expert researchers and designers as well as major manufacturing companies like Nokia and Huawei, say the researchers, who hope that it will be adapted across the industry and help drive down carbon emissions, by making consumers’ goods last longer. Developed by former Samsung, Microsoft and HCL Technologies employees, the software uses artificial intelligence (AI) to optimize chip performance, heat generation and efficiency.

The app works, say the researchers, by dramatically increasing efficiency and reliability in phones, tablets, cars, smart fridges and computers’ batteries.

“It is our hope that this app will help make everyone’s life better, save them money and help save the environment,” says Dr Amit Singh, from Essex’s School of Computer Science and Electronic Engineering. “This will be the first step on what we hope is a journey that will see our app in the hands of consumers across the globe.”

The cutting-edge technology analyses how an app is being used throughout the day and optimizes energy use. For example, a user might quickly scroll through a news app while at work to check the headlines, which will require a higher FPS (frames per second) than when they spend more time on the app in the evening, slowly scrolling down and reading more stories in full.

The methodology, say the researchers, means the AI realizes the change in FPS for the app being used and tries to find the best operating frequency of CPU and GPU processors to cater for the change while still consuming the least amount of power and temperature gain in the device – a critical issue in mobile phones.

The app will be launched and demonstrated as part of a workshop, which will be attended by several industry leaders and practitioners, and organized by the University of Essex, hosted in Cambridge on 11th July. The workshop is being organized as a part of the project titled “Understanding Commercialization Potential of Embedded Machine Learning Technology to Help in Achieving Net Zero Emissions,”

For more, see “EOptomizer launch and Workshop.”

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