A team of researchers at the University of Essex has developed a commercial app called EOptomizer that optimises the performance of other running apps on smartphones while optimising the battery life and thermal behaviour of the device using machine learning.
The same team, comprised of ex-Samsung, Microsoft and HCL employees, had earlier developed a machine learning based algorithm that optimises performance and battery life of future smartphone devices based on the user's interaction with the phone, which has appeared in several press including Business Weekly and The i News.
The app will be launched and demonstrated as part of a workshop, which will be attended by several industry leaders and practitioners, and organised by the University of Essex, hosted in Cambridge on 11th July. We have invited leading companies to participate and provide feedback.
This workshop is being organised as a part of the project titled “Understanding Commercialization Potential of Embedded Machine Learning Technology to Help in Achieving Net Zero Emissions,” funded by the University of Essex. The project proposes to explore the commercialisation potential of our embedded machine learning technology aimed at contributing to the Net Zero emissions goal of the UK.
You are cordially invited to attend the workshop. If interested, please apply through our Google Form.
The organising committee also have access to funding to support travel to the workshop venue. If you require funding, please indicate it in the relevant section of application on the Google Form (please note that funding is limited and thus not guaranteed).
As space at the venue is limited you will receive an email confirming whether or not you have secured a place, along with the status of any funding support you may have applied for.
Project/Workshop organisers and committees