How can AI target 'zombie' batteries – and make recycling safer?
Exploding or zombie batteries can cause injury and disruption during the recycling of discarded electronics. Experts at The University of Manchester have used artificial intelligence (AI) technologies to develop a vision-based device to scan electrical junk and detect problem batteries – even in the most damaged equipment.
The Environmental Services Association warns that too many batteries are carelessly discarded in bins where they're easily damaged and can start to burn, creating so-called 'zombie' batteries.
Profesor Hujun Yin of the Department of Electrical and Electronic Engineering has created a tool that helps reduce fire and safety hazards in recycling across items such as laptops, phones and tablets, DIY power tools, and other home appliances.
Putting out fires
This issue poses a major fire hazard and small fires at recycling centres are a daily occurrence in the UK (on average). As well as being disruptive to the recycling sector, these batteries represent a serious health and safety risk to workers in recycling plants.
Using deep learning technology and images from a moving recycling conveyor belt, Professor Yin’s intelligent vision system is able to recognise zombie batteries, even if deformed or degraded. An in-house prototype has been developed through a Knowledge Transfer Partnership with Benson Components Ltd and successfully tested, using a test rig installed by waste services experts Biffa.
The next step for Professor Yin's AI project involves scale-up and a ready-for-market product, involving an exciting Knowledge Transfer Prtnership between The University of Manchester and Benson Components Ltd, supported by Innovate UK.
Defeating zombies with AI
Businesses across all sectors are becoming increasingly reliant on advanced machine learning technology and automation for making sense of their data, and optimising decision-making, efficiency and performance.
AI (including machine learning and deep learning), data analytics and optimisation techniques have advanced significantly in the last decades, and are now having a revolutionary impact on most industries and businesses – including those looking to mitigate the impact of climate change.
Professor Hujun Yin
Professor Yin is a Professor of Artificial Intelligence in the Department of Electrical and Electronic Engineering.
View Professor Yin's research profile
- Hujun Yin is a senior leader at Manchester's Institute for Data Science and Artificial Intelligence – acting as an access point to the University’s expertise in data science and artificial intelligence, and providing a gateway to leading researchers and experts in the field.
- BBC Research and Development has a five-year research partnership with eight UK Universities, including Manchester, to unlock the potential of data in the media. The Data Science Research Partnership is at the forefront of machine learning in the media industry, helping create a more personal BBC that can inform, educate and entertain in new ways.
- Manchester is one of four partner universities that have established the Greater Manchester AI Foundry which shares artificial intelligence expertise with regional businesses in a bid to help them develop new products and services as part of a £6m project. University researchers with specialist knowledge in AI will work with a minimum of 170 small to medium enterprises (SMEs) in the area.
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