Lithium-Ion Battery Detection

Project description

We are going to make an AI algorithm for the customers of Core Changemakers. With this algorithm, the customer will be able to take the batteries from the waste and prevent the explosion. Basically, the waste will go through the X-RAY and the AI algorithm will detect batteries and an employee is going to take it away from the waste, to prevent it from shredding.
Main Research Question
How can Lithium-ion batteries be detected and located with AI modelling using X-Ray images to prevent them being shredded?

Sub Questions
What are identifiable features of the objects we want to detect?
Which machine learning models are appropriate for this task?
What are limitations or biases in our dataset compared to the real situation?
What other objects can be present that could be mistaken for the target object?
How accurate should the coordinates for object location be?

Context

When it comes to batteries, the most dangerous type is Lithium-ion. These are popular batteries that you can find in items such as mobile phones, electric toothbrushes, laptops, power tools and other daily appliances. The cause for their popularity is the fact that these batteries are one of the most energetic rechargeable available.
We know that the cause of batteries becoming flammable is the sensitivity to high temperatures. The Netherlands prevents this by motivating people to turn in their empty batteries, so that these can be sent to the correct places to be recycled. Moving on to detecting batteries in waste, only in 2022 the world started to think how to automize this process, because now there are only several ways to detect batteries and most of them are manually. From the Core Changemakers research, they are in a process of detecting batteries through X-Ray which they made by themselves and using AI together with it.

Results

The goal of this project is to make a proof-of-concept model to detect the Lithium-Ion batteries in a waste. The team wants to predict the coordinates of each Lithium-Ion batteries in an image through X-Ray. The results we will have is a POC which will detect batteries.

About the project group

Our group 3 people, David is from Software profile, Stephanie is from Technology profile and Izabella is from Business profile. We have one thing in common, which is AI. We have good set of skills to combine for the project.