BAMFmartinFTW t1_is4vn3s wrote on October 13, 2022 at 9:42 AM

Hi, I want to know if the next case is possible through ML for my project.

For my schoolproject about logistics my idea was to measure what percentage of the cargo hold is loaded with goods (12ton truck, with two axis and a white canvas around the cargo hold). I thought this approach was interesting because a single sensor in the middle of the cargo hold would give faulty reading if the cargo is loaded unevenly. As the contents of the cargo hold consists of bin bags (so it's a soft base product and a non -structured load)

So I thought of hanging a camera in the cargo hold (lights comes through the canvas) and through ML train the model of how much the cargo hold is loaded. The cargo gets weight when unloading. And everytime some cargo gets loaded an estimation is made of the weight that was added.

Would it be feasible to mount a camera and train it with the unloading weight and perhaps also with the estimation weights? Or does it sounds too much as a hassle and would Lidar be a more realistic approach in which case I would search for another project case?

Thank you in advance

ThrowThisShitAway10 t1_is5onty wrote on October 13, 2022 at 2:17 PM

I think the data would be rather noisy, and you'd have to collect a lot of it.

It would be nice if you could collect the sensor data from the single sensor in the middle of the cargo as well as the camera data. This way you have a good prior (approximation) for the weight. So instead of trying to predict the weight using camera data alone, you just have to predict the difference between the sensor weight and the true weight.