The CMU CREATE Lab developed this tool to engage citizens in labeling smoke videos, which are obtained from our Pittsburgh Mon Valley monitoring camera network. With sufficient labeled videos and state-of-the-art artificial intelligence, we aim to train a computer system that can detect smoke emissions automatically. A brief introduction video about this tool can be found at this link.

Smoke disappears slower and has unclear edges when compared to steam. Smoke can also have various opacities. High-opacity smoke can block most of its background. Here are examples that show high opacity smoke.

For low-opacity smoke, its background is mostly visible. Here are examples that show low opacity smoke, which also needs to be identified.

Steam disappears faster and has sharp edges when compared to smoke. Steam also has extremely high opacity, which makes its background not visible. Here are examples that show mainly steam, which should not be selected.

Smoke and steam can appear at the same time. Here are examples that show both smoke and steam, which also needs to be identified.

Various bad weather conditions can affect the camera view. Here are examples that show bad weather, which should not be selected.

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