We listed and answered frequently asked questions below. Please let us know which aspects are working well or could be improved via our 15-minute Survey Study. We appreciate your input!

Q1: Why sometimes a dialog box popped up and asked me to enable video autoplay?


A1: During labeling, videos need to play and loop automatically. However, if a mobile device has data saver enabled, videos will stop autoplay. Also, some mobile devices pause videos after users wake it up from sleeping mode. In order to enable autoplay, browsers require user interactions, which is why the system shows the dialog box.

Q2: Why my labels did not pass the quality check? How did you define the quality?


A2: For each batch (16 videos) on the page, the system randomly placed several videos with known answers, also called gold standards. A batch will pass the quality check if you label these gold standards correctly.

Q3: Why sometimes I saw similar videos? Were they the same?


A3: There can be two reasons. Firstly, videos that have closer times (e.g., 8 and 8:10 am) can look similar due to the same weather and lighting conditions. Secondly, gold standard videos for the quality check can appear again if you label many batches.

Q4: What are you planning to do with all these labeled data?


A4: We will use these labeled videos to train a deep neural network for detecting smoke emissions. While deep neural networks have been proven to outperform traditional models in various applications, training such large networks requires a considerable amount of labeled data, which is why we need volunteers' help.

Q5: Where do these video clips come from?


A5: We selected and cropped several windows into videos from our camera network (as shown in the following image). Most videos are from the the Clairton Coke Works camera, and some videos are from the Edgar Thomson Steel Works camera. Each video contains 36 frames, which represent about 6 minutes in real-world time.

Q6: Can I build a similar system with your code?


A6: This project is open-sourced on GitHub. Please feel free to reuse the code.

Q7: Are there other actions that I can take to advocate for better air quality?


A7: If you are interested in smoke reading (visual emissions observation using EPA Method 9), we recommend checking the smoke school training materials.

Q8: Why does this tool not support systems that are older than Android 7 and iOS 11?


A8: When labeling smoke, this tool shows 16 videos at the same time. Older devices have difficulties in playing these videos, which results in poor user experiences.

Q9: How does the system know whether smoke emission is present in a video or not?


A9: At least two volunteers will review each video. If their answers agree, the system marks the video according to the agreement. Otherwise, the video will be reviewed by an extra volunteer, and the result is aggregated based on majority voting.

Q10: Why are there no nighttime videos to label?


A10: Smoke emissions in nighttime videos (captured by commercial digital cameras) are extremely tough for the computer to recognize due to insufficient light. We want to focus on training the computer to detect daytime smoke emissions first.

Video autoplay is disabled. Please enable it.