Here are some more ideas for you to use the data * What's the most common pattern for two occupied toilets (from the frequencies, it appears to be the classic

Here are some more ideas for you to use the data * What's the most common pattern for two occupied toilets (from the frequencies, it appears to be the classic occupied-free-occupied, to allow more space between users) * What's the day of the week that the toilets are most used? And less used? (it would also be nice to cross-reference that with the menus from nearby cafeterias) * Check if there's any correlation between the frequency of people going to the toilet and issues on you bug tracker. What about the average duration? * If you extend your system to a coffee machine, correlate the coffee consumption with the toilet's usage. Actually, with this, you could use most of this data and train a decision tree with it. Then, you could warn your co-workers with "In 10 minutes it is expected that the toilets will be occupied, maybe you want to go now?". On the other hand, maybe you just want to keep this functionality to yourself, otherwise everyone will just go to the bathroom 10 minutes earlier.