Logging The Data

We recommend this article which explains how you can log your data periodically (every minute) to a Google Spreadsheet for analysis. This will give you a never ending spreadsheet with patterns of usage history, useful in our case to make some visualization of frequency. One could easily replace this with a real database and output the data on the web with a small amount of effort.

What you can do with this type of data is get a minute by minute log of the activity of your sensor from the internet. What we found from a month of door activity is interesting; the hours spent per day/week/month in use, the times of day it’s available, and readings that almost indicates someone’s living in the building. We can’t tell if it’s reducing or creating more time in the bathroom; yet.

Our Findings

With over 100 web designers and developers sitting near this bathroom, we saw an immense amount of traffic around lunch time. Activity at 3AM and false positives (someone closes the door behind them) were fun anamolies to see as well. The most impactful part of this information at a company that tracks billable hours is asking the question:

How many hours per day, on average, are spent in the private bathroom?

Surely a company can't stop employees from using the bathroom to increase efficiency. However they can help increase visibility to what's available when you need to take a seat. Five hours a day on average were spent with this bathroom door closed; one of the many bathrooms in the area. 

That's a lot of time flushed down the toilet

Is a natural response by managers, but what isn't being considered is the time spent leading up to occupancy. Every day we'd watch dozens of people get rejected by a locked door, but since this device helps be more effective. We don't have enough data at this time to determine if the bathroom indicator is creating more or less time spent using it. 


Sure, this gag wears thin with people don't like to talk about bathrooms or the notion of people pooping. If we shift the conversation to a different type of room that does have critical impact on a business; we can talk about people squatting in conference rooms. Conference rooms are a vital resource, we have plenty of tools to book time in them, but we still fail to find a place to meet.


How many conference rooms does your company have? The Nerdery has 37 in one office and they're always booked at certain times in the day. Many times those rooms are booked for recurring meetings most people don't attend anymore. By using a different type of sensor, we could apply our same concept from the bathroom. Determining whether someone is in the room or not is all we need to know, not who it is or when they're done. Simply the status.

Our next project will be solving the problem of conference rooms in businesses in the same way. We hope that this inspires you to solve a small problem of your own using a internet of things style device. 

This guide was first published on Dec 15, 2014. It was last updated on Dec 15, 2014.

This page (Our Results & Ideas) was last updated on Dec 06, 2014.

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