Smart Washroom of the Future

Smart Washroom of the Future

If you have ever been in a public restroom chances are that you have seen a paper checklist hanging next to the door. These are used by cleaners to registrate the date and time and when and who cleaned it. These not so handy papers can get lost, filthy or destroyed which causes all the data to be lost or unusable. Well not anymore with the future of Internet of Things, sensors, apps and the Smart Washroom

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The transformation to a smart washroom and toilet groups

These checklists are a good example of yesterday’s washroom: a routine, uncontrolled and potentially unnecessary check on a piece of paper. The information on the paper is only processed and evaluated when the managers get it at the end of the week. And it only serves to check if something has not been fully completed.

Evidence based toilet lady

How different the experience was when washrooms had a toilet lady at the door! The presence of this lady served several purposes: she welcomed you, could solve problems for you, and she kept an eye on how often a washroom was used, and could, based on this, decide when she had to clean. This was true evidence-based cleaning.


A recent update on the Smart Washroom (3/2020)

Sparked your interest? Discover more by visiting the page on the recent development
of the Smart Washroom with Ophardt Hygiene.

Smart Washroom >>>


Digital toilet groups with sensors

For a restaurant it can still pay to use a toilet lady. But for (semi) public washrooms it is too expensive to use a physical person. And this is what the internet of things can solve. Wireless sensors enable us to digitally record what the toilet lady used to do: how many people have used the washroom since it was last cleaned, how much toilet paper is there and how much is left on the towel roll . Also in measuring the filling rate of trash bins in the (semi) public space via partner Binster.  In short: evidence-based cleaning.

Big Data in toilet groups and washrooms

But it gets even better: digital recording of the measurements means that we can analyze the historical data, in order to discover trends. And if the data sets are large enough, we can use big data analysis to make real-time predictions. The end goal: optimization (a simple example: making a round along full trash cans instead of making a round because it is six o’clock).


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The impact of a Smart Building on Cleaning Companies of the Future

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