If you have ever been in a public restroom you may have seen a paper checklist. Cleaners use these checklists to register the date, time and person that last cleaned the restroom. These papers can get misplaced, dirty or ripped which causes all the data to be lost or unusable. No more with the Internet of Things, sensors, apps and the Smart Washroom.
In fighting the spread of infections and disease, hand hygiene and cleaning quality is of great importance*. Especially in in public areas, such as toilets or washrooms. This has increased pressure on the medical industries as well as public area maintenance. In combination with a lack of personnel, this situation requires innovative solutions to meet hygiene standards.
The transformation to a smart washroom and toilet groups
Routine, uncontrolled and potentially unnecessary paper checklists are common in traditional washrooms. At the end of the week, managers process and evaluate the information which only serves to check completion of tasks.
In the past, when washrooms had a toilet lady at the door, things were very different. She welcomed you, solved your problems, knew how many people had used the washroom and decided when she needed to clean the room. This was true evidence-based cleaning.
Digital toilet groups with sensors
For a restaurant it can still pay off to use a toilet lady. But for (semi) public washrooms it is too expensive to use a person. And this is what the internet of things can solve. Wireless sensors digitally record what the toilet lady used to do and answer traditional questions.
- How many people used the washroom on a particular day or time?
- What is the level of toilet paper and soap in the dispensers?
- When wil bins in (semi) public spaces be full?
The washroom, toilet and dispenser sensors send and store their data to a central cloud database. Using any mobile device, managers and cleaning staff have real time access to all data. E.g. individual dispenser fill levels, the amount of people that have entered the restroom and the toilet bin fill rate. Accordingly, they can plan cleaning activities based on data.
In short: digital evidence-based cleaning.
Big Data in toilet groups and public washrooms
But it gets even better: digitally recording 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 on when certain areas require cleaning or specific dispensers need refilling. 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).