Zanitor - Zan's Facility Maintenance AI Platform is a continuously learning AI system which uses curated data from:
✓ Relevant IoT sensors
✓ Occupant's feedback through feedback displays
✓ Cognitive/Environmental data such as weather, flight schedules etc.
✓ Other Third-Party data
Zanitor consumes all the data available to it and uses what is relevant based on its past knowledge and eliminates those that don’t add value. Zanitor is a hierarchical learning and inference model that predicts cleaning needs based on aggregated signals and provides actionable recommendations which help cleaning staff maintain high efficiency and Quality of Service.
Modern facility management systems and smart washroom systems involve widespread use of toilet occupancy sensors, smart washroom sensors and janitorial sensors.
In the post COVID workplace, it is important to ensure that employees are comfortable with entering and being a part of the work environment. A commercial cleaning
facility requires staff to be dedicated to a small work area so that issues are found and addressed in a timely manner. Servicing proactively addresses needs before
they become issues that can negatively impact customer experience. This time-period will vary widely based on the type of issue, type of facility, and usage of the
facility; without fully understanding these factors the following scenarios repeatedly occur:
1. Staff are scheduled and dispatched to areas not requiring servicing to check if servicing is required.
2. Restroom management staff and janitorial staff are not aware of servicing needs until they are reported/complained about and are dispatched retroactively.
3. In the post-COVID era, occupancy and cleanliness of restrooms are two critical metrics that the customer is interested in tracking
· Client is interested in knowing how many people are in the restroom before going in and if the rest room is full, the employees should be informed and redirected to other available restrooms
· Customer is interested in knowing when the restrooms where last cleaned and when the next cleaning has been scheduled
Because of this lack of information, multiple problems occur in a conventional serviced facility:
· Material wastage - Average waste of toilet paper and paper towel in new deployments in commercial cleaning facility prior to Zan’s recommendations (Baseline) is ~40%
· Lack of staff engagement and job satisfaction - Lack of awareness of servicing needs and tools to manage effectively
· Unsatisfactory cleanliness - Bad user experience and low customer satisfaction with the facility
· Unchecked maintenance issues - Because of the lack of proactive and real-time intelligence, routes are typically on a fixed schedule and dispatching of cleaning staff is done reactively, which perpetuates these inefficiencies. We are proposing a system for you that empowers the restroom management staff to have the information they need to discover and predict servicing needs to proactively dispatch the cleaning staff. Basically, have the right people in the right place at the right time to maximize positive customer experience, minimize material waste (environmental impact), as well as control labor and resource costs of the business.
We offer a range of IOT based toilet occupancy sensors, smart washroom sensors, janitorial sensors and other solutions aimed at making the users' washroom usage experience
pleasant, safe, clean, and pleasurable.
The following solutions are currently deployed, and we can develop new sensors quite easily based on user requirements.
Toilet occupancy sensor is a device that can anonymously count people as they enter and exit the restroom to limit occupancy to safe levels and avoid overcrowding.
Display signage outside the washroom can warn staff in real time whether it is safe to enter or whether they should wait until someone vacates the area. Toilet occupancy sensors can also handle restrooms with multiple doors for entry and exit in large open spaces like shopping malls and airports.
This is a short-range time of flight distance sensor that measures the range of a target object. This sensor can detect the amount of toilet papers that is still available in the roll and can send out alerts when it is nearing empty, threshold level for sending out alerts is configurable.
This is like the toilet paper sensor and can send out alerts by monitoring the paper towel remaining, paper towels may be in the form of rolls or sheets, the sensor is capable of monitoring both types.
Wet Wipes Sensor is a minor modification of the Paper Towel Sensor for hand hygiene, but the functionality is the same. Everything is configurable and therefore it is so easy to develop new sensor types by just changing a few parameters within the embedded application.
Soap dispensers are of two types - one which requires manual operation and other which is automatic or touch free, our sensors can work with both models. Alerts will be sent out when the soap level goes below a specified threshold.
Sanitizer dispensers are also of two types - one which requires manual operation and other which is automatic or touch free, our sensors can work with both models. Alerts will be sent out when the sanitizer level goes below a specified threshold.
Overflowing trash bins present a very unpleasant user experience and a health hazard as well. Traditional methods involve more frequent janitorial visits to the washrooms to empty the trash bins before they become full. Trash Bin sensors use long range time of flight distance sensors to detect the trash bin level and send out alerts when the level goes above the specified threshold.
The water flow sensor can be used with hot water, cold water, warm water, and any fluid for that matter. The sensor sits in line with the water line and measures how much liquid has moved through it. When there is no water flow for a pre-configured amount of time, it will send out an alert about a potential device malfunction.
Leakage detector sensors can identify leaking taps, flushes and urinals and send out alerts to building management for timely resolution of the problem.
Zan's smart restroom solution is a facility management system that makes use of large numbers of sensors to collect data and store them in the cloud. A typical mid-sized
office building has a few hundred sensors, there is so much data generated from these sensors that we need AI, Machine Learning and Data Analytics tools to make sense of
them all. Zanitor from Zan Compute is one such solution which uses the latest technologies and data models to analyze past data and predict future trends. Zanitor is a
continuously learning AI system that can curate data from the relevant IOT sensors as well as third party data such as flight schedules, event schedules and weather
information. Zanitor automatically adapts itself to the type of facility that it is operating in and eliminates data that do not add value.
Zanitor facility management system analyzes all the data, selects a subset of the most useful data, and then preprocesses and transforms it to create a meaningful dataset. Then it splits the dataset into two datasets - training dataset and testing dataset. Training dataset is used to train and tweak the model and the testing dataset is used to back test the model to compare expected vs actual results. The fine-tuned and fully validated model is then deployed into production to predict future trends. This approach has helped our customers reduce wastage of consumables by up to 40%. In the conventional approach they would replace consumables, e.g.,toilet paper roll, based on a fixed schedule irrespective of whether the roll needs replacement or not whereas in the new machine learning approach the system would send an SMS alert to replace the toilet paper roll only when the remaining paper level reaches the pre-specified threshold.
A smart facility is one which has a set of Internet of Things (IoT) enabled devices that use embedded Artificial Intelligence (AI) systems to collect, send and act on data
they acquire from their environments.
The sensors share the data they collect with a gateway which in turn stores it in a database in the cloud for analysis with data sourced from other sensors and external software sources like airports flight schedules and traffic patterns.
The devices don't need human intervention, although it's possible for humans to interact with them to set them up, give instructions or access the data. Smart restroom system is one example of a smart facility management system that vastly improves the decision-making capability of facilities managers.
An AI facility maintenance platform is one which uses sensors to collect data and a machine learning solution to analyze the data with a view to improve building management efficiencies and reduce product consumption / product waste.
Sensors are allowed in washroom solutions only if they do not impinge on user privacy. None of Zan Compute sensors including those that are deployed outside washrooms to collect any private/personal information.
A smart restroom is a restroom which deploys an AI and ML based facility management system. It uses IoT devices to collect data and enhance the experience of its users, and facilities managers, reduces cost of consumable products, labor, and other resources, improves hygiene and overall operations efficiency of all tasks in a commercial cleaning facility.