Cleaning in the Digital World - smart city of 2040

26th of October 2016
Cleaning in the Digital World - smart city of 2040
Cleaning in the Digital World - smart city of 2040

The cleaning sector, as we all recognise, is a down-to-earth one and is slow to adopt new technologies. But if we look ahead to the future with a focus on how customer requirements will develop, we can be a little more visionary. Marco Cardinale, head of product management floor care at Kärcher - which is leading the way in the industry with its Connected Cleaning principle - writes exclusively for ECJ.

This article is from ECJ's new Cleaning in the Digital World special supplement.

The cleaning services sector is a down-to-earth business. There, unlike in the automotive sector or IT, new trends do not follow each other thick and fast. Yet a glimpse into the future, based on actual customer requirements, can be innovative and visionary. Where connected cleaning is making an entry, sensor-supported cleaning on demand is not far behind. This makes it possible for cleaning services providers to cater even better for customers’ individual expectations, improve quality and enhance satisfaction.

Needs-oriented use of service robots or pay-per-use models will present further opportunities that should be utilised. If building service contractors (BSCs) position themselves as building information modelling consultants, the smart building of the future will be designed for efficient, resource-saving working from the outset. Smart integration of new technologies will transform the cleaning of buildings from a necessary evil into an integral component of the smart city of 2040.

Data as the key to new business models: from connected cleaning to cleaning on demand

Fleet and process management solutions already support cleaning services providers’ workflows, says Philipp Kipf of Kärcher Product Management Digital Solutions: “Whether the aim is to know how many hours were worked, the cleaning status in a building, or when machines need servicing, modern solutions help users to plan and deploy their resources efficiently.” The key to such solutions is smart recording of relevant data that BSCs can access in real time, including on the move. Thinking forward to the future, the pool of usable data can be enlarged significantly so that ultimately very precise cleaning on demand can be practised.

The trick is to make use of all data in a smart building. “Weather sensors,” Kipf says, “can reveal whether, for instance, heavy rain will lead to heavier soiling. Sensors in lifts can show which floors have a heavier volume of traffic. WLAN network logon and logoff data or simply the Outlook calendar can tell you which offices or meeting rooms are in use. At some point, sensor technology may be so far advanced that it recognises the type and degree of soiling directly.”

Data analysis

This list could be continued ad infinitum and shows that the opportunity for much more precise working lies in the selection and analysis of relevant data. The trend is moving away from reduction of cleaning intensity for cost reasons and toward intelligent, dynamic operational planning.

“That, in our view, opens up paths to new business models. A basic cleaning service is offered for a basic price. Well-planned cleaning on demand that the customer can rely on is charged at different rates, as is customary in other industries.” Digital management, right through to service panels that record visitor satisfaction, can create the necessary transparency to provide the building’s owner with evidence of the service delivered and to invoice for it.

Service robots to support smooth workflows: from automation to autonomy

BSCs must cope with two important issues  - pressure of costs, of which wages account for around 80 per cent, and finding workers, who are increasingly hard to find and can be deployed more productively elsewhere. In addition, partly as a result of high labour turnover, there is the cost and effort of staff recruitment and induction. This development will become even more critical in future. So our goal is to support cleaning services providers’ workflows as well as we can to enable them to reduce the overall costs of cleaning.

One element under consideration is the use of service robots. Solutions are already on the market, but they function semi-automatically, are designed for large, uncluttered areas and are economically efficient only in such areas. In my view, developing the use of robots in complex premises such as office buildings is a complex matter.

For example, the sensor technology must ensure sufficient environmental perception to guarantee collision-free operation even if something unexpected happens. Various technologies must be linked intelligently, and that requires powerful software. My vision is to have a cleaning robot with a high degree of autonomy that can be used completely safely and economically in any area. Thus solutions that are fit for the future will be geared to specific needs and the actual added value that new solutions deliver for the user.

Pay-per-use and building information modelling: efficient and resource saving at all levels
Digitisation and automation have a further advantage for operational planning. At present, cleaning services providers have their own machine fleets that have to be maintained and serviced. Different models are conceivable in future.

Philipp Kipf notes that “cleaning services providers might no longer buy machines, but instead could book a machine to perform a cleaning service, which could work autonomously or be operated by a person, in a specific area. That would be of interest to smaller companies or for seasonal tasks, special cleaning projects or major events”.Thus increasing flexibility will give BSCs the opportunity to reduce their investment while catering even better for their customers’ demands.

One step further

Ideas of integrating robot-assisted cleaning directly into building information modelling go one step further still. This is already happening to some extent, but increasing integration of sensor systems, data analysis and automation holds even more potential. A robot generates a 3D model of the building, which is the starting point for the development of cleaning workflows.

Questions such as which machines are to be deployed and how many, where charging points should be located or which floor coverings can be cleaned especially efficiently and in an environmentally friendly way can be answered in advance and taken account of in the building. By engaging in this consultation, BSCs can position themselves as competent partners from the very beginning.

Not glamorous … but modern: cleaning services in the Smart City of 2040

Data-supported cleaning on demand, meaningful use of robots, pay-per-use and smart building information modelling do not suddenly render the down-to-earth cleaning sector glamorous. However, they show that new technologies hold a host of opportunities for it to modernise for the future.

At the same time we should not forget that more efficient, economic cleaning opens up new global markets, in countries where the subject has previously played a subordinate role for cost reasons. Philipp Kipp explains that above and beyond that, in the cleaning services sector there are no bounds to the vision of a Smart City in 2040.

“Whether cleaning operatives use augmented reality spectacles to see the degree of cleanliness, facade robots clean windows, or a window cleaner flies through the air with a jet-powered rucksack, digitisation sets an unbelievable pace. Some of this will happen, other things will come and go. We can look forward with keen anticipation.”

Taking the broader view: a day in the Smart City – vision of a clean city

Dr Karl Engelbert Wenzel, specialist in research and advanced development intelligent systems, describes his scenario.

Drones equipped with 3D cameras and GPS systems swarm out to check the situation. Via the Cloud, they control municipal machines on their way to their places of work. Robots with suction pads move along facades to clean windows, albeit only where there is no self-cleaning infrastructure such as blinds incorporating a cleaning function.

In office skyscrapers, cameras use spectral analysis to supply building supervisors with information about major deviations from targets, such as a yoghurt pot that has spilled over in the departmental kitchen. A swarm of cleaning drones with degradable detergents is dispatched.

Normal cleaning is done by the air conditioning system, which extracts dust particles via an ionised air current. The refuse collected during daily cleaning is separated automatically and recycled on the spot wherever possible. Only residual waste is collected – by unmanned refuse collectors. Residential skyscrapers have private vehicle washes in underground garages.

A car waits for its driver to get out, drives autonomously through the wash and parks automatically. Meanwhile, its owner can go to his or her apartment and assign tasks to a humanoid service robot that can use tools.

Office skyscrapers have greenhouses on the mezzanine floors. There, sensors monitor the moisture in the growing medium and deploy watering drones as and when needed. In private dwellings, gamification of cleaning is on the advance, because life is a bit more human on the outskirts of the megacity.

The vacuum cleaner registers which person has used it for how long, and how many dust particles he or she vacuumed up. Points are awarded for that, and for preparing meals with a semi-automatic food processor. Meanwhile, the electric broom keeps the terrace clean, and watering sensors take the effort out of managing the allotment.

After a long bike ride, the e-bike can be cleaned automatically in centrally accessed sharing parks, while nanoparticles have already cleaned the functional clothing en route. When evening draws nigh all cleaning machines are at their charging stations, except for where cleaning is better done at night, such as in some commercial spaces that are not used at that time.

www.karcher.com

To read ECJ's Cleaning in the Digital World supplement click here

 

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