The Eco Bot Scrub 75 is the new class leader in autonomous cleaning robotics from ICE is extremely quick and easy to map the commercial & residential areas to be cleaned.
The Eco Bot 50+ is an easy to operate robotic scrubber dryer. It takes just 30 minutes to map a…
The Eco Bot 50 Combi is an automated scrubber dryer that has been specially designed to sweep and scrub surfaces…
AUTO REFILLING & EMPTYING The Eco Bot 50 will automatically return to the service station when either the fresh water…
The Phantas is a small machine with a 30 cm cleaning width that literally cleans right up to edges and corners,…
The Eco Sweep 111 is a autonomous heavy duty sweeper, ideal for both internal and external environments.
The ICE Eco Vac 40 is perfect for the consistent cleaning of supermarkets, showrooms, shopping centres, and public facilities. Advanced Safety & Navigation System include when you hire from ICE.
The IRIS is a charging station that holds 8 Mini Bots for easy transportation and distribution. The IRIS is a…
The Mini Bot II is a robot vacuum cleaner with an auto-empty and charge docking station. This unit vacuums for…
This isn’t just another robotic vacuum mop; it’s a comprehensive cleaning companion designed to make your life easier, cleaner, and…
FAQS
ICE have been pioneering robotic cleaning for over a decade so it’s fair to say we have encountered numerous reservations and misconceptions along the way! The most common and obvious misconception is that cleaning robots will replace people and take away their jobs. This is certainly not the case and is something we have been educating the market on over a number of years. It hasn’t been an easy road, but the cleaning industry is now truly embracing the fact that automation isn’t about replacing operatives, it is about collaboration, working alongside the robotic equipment and redeploying the valuable resource elsewhere, such as for thorough detailed cleaning tasks.
ICE provide three detailed training sessions when installing autonomous equipment from our ICE Co-Botics range. These essential sessions cover mapping, operation, daily maintenance, data and reporting. In addition, we also highly recommend the extra security of our full-service maintenance package for all robotic equipment. This is vital and gives peace of mind that any issues with the equipment can be fixed by an expert ICE engineer.
If the machine breaks down, we will ensure that an engineer is on site within 24 hours. If we can’t fix the issue during the first visit, we will ensure that a temporary loan machine is in site within 72 hours of the initial call ensuring that cleaning can continue whilst your machine is repaired. We also offer ICE SMARTcall, a technical support service that allows the operatives to have a live video call via the ICE App, to enable us to diagnose and fix remotely where possible.
Designing robotic floor cleaners to work in conjunction with humans is crucial as human interaction will always be necessary. The collaboration between robots and humans delivers consistently high standards – the data available from the autonomous equipment quantifies and proves cleaning results whilst enhancing standards delivered by the cleaning operative who has more time to focus on detailed cleaning.
It is also a more flexible approach as robots can be programmed to perform specific tasks, but they cannot adapt to unexpected changes as well as humans can. Overall, designing floor cleaning robots that collaborate with humans is more efficient, flexible, and inclusive than designing robots that replace them. By working together, humans and robots can create a cleaner and safer environment for everyone.
It’s well documented that deploying autonomous cleaning equipment increases productivity, enhances cleaning standards and delivers consistent cleaning results. A return on investment of up to 30% can also be expected when introducing robotic machines.
Using autonomous cleaning equipment also demonstrates real commitment to your Environmental, Social and Governance (ESG) strategy and goals – something we should all take extremely seriously.
Switching from traditional manual cleaning machines to autonomous equipment not only saves up to 1,628 hours of cleaning time per year, the on-board water recycling function means it can also save up to 139,412 litres of water annually compared to a traditional scrubber dryer. That’s equivalent to almost 1,000 baths!
Additionally, having the machine operating autonomously reduces the likelihood of operator damage, which reduces carbon footprint relating to engineer visits. The machines can also be managed remotely which further reduces the need for engineers to visit site.
Whilst infrastructure changes are not required when introducing automated cleaning, cultural changes are essential. The challenge is how to change the culture so that cleaning operatives embrace the technology rather than fearing that it will replace them. The key to this is collaboration and this relies heavily on educating and involving the cleaning teams prior to deployment. This will help them welcome the change and understand that the machine can truly become part of the team, empowering the operatives to carry out other valuable tasks.
Robotic floor cleanears have developed significantly over the last few years – many are now self-charging, emptying, and re-filling, and are even able to integrate with lift technology which allows the machines to clean different floor levels without any human interaction.
This development is only expected to continue, with the commercial robotic floor cleaning market forecast to experience growth in the next few years, and it is constantly evolving with numerous new companies and robots entering the market.
With the increasing adoption of automation across the industry there is now a growing demand for smart cleaning solutions such as integrating the robotic machines with building management systems to provide real-time data on cleaning operations and efficient cleaning schedules.
Increased use of artificial intelligence (AI) to improve cleaning efficiency and accuracy is also likely to evolve. For example, training robots to identify and avoid specific types of obstacles, or to focus on cleaning areas with the heaviest foot traffic.