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IoT improves commercial laundry first by making equipment and processes visible as they run. Connected washers, dryers, sensors and management software can show cycle status, resource use, faults and maintenance conditions in one place. That visibility helps staff respond to problems earlier, direct technicians to a specific machine and adjust operations when measurements move outside acceptable limits.
The technology is not a guaranteed percentage saving. The documented examples are vendor product descriptions and case studies, so any business case should use a site-specific baseline for water, energy, throughput, service visits and downtime.
What an IoT-enabled laundry actually connects
A practical installation has three layers. The first is the equipment and sensing layer: washers, dryers, controls and added sensors produce information about cycles, faults and operating conditions. Depending on the machine and integration, measurements may include water, air, temperature, energy or tank levels.
The second is the communications layer. A wired connection, Wi-Fi or cellular gateway carries readings to a monitoring or management platform. The third is the action layer, where operators, managers or technicians view dashboards, receive alerts and change a process or schedule a service visit.
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| Layer | Typical information or function | Questions to verify |
|---|---|---|
| Machines and sensors | Cycle state, completion, faults, water, energy, air, temperature and other process readings | Which makes, models and control generations are supported? Are retrofit sensors required? |
| Network and gateway | Moves data from equipment to the platform; may use Wi-Fi, wired networking or cellular service | Is coverage reliable at every site? Who supplies, secures and supports the gateway? |
| Platform and workflows | Dashboards, alerts, maintenance records, remote status and, where supported, remote controls | Which users see data? Can alerts be configured? Can information connect to maintenance, payment or business systems? |
Where IoT delivers practical improvements
1. See every machine and cycle
A centralized view can show cycles in progress and completed, machine availability and maintenance information. DANUBE describes DANUBE ONLINE for on-premises laundries with views of cycles, water and energy consumption, maintenance data and remote access. Mission Laundry’s connectivity case describes customer notifications when a machine is available or a load has finished, alongside back-end access to machine status.
These features are deployment-specific. A platform may expose only the readings available from a particular machine, controller or retrofit sensor; “connected” does not mean every installation provides the same dashboard or controls.
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2. Target maintenance instead of checking everything manually
When a platform identifies a machine and its problem, a technician can arrive prepared for that particular fault rather than making a general inspection. WASHCO’s UK case with Vodafone and Onecom says sensor and recording-device data helped staff identify the right machine and problem, and reduced the need for routine maintenance checks. The company’s managing director, Peter Hosking, described the Vodafone platform as providing stable, secure communication between the washing machines and WASHCO’s portal.
This is targeted maintenance, not remote repair. A technician still has to inspect, isolate, clean, replace or test physical equipment when the fault requires hands-on work. The value is better information and dispatch decisions.
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3. Act on process deviations and threshold alerts
Industrial monitoring can alert staff when a measured value exceeds a chosen threshold. In an Initial laundry-services case, ifm describes its moneo software monitoring water, air and temperature and notifying personnel when limits are exceeded. Such an alert can prompt an investigation into a water-supply issue, tank level or process setting before the deviation affects more loads.
Alerts only create value when someone owns the response. Define who receives each notification, the response time, the escalation path and the evidence that the issue was resolved. Poorly chosen thresholds can create alert fatigue; overly broad thresholds can hide a developing problem.
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4. Measure water and energy use
Resource data supports comparisons between machines, shifts, programs and sites. DANUBE describes water and energy consumption in its laundry-management view. Wientjens describes an IoT-enabled installation at Oxwash with real-time information on water and energy use, system performance and predictive-maintenance information. Its reported water-use figure applies to that operation and is not a commercial-laundry industry benchmark; Oxwash was acquired by Elis at the end of 2025.
Use the measurements to establish a baseline before changing settings. Compare equivalent loads and programs, account for production volume and record whether a reading comes directly from a meter, a machine controller or an estimate.
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5. Support distributed sites and customer-facing services
Cellular connectivity can be useful where Wi-Fi is unreliable or where equipment is spread across locations. Hongdian describes a multi-region laundry operator using industrial cellular routers for this reason and reports more than 30,000 connected washing machines in that operator’s deployment. That figure is a vendor case-study claim, not an industry total or an independently audited count.
Mission Laundry’s case illustrates another use: machine-availability and load-finished notifications can improve the customer experience in a self-service setting. The specific functions depend on the service, network and machine interfaces.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the documented deployments show—and what they do not
- WASHCO’s implementation is reported as capable of powering up to 20 machines simultaneously. Treat that as a feature of that deployment, not a general capacity specification.
- Initial’s ifm case describes an operation processing about 10,000 to 11,000 garments per day. That is the scale of the named operation, not a typical or required IoT-laundry volume.
- Vendor examples report capabilities and experiences, but they do not provide a comparable independent percentage reduction in water, energy, cost, breakdowns or downtime across commercial laundry.
- Predictive-maintenance labels do not guarantee that every failure will be predicted or prevented. Sensor coverage, data quality, equipment age and staff response determine the result.
How to plan a connected-laundry project
- Record a baseline. Gather several weeks or months of water, energy, loads, cycle times, service visits, faults and downtime by machine or site.
- Map the equipment. List make, model, control generation, location, available interfaces and any existing meters or payment systems.
- Choose the measurements that matter. Start with the decisions you need to make—such as dispatching a technician or investigating excess water use—rather than collecting every possible signal.
- Confirm connectivity at each location. Test Wi-Fi, wired and cellular options. For an industrial cellular IoT router, verify carrier coverage and bands, electrical and environmental requirements, machine integration and whether a managed gateway is required.
- Define ownership and access. Specify who receives alerts, who can view customer data, who performs updates and who supports the network and platform.
- Pilot a representative group. Include different machine models, a difficult-to-cover area and a normal production period. Check data completeness, false alerts and technician workflow before expanding.
- Measure the result against the baseline. Compare like-for-like production and report changes in resource use, response time, service visits and downtime. Separate one-time installation costs from recurring connectivity, platform and support costs.
Questions to ask suppliers
- Which machine makes, models and control generations are supported, and which require retrofit hardware?
- Are cycle status, faults, water, energy, temperature and other process variables available individually or only in a combined status?
- Can alerts be configured by machine, value, time and recipient? Is there an audit trail of acknowledgement and resolution?
- What can be controlled remotely, and which tasks always require a person on site?
- How are data access, retention, security, software updates and account termination handled?
- Can the platform exchange information with maintenance, payment, scheduling or business-management systems?
- What are the separate hardware, installation, connectivity, platform and service charges?
Bottom line for commercial-laundry operators
IoT is most useful when it turns an invisible operating condition into a specific decision: dispatch this technician to this machine, investigate this water threshold, or tell a customer that this load is complete. Start with reliable status and resource visibility, design connectivity around the actual site, and judge savings only from measured before-and-after performance. The available evidence supports these workflows, not a universal return-on-investment promise.
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