Here's your cleaning crew, scrubbing an empty conference room at 3 PM while the lobby's packed with people tracking in mud. That's what happens when you follow fixed schedules instead of actual building use. Traditional cleaning routines waste time and money, they miss the spots that need attention and spend resources on spaces nobody's using. Building automation systems change that. They track real-time occupancy data, so you send crews where people actually go. You get cost savings in quieter areas and clear data on who's doing the job right. The shift's already paying off - AI-driven, demand-based cleaning cuts cleaning costs by 15-20% while keeping standards high. And the timing's right: the global building automation market's on track to hit USD 191.13 billion by 2030 with 13.4% annual growth. Let's break down how to roll out demand cleaning routes, add sensor data to your platforms, and use simple KPIs to measure the difference.
Demand-based cleaning sends your team only where there's actual use. Old schedules send cleaners to every conference room at 6 PM - even if they've been empty. Demand-based tasks only trigger when sensors show real activity.
This shift matters. Labor is expensive, and complaints pile up if busy spots aren't cleaned on time. If your restroom gets 200 visits by noon, don't wait until 3 PM to clean. One meeting in an executive suite? Skip daily vacuuming. Smart platforms use sensor counts and dispatch crews right where they're needed.
There's still basic service for low-traffic spots. But now, high-use areas get more attention. You avoid wasted effort and cut down on, “This wasn’t cleaned!” emails.
Occupancy sensors track how many people use a space. No cameras. No personal info. Just people counts, total visits, and dwell time. This shows which restrooms get hit hardest, which meeting rooms turn often, and where things stay quiet.
Layer occupancy data onto your cleaning routes and you spot patterns. Say your cafeteria averages 300 visits during lunch and just 50 in the afternoon - you can schedule a mid-day clean and skip later. If a lounge is packed most evenings, send in the crew then instead of the morning.
Dwell time tells you even more. Quick visits? Expect more surface contact. Long stays in a quiet room? Fewer touchpoints to worry about. Real behavior drives real cleaning. The benefits of occupancy sensors go beyond cleaning - they help with space planning and energy savings. But for custodial teams, the payback is instant.
All data's anonymous and privacy-friendly. You don't know who used the room - only that they did, and how much. That's all the info you need to get the job done right.
Your building automation system (BAS) connects HVAC, lighting, security, and now cleaning, all on one platform. Occupancy sensors stream counts through APIs right into your BAS, IWMS, or CMMS. If a conference room sits empty for two hours, the BAS dims the lights and lowers the thermostat. If it gets a rush - 15 visits in 90 minutes - it gets queued for cleaning immediately.
Integration is straightforward. Occuspace sensors work with HPE Aruba, so setup is fast and accuracy is strong (about 95%). Sensors send data to the cloud. The analytics engine sets the rules: "If visits go over 50 in four hours, create a high-priority cleaning task." The mobile app gets the task - with details and checklist. Once the cleaner finishes, the system logs the time and resets everything for next time.
This ties occupancy straight to building controls. Rooms without anyone in them don’t need full lights, cooling, or cleaning. Verified occupancy equals real savings - about $0.50 per square foot a year for energy. You can save another $0.50 to $0.75 per square foot by skipping unnecessary cleaning.
Your BAS is the control center. Sensors feed it data. It creates tasks and makes adjustments. Dashboards tell you which zones are busy now, which are idle, and which need attention. Facility managers get a live view - not yesterday’s guesswork.
First, set clear thresholds for every space. Maybe you clean restrooms after 100 visits. Break rooms might get a task after four hours of steady use. Lobbies get hit if foot traffic doubles the average.
Link these thresholds to task templates in your work order systems. Each template covers what room, which supplies, estimated time, and checklist. If a sensor passes the threshold, the task's assigned to the next available team member.
Mobile apps sort tasks by priority. High-traffic restrooms go to the top of the list. Low-use offices go lower. Cleaners log completion with a simple tap. Supervisors watch progress in real time and reassign as needed.
You can always add manual tasks. If there's a spill, dispatch an ad-hoc team. But most cleaning flows straight from occupancy data. You’ll cut down on radio calls, speed up response, and keep every zone covered.
Keep your space IDs in sync across the sensor network, BAS, and work order systems. Labels like "3F-CR-201" and "Conference Room 201" need to match. This keeps automation tight and tasks accurate.
Demand-based workflows track performance for you. You'll see how fast vendors respond, how often they finish tasks on time, and how complaint rates look by zone.
Key metrics:
Some places show "last cleaned" times on digital signs. It reassures people and keeps vendors accountable. Others track it internally and cover results in reviews.
You can also check cost per occupied hour. Just divide your total cleaning costs by the total hours spaces were occupied. If your building logged 10,000 occupied hours last month and cleaning cost $15,000, that’s $1.50 per occupied hour. Compare to the old way and see your savings clearly.
Focus on these KPIs:
Check these numbers weekly on your dashboard. Watch for more complaints or missed targets by zone. Adjust as needed. Every month, dive deeper. Compare costs, spot trends, and review highlights with your contractor.
Quarterly, reset your thresholds. If complaints stay low even with frequent triggers, raise the visit count. If a busy space isn't getting enough cleaning, lower the target.
Automate your reports. Set systems to email a dashboard every Monday and a summary on the first of each month. Make it visual - charts for occupancy, completion rates, and cost per hour. No more spending hours in spreadsheets.
Occupants care about privacy. Demand-based cleaning uses only anonymous, aggregated counts - never tracking individuals. Privacy-first sensors estimate people with no cameras, faces, or device IDs.
Be transparent about data. Store numbers for 90 days or less, unless you need long-term trends. Aggregate everything to zone level, never track who enters which room. Post simple privacy notices and signs where you use sensors.
Follow GDPR and similar rules: only collect what you need, protect it, and anonymize any booking or badge data if you blend them with occupancy counts.
Clear, up-front communication builds trust. When people know sensors help with cleaning, not watching, buy-in increases.
Start with restrooms, lobbies, and cafes. Busy spots generate the most feedback and show results fast. Install occupancy sensors, set a visit count (maybe 100 in busy restrooms, 50 in quieter places), and connect your work order system. Train your team with the mobile app and test everything for two weeks.
Watch your pilot. Track response, completion, and complaints. Adjust visit counts if too many or too few cleaning requests. Once it runs smoothly, expand floor by floor. Tailor rules to each space type.
Standardize your naming from day one - building code, floor, zone, room number. Keep this format across every platform. It prevents mix-ups and makes reporting simple.
Roll out in steps: one floor a week, one building a month. Fast systems like Occuspace can go live in days, but gradual rollout gives your team and vendors time to adjust and succeed.
Communicate with your occupants. Let them know cleaning is now smarter - high-traffic areas get more care, and privacy's respected. Ask for feedback, track comments with your KPIs, and keep people in the loop. Engagement smooths the transition and surfaces issues early.
It's when you send cleaning crews where the action is, using real-time occupancy. Sensors count visits and dwell time. Cleaning tasks trigger when needed - not just when the calendar says so. It cuts wasted work in empty areas and keeps busy spots fresh.
Occuspace sensors send data through a REST API - room ID, time, people count, total visits. Match sensor IDs with your space IDs in your management system. Set your platform to pull data every five minutes for real-time updates, or hourly for trends. Occuspace offers code samples and guides. Most teams are up and running fast.
Your management system (IWMS or CMMS) should send automatic reports: occupied hours, completion, and cost per hour. Schedule weekly summaries and monthly PDFs for reviews. Look for tools with easy filters so you can break down trends by zone or vendor. Occuspace dashboards give you live KPIs and simple exports—no manual number crunching needed.
Demand-based cleaning pays off. You’ll see 20-30% savings on custodial costs, about $0.50 per square foot on energy, and fewer complaints in high-traffic zones. Building automation links occupancy sensors straight to cleaning, environmental controls, and dashboards. You clean where people are, skip where they aren’t, and track every result.
Start with busy areas, then add more floors as you see impact. Occuspace data plugs right into your systems via a simple API. Privacy-first sensors keep data anonymous. The results come fast: lower labor costs, happier occupants, and more efficient buildings.
Occuspace brings you occupancy intelligence that fits your tech stack and goes live in days. It's all anonymous, with real-time dashboards and API exports to scale demand-based cleaning. Book a demo with Occuspace to see how you can cut custodial costs by 15-20% and boost comfort with smarter, data-driven cleaning routes.
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