Ambient Temp
18.5°C
OPTIMALTARGET: 18-20°C
Sleep Guard · AI Based · IoT Platform
Wireless, battery-powered sensors with AI based analysis that continuously track a room's sleep environment across the Sleep Grade dimensions — turning raw data into live scores, alerts, and operational insight.
Granular environmental monitoring engineered to optimize the 6 dimensions of the Sleep Grade algorithm in real time with advanced AI.
Polling rate
Configurable
18.5°C
OPTIMALTARGET: 18-20°C
45%
STABLEIDEAL: 40-50% · MOLD RISK: LOW
600ppm
FRESHTARGET < 800PPM · ALERT > 1000PPM
12µg
CLEANTARGET < 35µg
32dB
QUIETBASELINE < 30DB · FLAG SPIKES > 45DB
<1Lux
DARKTARGET < 1 LUX AT NIGHT
A device guests never notice, running on standards your engineering team already trusts.

No cabling, no renovation, no rooms taken offline for install.
Long range LoRaWAN network means no need for wi-fi.
Measures environment only — no cameras, no microphones, no audio recording.
Real-time scoring and threshold alerts transform complex environmental data into a simple, actionable overview.
Property status
RM 101
10.0
GOOD
RM 102
9.8
GOOD
RM 103
6.2
CRITICAL
RM 104
8.5
WARNING
Per-Room Sleep Grade Score
9.2
Ideal Range
Transform passive data into active orchestration. The Sleep Grade Sleep Guard platform automates the invisible tasks that guarantee a flawless guest environment for perfect sleep.
Rooms dynamically auto-group by status: Good, Warning, or Critical. Prioritize interventions based on live environmental drift.
Real-time updates track staff presence and task completion, ensuring no room is missed during critical turndown hours.
Alert-triggered dispatching. Auto-generated work orders for humidity spikes or temperature drift prevent long-term issues.
Flagging humidity spikes before stains appear or damage occurs, protecting your structural assets proactively.
Detecting mechanical degradation early by monitoring temperature drifts and unusual acoustic noise from HVAC systems.
Our sensors dictate exact fresh air requirements per occupied zone, eliminating blanket ventilation strategies and reducing waste.
Achieve savings up to ~20%. The AI learns thermal retention behavior of individual rooms, you can pre-conditioning spaces only when mathematically necessary.