RTLS brings the user identification required to develop user-centric proactive and learning home appliances and services.
RTLS ENABLES THE FUTURE HOME
Let's Partner Up!
Intellithings could be just the accessory for getting our “smart homes” to do exactly what we want them to do in any given room, at any given time.
Julie Jacobson - CEPro Founding Editor
INTELLIGENT USER-CENTRIC
PROACTIVE OPERATION
Smart home market reports show that most smart home users want appliances and services to become much more autonomous and do it on their own.
Our real time location systems are the first to bring room-level user identification to the home, enabling home appliances to identify who's using them, learn users' personal preferences and proactively adjust.
-
Proactive personalization of light, temperature, music and other appliance-specific personal preferences such as coffee machine program.
-
Automatic privacy control for surveillance cameras.
-
Automatic user profile selection for video and audio streaming services.
-
Automatic parental control profile setting based on who's in the room.
ENHANCED
SAFETY & ENERGY SAVING
Our RTLS systems enable appliances to identify when no users are in the room, to automatically enter energy saving mode or alert about safety risks, such as when stoves or ovens are left working while no users are in the room.
USER-CENTRIC
PERSONAL EMERGENCY DETECTION
RTLS enables personal emergency detection services to monitor user-specific presence behavior to identify potential personal emergencies.
-
Intelligent detection of possible fall or health events by monitoring specific people's home presence activity to determine anomalies.
-
Child-specific home return verification during expected hours, by room-level presence activity.
Detection Speed
SLOW
Depends on users to start talking + analysis time
SLOW
Depends on camera ability to clearly catch users' face + analysis time
FAST
Immediately as users enter the room
Requires Cloud Analysis
YES
NO
MOSTLY YES
Some solutions claim for local detection
Requires Learning
NO
YES
Needs to learn users' voice
YES
Needs to learn users' faces
Multiple Concurrent Users Detection Probability
LOW
Detects users clearly talking alone
LOW
Detects users clearly showing their face to the camera
HIGH
Detects all users with registered wearables
User Privacy
Low
Low
HIGH
Voice
Video
Wearables-Based RTLS
Home User Identification Methods
COMPETITIVE BENCHMARK