RTLS brings the user identification required to develop user-centric proactive and learning home appliances and services.

RTLS ENABLES THE FUTURE HOME

DISTRIBUTORS

RESELLERS

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MANUFACTURERS DEVELOPERS

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.

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  • Automatic privacy control for surveillance cameras.

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  • Automatic user profile selection for video and audio streaming services.

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  • 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.

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  • 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