NEWS

US researchers obtain patent for distributed network of LED lighting to produce height map

Release time:

2016-09-29 15:54

Researchers at the Center for Lighting Systems and Applications (LESA) at Rensselaer Polytechnic Institute (RensselaerPolytechnicInstitute) recently received a U.S. patent (No. 9,363,859) entitled "Sensing Lighting Systems and Methods for Characterizing Lighting Spaces.

The researchers' idea is to use a distributed network of LED lighting and low-cost Time-of-Flight (ToF) sensors to generate a height map (elevationmap) lit by lamps for a specific space.

Each light source is encoded to emit light via a predetermined modulation pattern, and the nearest set of ToF sensors can detect scattered light (light bouncing off objects or people in the room); the ToF sensors can determine the height of the object below its corresponding lighting unit.

On the other hand, the spatial characterization unit receives the distance recorded by each set of sensors/luminaires and generates a height map that can be used for comparison with a reference map, such as an empty office.

The technology can also be installed on existing LED infrastructure, and in the future, ToF sensors can also be integrated into LED-based lighting fixtures to achieve real-time state-of-use detection (occupancyDetection) and automatic lighting at a lower cost than existing detection technologies.

Since the ToF sensor only detects the pattern of light, the privacy of the occupants can be maintained. Accurate spatial mapping will help determine the location as well as the height (objects in the room as well as individuals are sitting or standing), while monitoring any changes with motion detection.

To further develop and validate the new technology, LESA built two prototype testbeds, a "smart meeting room" (SmartConferenceRoom) managed by Rensselaer Polytechnic Institute and a "smart medical room" (SmartHospitalRoom) at the University of New Mexico (UniversityofNewMexico). Both test platforms use only the characteristics of the light source itself, and strive to make LED lighting reach a new level of data generation and control in a more cost-effective manner.

Ultimately, LESA expects to incorporate not only ToF sensors, but also other low-cost sensing technologies, control software and machine learning in future indoor luminaires.