Intelligent Lighting Systems

Research Group

Signal Processing for Optical Wireless Communication

LEDs are rapidly replacing almost all kinds of conventional lighting. Besides illumination, LEDs can also can be used to transmit data. The reuse of the lighting infrastructure for communication is attractive because it can potentially delivery very high bit rates in well-defined areas. The latter is a key advantage because optical wireless system are less limited by mutual interference, thus Quality of Service and low latency van be guaranteed much better than for instance for WiFi. In our team, we aim at improving the performance of such systems. One aspect is the optimization of transmit signals for the specific LED channel. For instance, LEDs have non-linearity’s due to the internal transport mechanisms in semiconductor s that are not yet well handled in optical communication.

Signal Processing for Intelligent Lighting Systems

Lighting has a major impact on how we experience our environment. The insights in how Human Centric Lighting can improve our well-being, our sleep, our mood, our ability to focus or to enjoy social events are rapidly growing in the scientific world. In our team we try to use this insights in proving convenient and efficient automatic lighting control. For instance, in the Optilight project we track light exposure, human activities and psychological parameters to optimize light setting to achieve the best Image-Forming (alertness, ..) and non-image forming (circadian rythm) effects. We also optimize the signals of multiple sensors for this purpose. For instance, the combination of multiple unreliable sensors can nonetheless give sufficient information to substantially improve comfortable settings for the environment

The project aims to create a systems in which the existing lighting infrastructure is able to detect persons in a room, their light exposure, and determine each person’s circadian phase. This way such a system can determine the optimal lighting situation for a person independently.

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Anton Alexeev

PhD Student, TU/e

Charikleia Papatsimpa

PhD Student, TU/e

Jochem Bonarius

PhD Student, TU/e

Mahmoud Talebi

PhD Student, TU/e

Shokoufeh Mardanikorani

PhD Student, TU/e

Xiong Deng

PhD Student, TU/e

All members

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