Vilipa - Visible light based Person and Group Detection in existing buildings

Evaluation of the technical and economic feasibility of an occupancy detection system based on the technology of visible light sensing, which, in combination with the building management system, should reduce the energy consumption of buildings. The goal is to implement low-tech/low-complexity solutions that can distinguish between individuals and groups based solely on the detection of visible light reflections.

Short Description

Starting point/Motivation

In Europe, buildings are responsible for a significant proportion of primary energy use. Targeted control of building management systems, based on automatic detection of people in the building or in sub-areas of the building, can achieve energy savings of up to 40%. Currently implemented systems are based on different technologies and methods.

In most cases, the installation of these systems requires significant effort and some technologies are also problematic, raising legitimate privacy concerns. The high installation effort, especially in existing buildings, usually prevents realization of such systems due to economic concerns.

However, approaches based on existing infrastructure do not provide reliable results due to the main task being focused elsewhere. The recognition of persons based on the reflection of visible light caused by the persons themselves, known under the synonym "Visible Light Sensing", represents an innovative possibility to use the existing lighting infrastructure for person recognition without privacy concerns.

However, currently described systems neglect both the communication interfaces to be used and the aspect of networking several such innovative luminaires and the data to be obtained by a cooperation of these luminaires.

Contents and goals

The aim of the project is to examine the economic and technical feasibility of an approach for a network of luminaires that perform person recognition based on the technology of visible light sensing.

One of the main aspects is the differentiation of single persons and groups, as well as the detection of parameters such as walking speed of the persons and, if necessary, the detection of abnormal conditions by cooperation of the luminaires.

In order to make the planned system economically feasible for use in existing buildings, another focus of the project is to enable communication between the luminaires and with a higher-level system without the need for additional installation effort. Machine learning algorithms are to be used as a basis, both for the detection to be performed and for the classification.


Based on an iterative approach, laboratory samples of a luminaire consisting of LEDs as light sources and photosensitive elements as receiver units, which allow the detection of persons or groups of persons by measuring the intensity of the reflected light, will be designed.

These laboratory samples are subsequently integrated into a network of cooperating nodes and finally validated in a test bed using representative test scenarios. The following figure shows a schematic overview of the envisioned system.

Expected Results

The expected outcome of the project is the evaluation of a concept for a network of luminaires that determine, with a high success rate, the number of persons in a sub-area of a building. In addition, parameters such as the walking speed of the persons shall be determined.

The installation effort should be minimally small and therefore economically feasible. Likewise, a high modifiability of the system is aimed at, and an evaluation of the technical and economic advantages and disadvantages of the approach will be carried out.

Project Partners

Project management

  • Dr. Andreas Peter Weiss
  • Joanneum Research Forschungsgesellschaft.mbH

Project or cooperation partners

Graz University of Technology (TUG) - Institute of Microwave and Photonic Engineering (IHF)

Contact Address

JOANNEUM RESEARCH Forschungsgesellschaft mbH
MATERIALS - Institut für Oberflächentechnologien und Photonik Smart Connected Lighting
Dr. Andreas Peter Weiss
Industriestraße 6
A-7423 Pinkafeld
Tel.: +43 (316) 876-3605