Patent Description:
Many environments, such as buildings, comprise a large grid of luminaires which are distributed in the environment to ensure that every place in the environment can be illuminated adequately, e.g. every room in the building.

It is known to additionally arrange various types of sensors, e.g. motion sensors or noise sensors, in such an environment to collect environmental information, e.g. information about the presence or distribution of people in the environment. This information can be used to control the luminaire grid.

However, it is difficult and costly to distribute, network and power a sufficient number of different environmental sensors in parallel to the luminaire grid.

The document <CIT> discloses a luminaire network comprising a plurality of luminaires as well as a central unit, and comprising a central communication unit. A plurality of the luminaires in the luminaire network further comprise at least one sensor which can sense information relating to the environment of the luminaire. The document <CIT> discloses a system combining obtained real-time sound data, obtained real-time environmental data, and topographical information about an environment to create a propagation map of the sound data.

In addition, many environments, especially offices, comprise rooms in which many people are present at the same time. This can lead to problems with the confidentiality of conversations that might be overheard easily. Especially in open office environments or shared desks, the location of coworkers can change dynamically, which makes it difficult to ensure that confidential information is not shared accidentally. Further, the ambient noise in such an environment, especially human chatter, can cause a distraction.

It is known to use noise dampening or sound masking, for instance by means of white noise sources, to reduce the comprehensibility of sounds in an environment. However, the efficiency of such systems is often not monitored, especially not regularly. Further, the specific type of noises that should be masked, e.g. human chatter, is often not taken into consideration.

Thus, it is an objective of the invention to provide an improved grid comprising at least one luminaire, an improved system comprising said grid and an improved method for operating a grid of at least one luminaire, which avoid the above-mentioned disadvantages. In particular, it is an objective to assess the distribution and range of specific sounds in an environment.

According to a first aspect, the invention relates to a system comprising a grid, a data processing unit and a database,wherein the grid comprises a plurality of luminaires, wherein each luminaire in the plurality of luminaires comprises one or more acoustic sensors and preferably other sensors;wherein the grid further comprises a controller supplied with the output signals of said sensors, wherein the controller is arranged for discriminating different sound categories in the output signals, including human voice sound, and to issue a sensor information signal representing at least the sound category,wherein the sensor information signal is stored in the database,wherein the data processing unit is configured to analyze the database for evaluating correlations between sensor information signals of sensors of different categories and/or different luminaires, and wherein the data processing unit is further configured to generate a sound map depicting a propagation of sound in an environment of the grid based on the sensor information signals stored in the database.

This achieves the advantage that environmental information, in particular information on a type or category of ambient noise in the environment, can be collected efficiently. This information can be used to assess a distribution and range of sounds in the environment.

Integrating the sensors in the luminaires of the grid leads to a cost reduction, because components such as housing, communication means and/or power sources can be shared between the luminaires and the sensors.

In an embodiment, the sensor information signal further comprises a timestamp.

This achieves the advantage that a detected sound category can be linked to a certain time.

In this way, for instance, it can be detected during which hours human chatter occurs in the environment. This information can be forwarded by the controller by means of the sensor information signal.

In an embodiment, the sensor information signal further comprises a probability value for the sound category, an overall sound pressure and/or presence data provided by a motion sensor of the at least one luminaire.

This achieves the advantage that a certainty or uncertainty of the assessment of the sound category is known.

In an embodiment, the sensor information signal comprises a luminaire identifier (ID).

This achieves the advantage that the detected sound category and can be linked to the place in the environment at which the luminaire is installed. This information can be used to generate a sound map of the environment.

In embodiment, the sound categories further comprise one or more of: crowd chatter, white noise, machine noise, music, street noise, traffic noise, sudden/burst noise, or broadband non-white noise.

This achieves the advantage that the ambient sound can be classified efficiently according to its origin.

In an embodiment, the controller is arranged for forwarding the sensor information signal repetitively with a constant or a varying, especially adaptive, frequency.

This achieves the advantage that a temporal development of the presence and category of the ambient sound can be detected. In this way, for instance, it can be detected how the ambient noise changes over the day.

In particular, the controller is arranged to forward updated sensor information signals based on current output signals of the sensors with constant or varying frequency.

The system according to the first aspect achieves the advantage that environmental information, in particular information on a type or category of ambient noise in the environment, can be collected, forwarded and processed efficiently.

The system can further comprise a gateway configured to forward the sensor information signal to the database and/or the processing unit.

In an embodiment, the database can be analyzed, in particular by the data processing unit, for evaluating the time development of one or more sensor information signals.

This achieves the advantage that a temporal development of the presence and category of the ambient sound at different places in the environment can be determined.

In this way, for instance, it can be determined how the ambient noise in the environment of the grid changes over the day.

Preferably, the database is adapted for being analyzed by the data processing unit for evaluating the time development of one or more sensor information signals.

In an embodiment, a location of the at least one luminaire of the grid can be determined based on the evaluation of the time development of the one or more sensor information signals.

Preferably, the data processing unit is configured to determined the location of the at least one luminaire of the grid.

The database is analyzed, in particular by the data processing unit, for evaluating correlations between sensor information signals of sensors of different categories and/or different luminaires.

This achieves the advantage that the system has a high robustness, e.g. faulty sensor signals can be detected via comparison with signals from other sensors. In addition, this sensor fusion, i.e. the combination of different types of sensor signals from different sensors, allows determining additional information about the environment with low uncertainty.

The data processing unit is configured to generate a sound map depicting a propagation and optionally further depicting a range of sound in an environment of the grid based on the sensor information signals stored in the database, preferably based on a k-nearest neighbor algorithm.

This achieves the advantage that the collected sensor information signals and information determined based on said signals can be visualized for a user.

In a further embodiment not covered by the scope of the claims, the data processing unit is configured to apply a correlation algorithm on a time series of sensor information signals from different locations of the grid, in particular on sensor information signals from different luminaires of the grid. Preferably the data processing unit is configured to generate the sound map based on a results of applying the correlation algorithm on the time series.

Preferably, applying the correlation algorithm comprises applying a correlation function, such as the Pearson Product-Moment Correlation coefficient, in a matrix form. Preferably, a k-nearest neighbors or similar algorithm is used for calculating this correlation matrix. Furthermore, a moving average, smoothing and/or low pass filter can be applied to a time series progression of matrix elements of the correlation matrix.

In an embodiment, the data processing unit is configured to determine disturbance and/or privacy parameter for different locations in the environment, in particular based on the sound categories in the sensor information signals, and to include the disturbance and/or privacy parameter in the sound map.

This achieves the advantage that information on disturbance and/or privacy in the environment can be visualized efficiently.

In an embodiment, the data processing unit is configured to generate alerts based on the disturbance and/or privacy parameters, in particular based on changes of the disturbance and/or privacy parameters.

This achieves the advantage that information on disturbance and/or privacy in the environment can be used efficiently.

According to a second aspect, the invention relates to a method for operating a grid comprising a plurality of luminaires, wherein each luminaire in the plurality of luminaires comprises one or more acoustic sensors and preferably other sensors; the method comprising the steps of:.

The above description with regard to the system according to the first aspect of the invention is correspondingly valid for the method according to the second aspect of the invention.

<FIG> shows a schematic diagram of a luminaire <NUM> according to an example.

The luminaire <NUM> comprises a one or more acoustic sensors <NUM> and preferably further sensors <NUM>, <NUM>. The luminaire <NUM> further comprises a controller <NUM> supplied with the output signals of said sensors <NUM>, <NUM>, <NUM>, wherein the controller <NUM> is arranged for discriminating different sound categories in the output signals, including human voice sound, and to issue a sensor information signal representing at least the sound category.

The luminaire <NUM> is comprised in a grid, as for instance shown in <FIG>. The grid comprises a plurality of the luminaires <NUM>.

Preferably, the luminaire comprises a light sensor <NUM>, in particular a daylight sensor, and a motion sensor <NUM> in addition to the acoustic sensor <NUM>.

The acoustic sensor <NUM> of the luminaire <NUM> can comprise a noise detector, in particular a microphone. For example, the acoustic sensor <NUM> is configured to detect a noise pressure level and/or noise patterns such as voice or burst sounds.

The motion sensor <NUM> can be a presence sensor. In particular, the motion sensor <NUM> is a Doppler based motion sensor, i.e. a sensor that detects motion based on the Doppler Effect.

The daylight sensor <NUM> can be configured to detect a natural light intensity, e.g. of daylight.

In particular, the sensors <NUM>, <NUM>, <NUM>, in particular the acoustic sensor, can be of low technical complexity and, therefore, cheap.

The controller <NUM> can be a micro controller unit (MCU).

In particular, the luminaire <NUM> further comprises a wireless interface <NUM> configured to forward the sensor information signal, for instance to a gateway. The wireless interface <NUM> can be a Bluetooth interface and can be configured to forward the sensor information signal using the Bluetooth standard.

Preferably, the sensor information signal comprises a timestamp and/or a luminaire identifier (ID). Via the timestamp and the identifier, the sound category can be correlated to a place and time in the environment.

For example, the controller <NUM> is configured to forward a new sensor information signal every few milliseconds or at least every few seconds.

In particular, the sensor information signal comprises a set of sound categories or features that provide a fingerprint of the location of the luminaire <NUM> and a human presence probability.

In this way, a 2D sound map of the environment can be generated based on data forwarded to the central database. For instance, the 2D sound map shows noise levels, in particular volume and/or intensity, or noise categories in the environment at different times during the day. The 2D sound map can further show an overall sound pressure in the environment and/or the presence or presence probability of people, for instance determined based on the output signal of the motion sensor <NUM>.

Preferably, the audio data is processed in the luminaire, in particular by the controller <NUM>. Especially, no direct voice recordings are forwarded by the luminaire due to hardware restrictions in the luminaire. Thus, the privacy of people in the environment is respected and no audio recordings are stored.

Preferably, the acoustic sensor <NUM>, in particular the microphone, is connected to the controller <NUM> for processing the sound, and the controller <NUM> is connected to a wireless interface <NUM> via the UART (Universal Asynchronous Receiver Transmitter) protocol, wherein the wireless interface <NUM> can be a low bandwidth radio interface.

In an embodiment, the controller <NUM> is arranged for forwarding the sensor information signal repetitively with a constant or a varying, especially adaptive, frequency. In particular, every new sensor information signal is based on a current output signal of said sensors <NUM>, <NUM>, <NUM>.

The sound categories can comprise one or more of: human voice (single or few), crowd chatter, white noise, machine noise, music, street noise, traffic noise sudden/burst noise, and/or broadband non-white noise. Preferably, the sensor information signal further comprises a probability value for each sound category, an overall sound pressure and/or presence data provided by a motion sensor of the at least one luminaire.

Preferably, the controller <NUM> is executing an interference model based on a recursive or a convolutional neural network in order to discriminate and assign the sound categories.

Preferably, the luminaire <NUM> further comprises a light source <NUM>. In the exemplary embodiment of <FIG>, the light source <NUM> comprises an LED array with a plurality of individual LEDs L1,. For instance, the LED array comprises <NUM> LEDs providing a total illumination of <NUM> lm.

Preferably, the sensors <NUM>, <NUM>, <NUM> and the controller <NUM> are arranged within a housing (not shown) of the luminaire <NUM>, e.g. below a diffusing plate. In this way, the sensors are not protruding the visible interface and do not disturb the appearance of the luminaire <NUM>.

The luminaire <NUM>, as shown in <FIG>, may further comprises a circuit board <NUM>, e.g. a PCT board. The sensors <NUM>, <NUM>, <NUM> and the controller <NUM> can be integrated in the circuit board. Preferably, also the light source <NUM> and the wireless interface <NUM> is integrated in the circuit board.

The luminaire <NUM> can further comprise a power supply <NUM>, in particular a low voltage power supply (LVPS), which is arranged to provide a power supply to the light source <NUM>, the sensors <NUM>, <NUM>, <NUM>, the controller <NUM> and/or the wireless interface <NUM>.

The luminaire <NUM> in the exemplary embodiment of <FIG> further comprises a driver <NUM>, in particular a driver on board (DOB) for the light source <NUM>.

The luminaire <NUM> can comprise a downlight, an area light or a linear light.

In particular, the wireless interface <NUM>, the housing, the power supply <NUM>, the driver <NUM>, the circuit board <NUM> and/or at least one of the light sensor <NUM> or motion sensor <NUM> are optional features of the luminaire <NUM>.

In particular, the luminaire <NUM> shown in <FIG> is an exemplary luminaire 101a-b of the grid <NUM>, as for example shown in <FIG>.

The luminaire <NUM> comprises the light sensor <NUM>, the motion sensor <NUM>, e.g. in form of a <NUM> radar sensor, and the acoustic sensor <NUM>, e.g. in form of a digital sound sensor.

The luminaire <NUM> can further comprises a temperature sensor <NUM> and a power measurement unit <NUM>, e.g. for measuring a power consumption by the luminaire <NUM>.

Furthermore, the luminaire <NUM> can comprises a vibration sensor (not shown), e.g. for detecting vibrations in the ceiling.

Preferably, the sensors <NUM>, <NUM>, <NUM>, <NUM> and <NUM> are configured to forward sensor values to the controller <NUM>. In <FIG>, the controller comprises a CPU.

The sensor values can comprise amplitudes of detected signals, for instance, a brightness value detected by the light sensor <NUM> or a velocity of a movement detected by the motion sensor.

The luminaire <NUM>, as shown in <FIG>, comprises a dimmable LED driver <NUM> connected to the light source <NUM>, wherein the light source <NUM> comprises LEDs. The controller <NUM> can be configured to control a dim level of the light source <NUM>. The controller <NUM> can further be configured to receive information on a voltage or current consumption of the LEDs.

The wireless interface <NUM> can be configured to communicate with the controller <NUM> via the USART (Universal Synchronous/Asynchronous Receiver Transmitter) protocol.

The wireless interface <NUM> can be integrated in the luminaire <NUM> as a system on a chip (SoC).

The luminaire can further comprise a surge/burst protection unit <NUM>.

<FIG> shows a schematic diagram of a grid <NUM> comprising multiples luminaires 101a-d according to an example.

For example, each of the at least one luminaires 101a-d of the grid <NUM> in <FIG> corresponds to a luminaire <NUM> as shown in <FIG>.

Each of the luminaires 101a-d in the grid <NUM> comprises one or more acoustic sensors <NUM> and preferably other sensors, such as the light sensor <NUM>, preferably the daylight sensor or motion sensor <NUM>. Each luminaire 101a-d further comprises the controller <NUM>.

The controller <NUM> is supplied with the output signals of said sensors <NUM>, <NUM>, <NUM>, wherein the controller <NUM> is arranged for discriminating different sound categories in the output signals, including human voice sound, and to issue a sensor information signal representing at least the sound category.

Each luminaire 101a-d can further comprise the wireless interface <NUM> for a communication between the controller <NUM> and a gateway for forwarding sensor information signals to a central database (not shown).

Preferably, each luminaire 101a-d in the grid <NUM> comprises a light source <NUM>, in particular a plurality of LEDs.

Each of the luminaires 101a-d can be a downlight luminaire, a standing luminaire or an area light. In particular, the grid <NUM> comprises different types of luminaires at different locations in the environment.

The grid <NUM> can be arranged in an environment, in particular a building. Since luminaires 101a-d are typically evenly distributed over such an environment, equipping each luminaire 101a-d with sensors <NUM>, <NUM>, <NUM> leads to a good coverage of the environment with the sensors. Equipping luminaires with sensors has the additional advantage that no extra planning or commissioning for mounting external sensors in the environment has to be done.

The grid <NUM> comprises multiple luminaires 101a-d equipped with the same type and number of sensors. Alternatively, luminaires 101a-d of one grid <NUM> may comprise different sensors.

The distribution and propagation of ambient sound in the environment is determined based on the sensor information signals from the luminaires 101a-d of the grid <NUM>. Each luminaire 101a-d, in particular the controller <NUM> of each luminaire 101a-d, can be configured to evaluate the ratio of human voices versus other sound patterns, such as crowd chatter, white noise, machine noise etc., in the vicinity of each luminaire 101a-d. Further, each luminaires 101a-d can be configured to determine an overall sound pressure and the presence around the voice sources in its vicinity, e.g. based on the readings of radar presence sensors in the luminaires 101a-d. This information can be forwarded by means of the sensor information signals, e.g. to a central database, and can be used to generate a sound map of the environment.

Based on the information forwarded by the luminaires 101a-d, a privacy estimate in different locations of the environment can be evaluated. In particular, the following factors can thereby be taken into account: spread of noise, ratio of human voice to other patterns (e.g. chatter, white noise machine noise, music etc.), overall sound pressure, and presence around the voice sources. The evaluation results can be mapped over the locations of the luminaires 101a-d. The map can show voice probabilities, voice fingerprints, voice to white noise ratios and/or noise levels across the environment. The map can further show the location of people in the environment, e.g. based on the radar presence sensor readings. In this way, the spread and range of sounds and, thus, of information from sources to other locations in the environment can be determined and mapped.

Further, a quality assessment of locations in the environment can be performed. Thereby, an estimate of distraction by noise at different locations in the environment can be evaluated based on the following factors: noise level, probability of human voice, fingerprint of other noise sources (e.g. traffic noise, music etc.), and human presence. The evaluation results can again be mapped over the locations of the luminaires 101a-d. The map can show voice probabilities, noise fingerprints, voice to white noise ratios and/or noise levels across the environment. The map can further show the location of people in the environment.

The above mentioned evaluation results can be mapped over the luminaire grid <NUM>. Thereby, noise sources can be determined as the locations in the environment where a sound with the highest intensity of one or several categories (e.g. voice) is detected, either at a certain time (snapshot) or over a time series.

In particular, the sound map can be generated based on a k-nearest neighbor algorithm or a similar method. The map can be alert generated if a threshold sound value is detected, or by a control of a white noise generator or other sound masking device.

<FIG> shows a schematic diagram of a system <NUM> comprising a grid <NUM>, wherein the grid <NUM> of multiples luminaires 101a-d according to an embodiment.

For example, the grid <NUM> of the system <NUM> shown in <FIG> corresponds to a grid <NUM> as shown in <FIG>.

The system <NUM> further comprises the wireless gateway <NUM> and the database <NUM>, wherein the sensor information signal <NUM> from the at least one luminaire 101a-d is stored in the database <NUM>. The system <NUM> can further comprise a data processing unit <NUM>.

Preferably, the wireless interface <NUM> of each one of the luminaires 101a-d in the grid <NUM> is configured to forwarding sensor information signals from the sensors <NUM>, <NUM>, <NUM> of the respective luminaire 101a-d to the wireless gateway <NUM>.

The wireless gateway <NUM> can be configured to forward the sensor information signals to the central database <NUM>. The wireless gateway <NUM> can be a communication device, such as a smartphone.

The central database <NUM> can be a memory of a data-processing device, e.g. a computer. Alternatively, the central database <NUM> can be a cloud storage.

Preferably, the central database <NUM>, in particular the sensor information signals stored in the central database <NUM>, can be analyzed for evaluating the time development of one or more sensor information signals.

Alternatively, the data processing unit <NUM> can be configured to receive the sensor information signals and to analyze the sensor information signals directly.

The analysis of the sensor information signals can be used for various application. For example, the system <NUM> can be a street lighting system. If people are detected via a certain sound category of the output signal of the acoustic sensor <NUM>, e.g. speech noise or steps, the system <NUM> can be configured to increase a brightness level of respective luminaires 101a-d. If an approaching vehicle is detected by the system <NUM>, e.g. by detecting the sound category "tire noise", pedestrians in the surrounding can be warned, e.g. by changing the street lighting or transmitting an information signal, for instance via Bluetooth.

The system <NUM>, in particular the data processing unit <NUM>, can further be configured to detect an emergency situation based on the sensor information signals. For instance, the system <NUM> can be configured to detect events such as a suspected burglary by detecting a sound of the category "shattering glass", or a medical emergency, by detecting a sound of the category "falling person". As a reaction, the system <NUM> can be configure to increase the brightness or transmit an alarm signal to other connected emergency alarm systems.

In particular, a location of the at least one luminaire 101a-d of the grid <NUM> can be determined based on the evaluation of the time development of the one or more sensor information signals <NUM>.

The central database <NUM> is analyzed for evaluating correlations between sensor information signals of sensors <NUM>, <NUM>, <NUM> of different categories and/or different luminaires.

The sound map described above is generated based on the analysis of the database <NUM>.

In particular, the data processing unit <NUM> is configured to generate a sound map depicting a propagation and optionally further depicting a range of sound in an environment of the grid <NUM> based on the sensor information signals stored in the database <NUM>.

The data processing unit <NUM> can be configured to generate the sound map at least partially based on a k-nearest neighbor algorithm.

Preferably, the data processing unit <NUM> is further configured to determine disturbance and/or privacy parameter for different locations in the environment, in particular based on the sound categories in the sensor information signals, and to include the disturbance and/or privacy parameter in the sound map.

The data processing unit <NUM> can be configured to generate alerts based on the disturbance and/or privacy parameters, in particular based on changes of the disturbance and/or privacy parameters.

<FIG> shows a schematic diagram of a method <NUM> for operating a grid <NUM> comprising multiple luminaires 101a-d. In particular, each luminaire 101a-d comprises one or more acoustic sensors <NUM> and preferably other sensors <NUM>, <NUM>.

The method <NUM> comprising the steps of:.

<FIG> shows a schematic diagram of a method <NUM> for operating a grid <NUM> of a plurality of luminaires 101a-d.

In particular, the grid <NUM> of the plurality of luminaires 101a-d of the methods <NUM>, <NUM> corresponds to the grid <NUM> as depicted in <FIG>.

Claim 1:
A system (<NUM>) comprising a grid (<NUM>), a data processing unit (<NUM>) and a database (<NUM>),
wherein the grid (<NUM>) comprises a plurality of luminaires (101a-d), wherein each luminaire in the plurality of luminaires (101a-d) comprises one or more acoustic sensors (<NUM>) and preferably other sensors (<NUM>, <NUM>);
wherein the grid further comprises a controller (<NUM>) supplied with the output signals of said sensors (<NUM>, <NUM>, <NUM>), wherein the controller (<NUM>) is arranged for discriminating different sound categories in the output signals, including human voice sound, and to issue a sensor information signal (<NUM>) representing at least the sound category,
wherein the sensor information signal (<NUM>) is stored in the database (<NUM>), the system being characterized in that the data processing unit (<NUM>) is configured to analyze the database for evaluating correlations between sensor information signals (<NUM>) of sensors (<NUM>, <NUM>, <NUM>) of different categories and/or different luminaires (101a-d), and wherein the data processing unit (<NUM>) is further configured to generate a sound map depicting a propagation of sound in an environment of the grid (<NUM>) based on the sensor information signals (<NUM>) stored in the database (<NUM>).