System with acoustic sensor and method for real-time detection of weather data - Patents.com

Abstract

A system is provided, the system including one or more audio transducers, the one or more audio transducers including at least one audio sensor (110) configured to identify sound pressure information. Further, the system includes a processing unit (120) configured to determine meteorological information in response to the sound pressure information identified by the at least one audio sensor (110). The one or more audio transducers are configured to be installed in a mobile unit.

Description

[Technical field]

[0001] The present application relates to a system having an acoustic sensor and method for real-time detection of weather data, for example for integration into a robotic system or into an unmanned or manned aerial vehicle. [Background technology]

[0002] Weather forecasting is based on complex simulation models and relies on accurate measurement data. Against the background of climate change, the assessment of harsh weather conditions and their local impacts in the form of extreme weather is particularly important. However, due to the fixed distribution of weather stations, there is a lack of local meteorological information with high spatial and temporal resolution. Furthermore, some meteorological data are evaluated as averages over time and are not available in real time. Currently, there are no concepts that allow for an economical, resource-efficient and infrastructure-independent measurement of meteorological information. A comprehensive distribution of sensors is not economically feasible in terms of energy consumption, maintenance and upkeep.

[0003] Climate change is increasing the frequency and therefore the potential risk of extreme weather events, natural disasters and man-made environmental disasters. The manifestations are localized severe weather events, the intensity of which leads to the destruction of infrastructure and danger to life. Localized and high-resolution real-time meteorological data are of great relevance in order to initiate targeted measures as early as possible to protect the population and critical infrastructure. Summary of the Invention [Problem to be solved by the invention]

[0004] Compared to global standards, Germany already operates a very dense sensor network of precipitation radars and precipitation measuring devices, so-called rain gauges, but the accurate detection of local weather events remains a major challenge. The reason for this is the high spatiotemporal variability of these weather phenomena. Conventional measurements with rain gauges suffer from measurement errors such as wind, snow or evaporation. Although precipitation radars achieve sufficient spatial and temporal resolution, it is much more difficult to determine precipitation using radar reflectivity, since the droplet size distribution is usually unknown. Furthermore, such radar systems are hindered by shadowing effects or backscattering of the radar beam. Earlier research projects, such as the BNBF-funded "HoWa-innovativ" project [1], [3], have been carried out to address the poor spatiotemporal resolution. Here, conclusions about rainfall intensity could be drawn based on the signal attenuation between the radio relay antenna and the relay tower. However, this method also depends on the used radio network (CML), which currently roughly follows the population density. As a result, in sparsely populated areas the spatial resolution of precipitation monitoring is reduced. The problem here is the prevailing weather conditions that can cause impacts in populated areas, as well as a reduced level of security in rural areas. Furthermore, data processing has proven to be very complex and requires special wireless networks (see [2], [3], [4]).

[0005] Hydrophones are already used to measure precipitation in large bodies of water with depths of more than one meter. Based on a simple spectral analysis, the hydroacoustic signal caused by the impact of raindrops on the water surface is evaluated and then an estimate of the raindrop size is attempted (see [5]). Another method evaluated the noise caused by raindrops as a fixed trigger for exceeding a static threshold (see [7]). Both approaches have in common that they do not allow to draw intelligent conclusions about characteristic features. Moreover, both methods are location specific and therefore cannot be used flexibly.

[0006] In addition to precipitation, local winds in the atmospheric boundary layer, the so-called peplosphere, are an important factor in the occurrence of severe weather events. In the absence of meteorological data, measurement methods using drones are evaluated in the art (drone = unmanned aerial vehicle). Differential pressure sensors are therefore only suitable for drones like aircraft with constant forward flight and with wind incidence within a limited range of angles. On the other hand, conventional mechanical anemometers are limited to two-dimensional measurements and cannot be used due to their bulky design. Hot wire anemometers do not have these drawbacks. However, they are very fragile and prone to damage. These types of sensors are not suitable for general use in robotic systems or (unmanned) aerial vehicles.

[0007] The prior art describes configurations in which ultrasonic anemometers are mounted on multicopters (see [6], [8]). However, such configurations are very complex and can only be used to a limited extent. Moreover, this type of ultrasonic sensor does not allow a fully automated and adaptive assessment of the prevailing weather conditions. [Means for solving the problem]

[0008] A system according to claim 1, a method according to claim 36 and a computer program according to claim 37 are provided.

[0009] A system is provided, the system including one or more audio transducers, the one or more audio transducers including at least one audio sensor (e.g., a sound pressure sensor and / or a sound pressure gradient sensor) configured to identify (or determine or detect) sound pressure information (e.g., to identify a sound pressure and / or to identify a sound pressure gradient). Furthermore, the system includes a processing unit configured to determine (or identify or detect) weather information in response to the sound pressure information identified by the at least one audio sensor. The one or more audio transducers are configured to be installed in a mobile unit. Furthermore, a method is provided, the method comprising: - identifying sound pressure information by using at least one sound sensor; determining, by the processing unit, weather information as a function of the sound pressure information identified by the at least one sound sensor.

[0010] One or more audio transducers including at least one audio sensor are configured to be mounted to the mobile unit.

[0011] Furthermore, a computer program is provided having a program code for performing the above-mentioned method.

[0012] In one embodiment, the novel sensor system performs high-resolution spatiotemporal monitoring of localized or severe weather events in response to acoustic analysis.

[0013] Although weather conditions are often colloquially described by the sounds of their weather elements, acoustic sensors play no role in measuring weather phenomena. Weather data are typically measured at weather stations fixedly distributed across the country. Even when weather conditions are large-scale events, local effects are strongly characterized by location-dependent factors. High-resolution local data is lacking.

[0014] For more reliable weather forecasts, it is especially important to know the current characteristics of precipitation and wind. Acoustic sensors combined with tailored signal processing and AI have the potential to predict the intensity of multiple dominant weather elements based on their acoustic behavior. Due to the miniaturization potential of acoustic sensors, some embodiments are based on using such intelligent sensor systems in combination with robotic systems or (unmanned) aerial vehicles as high-resolution weather measurement systems. Such measurement systems can be independent of both location and infrastructure and can detect complex correlations in real time, which opens up completely new application possibilities.

[0015] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. [Brief description of the drawings]

[0016] [Figure 1] 1 illustrates a system according to one embodiment. [Diagram 2] 1 illustrates a system including a noise suppression module according to one embodiment. [Diagram 3] 1 illustrates a system according to one embodiment, in which the one or more audio transducers include at least one sound wave generator. [Figure 4] 1 illustrates a system according to an embodiment, further comprising a transmitting interface and a receiving interface. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] FIG. 1 illustrates a system according to one embodiment.

[0018] The system includes one or more audio transducers including at least one audio sensor 110 configured to identify sound pressure information.

[0019] Furthermore, the system includes a processing unit 120 configured to determine meteorological information in response to the sound pressure information identified by the at least one sound sensor 110 .

[0020] One or more audio transducers are configured to be mounted on the mobile unit.

[0021] For example, the sound sensor may be a sound pressure sensor and / or a sound pressure gradient sensor.

[0022] The identification of the sound pressure information may be, for example, an identification of the sound pressure and / or an identification of the sound pressure gradient (gradient of the sound pressure).

[0023] For example, the mobile unit may be a mobile unit.

[0024] For example, the mobile unit may be a vehicle such as an aircraft.

[0025] For example, the mobile or movable unit may be a motorized unit such as a (flying) drone, a motorized aircraft or a helicopter, but may also be a vehicle, for example, the mobile unit may be a non-motorized vehicle such as a hot air balloon or a glider.

[0026] However, the mobile unit may also be a wearable unit, such as a wearable module or suitcase, to which at least one or more sound sensors are fixed.

[0027] According to one embodiment, for example, at least one audio sensor 110 may be configured to discern sound pressure information at least in an inaudible sound frequency range and an audible sound frequency range, and / or at least one audio sensor 110 may be configured to discern sound pressure information at least in an audible sound frequency range and an ultrasonic frequency range.

[0028] In one embodiment, for example, the at least one sound sensor 110 may be configured to discern sound pressure information in the inaudible, audible and ultrasonic frequency ranges.

[0029] According to one embodiment, for example, the at least one sound sensor 110 may be configured to discern sound pressure information within a frequency range f, where 0≦f≦x, and 100 kHz≦x≦1 MHz.

[0030] In one embodiment, for example, the processing unit 120 may be configured to determine precipitation information and / or wind information and / or temperature information in response to sound pressure information identified by the at least one audio sensor 110 to determine weather information.

[0031] According to one embodiment, for example, the processing unit 120 may be configured to determine precipitation information in response to sound pressure information identified by the at least one audio sensor 110 to determine weather information. In this case, for example, the processing unit 120 may determine the precipitation information by using the following precipitation information: - Precipitation type, - Precipitation droplet size and / or particle size, - composition of precipitation, - kinetic energy of precipitation, - a direction of origin of precipitation.

[0032] In one embodiment, for example, the processing unit may be configured to determine at least the kinetic energy of the precipitation and / or at least the size of the raindrops of the precipitation to determine the precipitation information, where for example the processing unit 120 may be configured to determine an estimate of the cloud height and / or information about condensation nuclei and / or air particle pollution depending on the kinetic energy of the precipitation and / or depending on the size of the raindrops of the precipitation.

[0033] According to an embodiment, for example, the processing unit 120 for determining weather information may be configured to determine wind information, for example in response to sound pressure information identified by the at least one sound sensor 110. In this case, for example, the processing unit 120 may determine the wind information by using the following wind information: - horizontal and / or vertical speed of the wind, - one or more directional vectors of the wind, - wind type.

[0034] In one embodiment, for example, the processing unit 120 for determining weather information may be configured to determine temperature information, for example, in response to sound pressure information identified by the at least one sound sensor 110. In this case, for example, the processing unit 120 may be configured to determine an acoustic virtual temperature in order to determine the temperature information.

[0035] 2 illustrates a system according to an embodiment further including a noise suppression module 215 configured to apply a method for reducing noise to sound pressure information identified by the at least one sound sensor 110, for example to obtain one or more noise-suppressed sound signals. In this case, for example, the noise suppression module 215 may be configured to forward the noise suppression signals to the processing unit 120. Thus, for example, the processing unit 120 may be configured to determine weather information in response to the one or more noise suppression signals.

[0036] In one embodiment, for example, the noise suppression module 215 may be configured to apply one or more noise suppression filters to at least one received audio signal including a signal representation of sound pressure information identified by the at least one sound sensor 110 to determine one or more noise suppression signals.

[0037] According to one embodiment, for example, the processing unit 120 may be configured to determine weather information in response to sound pressure information identified by at least one audio sensor 110 by a machine training module trained by machine learning or deep learning.

[0038] FIG. 3 illustrates a system according to one embodiment that includes at least one sound wave generator 305 for generating sound waves for one or more audio transducers.

[0039] In a particular embodiment, the system of Figure 3 may further include the noise suppression module 215 of Figure 2. In another embodiment, the system of Figure 3 may be configured not to include the noise suppression module 215 of Figure 2.

[0040] According to one embodiment, for example, the at least one sound wave generator 305 may be configured to identify sound pressure information and / or the at least one sound sensor 110 may be configured to generate sound waves, for example.

[0041] In one embodiment, for example, at least one sound sensor 110 in the system may be arranged to receive sound pressure information in response to sound waves generated by the at least one sound wave generator 305. In this case, for example, the processing unit 120 may be configured to determine weather information in response to the sound pressure information dependent on the sound waves generated by the at least one sound wave generator 305 and identified by the at least one sound sensor 110.

[0042] According to an embodiment, the at least one audio sensor 110 may be a plurality of audio sensors forming a two-dimensional or three-dimensional array. In this case, for example, the processing unit 120 may be configured to determine direction-dependent information depending on the sound pressure information identified by the plurality of audio sensors and depending on the two-dimensional or three-dimensional array of the plurality of audio sensors. In this case, for example, the processing unit 120 may be configured to determine weather information depending on the direction information.

[0043] In one embodiment, for example, the processing unit 120 may be configured to determine the weather information as a function of the distance between the at least one sound wave generator 305 and the at least one audio sensor 110 .

[0044] According to an embodiment, the sound waves generated by the at least one sound wave generator 305 may be, for example, irradiated ultrasonic waves and / or irradiated inaudible sound waves and / or irradiated audible sound waves. In this case, the processing unit 120 may be configured to determine the wind speed and / or wind direction vector and / or acoustic fictive temperature and / or raindrop size and / or precipitation amount depending on the sound pressure information depending on the ultrasonic waves and / or inaudible sound waves and / or audible sound waves generated by the at least one sound wave generator 305.

[0045] According to one embodiment, for example, the processing unit 120 may process the following precipitation information to determine the wind speed, and / or to determine the wind direction vector, and / or to determine the acoustic virtual temperature, and / or to determine the raindrop size, and / or to determine the amount of precipitation: - Precipitation type, - Precipitation droplet size and / or particle size, - composition of precipitation, - kinetic energy of precipitation, - a direction of origin of precipitation.

[0046] In one embodiment, for example, the at least one processing unit 120 may be configured to determine an aeroacoustic characteristic of the airflow by sound pressure information identified by the at least one sound sensor 110, and to determine weather information according to the aeroacoustic characteristic.

[0047] According to one embodiment, for example, a system may include a housing in which a selectively directed air flow is caused.

[0048] In one embodiment, the one or more audio transducers may include at least one vibroacoustic sound receiver for identifying vibroacoustic sound waves, in which case the processing unit 120 may be configured to determine weather information in response to the vibroacoustic sound waves.

[0049] According to one embodiment, for example, the noise suppression module 215 of FIG. 2 may be configured to perform noise suppression in response to vibroacoustic sound waves identified by at least one vibroacoustic sound receiver.

[0050] For example, the processing unit 120 may be configured to determine information regarding precipitation in response to vibroacoustic sound waves.

[0051] According to one embodiment, for example, the processing unit 120 may be configured to recognize one or more acoustic events depending on the sound pressure information identified by the at least one sound sensor 110. Some acoustic events may be, for example, occurrences of a special type of sound. For example, special sounds may be recognized. The special sounds may be any type of sound, such as a human voice, an animal sound, a fire sound, etc.

[0052] In one embodiment, for example, the processing unit 120 may be configured to classify the sound pressure information identified by the at least one sound sensor 110.

[0053] According to one embodiment, for example, the processing unit 120 may be configured to recognize one or more acoustic events by a machine training unit trained by machine learning or by deep learning.

[0054] 4 illustrates a system according to an embodiment, further including a transmitting interface 412 and a receiving interface 418. For example, the transmitting interface 412 may be configured to obtain sound pressure information from the at least one sound sensor 110 and forward the sound pressure information to the receiving interface 418. For example, the receiving interface 418 may be configured to receive the sound pressure information from the transmitting interface 412 and forward the sound pressure information to the processing unit 120.

[0055] In particular embodiments, for example, the system of Figure 4 may further include the noise suppression module 215 of Figure 2. In other embodiments, the system of Figure 4 may be configured not to include the noise suppression module 215 of Figure 2.

[0056] According to one embodiment, the transmission of sound pressure information from the transmitting interface 412 to the receiving interface 418 may be performed, for example, in a wireless manner.

[0057] According to one embodiment, the transmission of sound pressure information from the transmitting interface 412 to the receiving interface 418 may be performed, for example, via wires.

[0058] According to one embodiment, for example, the system may include a mobile unit, in which case the at least one audio sensor 112 may be mounted, for example, on the mobile unit.

[0059] In one embodiment, for example, the system may include two or more mobile units including the mobile unit in question, in which case the at least one audio sensor 110 may be at least two audio sensors that may be mounted on different ones of the two or more mobile units.

[0060] According to one embodiment, the mobile unit may be, for example, an aircraft.

[0061] In one embodiment, the mobile unit may be, for example, a mobile robotic unit.

[0062] According to one embodiment, the mobile unit may be, for example, an airborne drone.

[0063] Specific embodiments of the present invention are described below.

[0064] In one embodiment, wind speed and / or direction is determined using a fixed, aircraft-mounted, or robotically-mounted acoustic sensor system.

[0065] According to one embodiment, additionally or alternatively, estimates of raindrop precipitation volume and size as well as further parameters are derived.

[0066] In one embodiment, in parallel and / or independently, the local environment is monitored for acoustic anomalies.

[0067] According to some embodiments, acoustic event recognition is provided.

[0068] In an embodiment, the prevailing weather event and / or its effects may be transmitted to population and emergency management, for example.

[0069] To achieve these objectives, embodiments provide a novel sensor system capable of discriminating between ultrasonic and / or audible frequency range (audible sounds) and / or inaudible sounds, which can be adapted to face the challenging conditions arising from use at fixed observation stations or mobile robot-supported or (unmanned) aerial-supported platforms.

[0070] In an embodiment, an acoustic sensor can have a suitable sensor design such that sensitive mechanical components are not required, as is the case with existing anemometer types. An acoustic sensor can eliminate the use of multiple sensors, thus allowing for a more compact and reduced maintenance construction.

[0071] In one embodiment, the measurement system combined with AI-based signal processing (AI: Artificial Intelligence) can recognize complex interactions of weather information from one or more signals. Thus, in one embodiment, for example, a local weather situation can be analyzed in detail and its direct impact on the surroundings can be monitored. For example, the water content of a river or an impending landslide can be recognized by the water absorption of the ground.

[0072] According to some embodiments, the use of, for example, robotic or aerial platforms may be provided, allowing flexible and rapid use of the system completely independent of the local network infrastructure.

[0073] In one embodiment, several carrier platforms can be used simultaneously, in this way, for example, a measurement network can be operated with dynamically adjustable spatiotemporal resolution in each field of view.

[0074] Based on the described multi-mode advances, there are great advantages for use in civil protection and disaster control. In particular, the presented advances may overcome practical shortcomings of conventional systems.

[0075] In an embodiment, one or more of the following parameters may be determined in detail by the novel acoustic sensor system:

[0076] Precipitation parameters: - Precipitation type / type (e.g., rain, snow, sleet, and hail), - Droplet or particle size of precipitation(s), - Precipitation, for example, the composition of the sleeve, - the kinetic energy of the precipitation. In one embodiment, the estimate of the cloud height and / or the conclusion regarding the condensation nuclei or the particulate contamination of the air is determined by: -Direction of precipitation origin Wind parameters: - horizontal and / or vertical wind speed, -wind direction vector(s), - Wind type / wind type (e.g. gusts, turbulence, etc.), It is determined according to a temperature parameter (eg virtual acoustic temperature, also called acoustic virtual temperature).

[0077] Subsequently, two particular embodiments of the sensor system are described, which can be considered alone or integrated into a composite sensor system, such a combination making it possible, for example, to detect detailed and additional meteorological parameters and correlations in real time.

[0078] First, the similarities between the two specific embodiments are described.

[0079] For example, in both embodiments, the acoustic sensor may comprise an electroacoustic sound transducer capable of detecting the largest possible frequency range from infrared to ultrasonic over audible sound. For example, the detection range may cover the range 0 Hz≦f≦x, where x may include values ​​of 100 kHz≦x≦1 MHz. For example, the detection range may cover 0 Hz≦f≦500 kHz.

[0080] In embodiments, for example, the sensor system of the invention may in both embodiments implement an adaptable method for reducing noise in order to prepare the acoustic signal for further signal processing. This allows the sensor system of the invention to be specifically adapted to the respective field of use. On the one hand, for example, information of the robot / air controller regarding the currently active actuator system of the carrier system can be detected, from which an acoustic filter can be derived and applied. On the other hand, meteorological measurement data of the acoustic sensor itself may be evaluated to generate or adapt the filter. A special arrangement of the sound transducers may, for example, cause selectively guided air flows, and noise filters can be derived by evaluating the air acoustic properties. For example, shielding of certain sound transducer components of the new sensor system may be used to reduce disturbances.

[0081] The interaction of meteorological elements and the mounting of sensor systems can generate vibroacoustic processes, which also apply to vibroacoustic effects from robots or flying systems. The resulting vibroacoustic events can be used to derive and apply acoustic filters to the acoustic signal of the audio receiver to reduce noise.

[0082] The first embodiment relates to an acoustic sensor system having an acoustic measurement path.

[0083] For example, the first embodiment may consist of a combination of an audio receiver and an audio source, or a two-dimensional or three-dimensional array of these audio transducers. In this way, a dynamically adaptive directional characteristic of the audio receiver can be achieved by digital signal processing. In a special embodiment, an audio source in the form of an electro-acoustic actuator can also function as an audio receiver and vice versa. Thus, the electro-acoustic audio transducer can be dynamically driven or used as an actuator or sensor depending on the situation.

[0084] In one embodiment, the wind is measured over one or more ultrasonic measurement paths, e.g. consisting of ultrasonic transmitters and opposing ultrasonic receivers at specified distances. These measurement paths form a corresponding ultrasonic array, e.g. in a two-dimensional or three-dimensional spatial orientation. By outputting signals, such as pulsed signals, sweeps, individual sinusoidal tones, and / or (pseudo)random sequences of signals, along the measurement paths, the wind speed as well as the wind direction vector are derived. Furthermore, a virtual acoustic temperature may be derived. For example, the use of multi-dimensional orientations may be used in parallel to validate the measurement data.

[0085] According to one embodiment, for example, wind is measured over one or more inaudible measurement paths consisting of inaudible transmitters at specified distances and inaudible receivers at the opposite ends. These measurement paths form a corresponding inaudible array, for example in a two-dimensional or three-dimensional spatial orientation. By outputting signals, such as pulsed signals, sweeps, individual sinusoidal tones, and / or (pseudo)random sequences of signals, along the measurement paths, wind speeds as well as wind direction vectors are derived. Furthermore, virtual acoustic temperatures may be derived. For example, the use of multi-dimensional orientations may be used in parallel to validate the measurement data.

[0086] In one embodiment, wind is measured over one or more audible measurement paths consisting of an audible transmitter at a specified distance and an audible receiver at the opposite side. These measurement paths form a corresponding inaudible array, for example in a two-dimensional or three-dimensional spatial orientation. By outputting signals such as pulsed signals, sweeps, individual sinusoidal tones, and / or (pseudo)random sequences of signals along the measurement paths, wind speed as well as wind direction vectors are derived. Furthermore, a virtual acoustic temperature may be derived. For example, the use of multi-dimensional orientations may be used in parallel to validate the measurement data.

[0087] According to further embodiments, a combination of two or three of the above three variants (ultrasonic, inaudible, audible) is provided.

[0088] To detect precipitation, the same ultrasonic and / or inaudible and / or audible transducers as for wind measurement may be used. The frequency of the emitted ultrasonic and / or inaudible and / or audible sound signals may be varied. The interaction of the raindrop size with the respective wavelengths of the ultrasonic and / or inaudible and / or audible sound waves creates scattering and attenuation effects. This may allow an estimation of the raindrop size and amount of precipitation. The variation in frequency may be used to detect the droplet size distribution more accurately.

[0089] The second embodiment relates to an acoustic sensor system without a dedicated measurement path.

[0090] The embodiment may be constructed, for example, with a single audio transceiver or with a two-dimensional or three-dimensional array. In this manner, dynamically adaptive directional characteristics of the audio transceiver may be achieved by digital signal processing. Further, for example, the embodiment may include a vibroacoustic audio receiver to detect vibrations in a robotic system or an aircraft.

[0091] To measure the wind, audio receivers for, for example, inaudible, audible, and ultrasonic waves may be used. Interaction of the wind with the airflow through special housings and / or placement of audio receivers may cause selectively guided airflows and / or aeroacoustic properties of the airflow may be detected or derived. By cascaded signal processing, information about prevailing winds such as wind speed and direction, as well as turbulence, may be detected and analyzed in this way.

[0092] In applications of the novel sensor system, precipitation impinges on the sensor housing and possibly also on nearby carrier system components. Signal analysis of the acoustic sensor components can be used to determine information about the precipitation, such as type and composition.

[0093] In addition to the measurement of meteorological parameters, the acoustic data of all audio receivers of both embodiments may be used for automatic acoustic recognition or detection of acoustic events. For this purpose, the sensor system may be equipped with, for example, machine learning and / or deep learning algorithms. In this way, it is possible to obtain further information on meteorological events and to recognize the occurrence of at least one monitored signal class. A possible application case may be the monitoring of the surroundings regarding the (direct) impact of meteorological events, in addition to the detection of human voices, animal noises or gas leaks. Thus, for example, the flow paths and / or dams and / or topography of rivers may be monitored for indications of landslides.

[0094] In embodiments, the processed sensor data may be provided by a wired and / or wireless interface. For example, in the absence of a connection, according to one embodiment, the data may be buffered / stored for later transmission. Furthermore, this data may be the starting point for an autonomous response of a robotic system or unmanned aerial vehicle.

[0095] Potential uses include for authorities and organizations with security tasks, as well as operators of measurement laboratories and critical infrastructure. Further potential applications include providers of vertical mobility solutions, as corresponding sensor systems are important for weather forecasting. The acoustic sensor system of the present invention can also be used in sensor combinations, such as in combination with a hazardous material sensor system.

[0096] While some aspects are described in the context of a device, it will be understood that the aspects also represent a description of a corresponding method, such that blocks or structural elements of a device should also be understood as corresponding method steps or features of method steps. Similarly, aspects described in the context of or as method steps also represent a description of corresponding blocks or details or features of a corresponding device. Some or all of the method steps may be performed using hardware devices such as microprocessors, programmable computers, or electronic circuits. In some embodiments, some or some of the most important method steps may be performed by such devices.

[0097] Depending on the specific implementation requirements, the embodiments of the present invention can be implemented in hardware or software. The implementation may be performed using a digital storage medium, such as a floppy disk, a DVD, a Blu-ray disk, a CD, a ROM, a PROM, an EPROM, an EEPROM or a flash memory, a hard disk, or any other magnetic or optical memory on which electronically readable control signals are stored that cooperate or can cooperate with a programmable computer system so that the respective method is executed. This is why the digital storage medium may be computer readable.

[0098] Thus, some embodiments according to the present invention include a data carrier comprising electronically readable control signals capable of cooperating with a programmable computer system to cause any of the methods described herein to be performed.

[0099] Generally, embodiments of the present invention may be implemented as a computer program product having program code which is effective to perform any of the methods when the computer program product is run on a computer.

[0100] The program code may for example be stored on a machine readable carrier.

[0101] Other embodiments comprise the computer program for performing any of the methods described herein, stored on a machine readable carrier. In other words, an embodiment of the inventive method is, therefore, a computer program having a program code for performing any of the methods described herein, when the computer program runs on a computer.

[0102] A further embodiment of the inventive method is therefore a data carrier (or digital storage medium or computer readable medium) having recorded thereon the computer program for performing any of the methods described herein. The data carrier, digital storage medium or recording medium is typically tangible or non-volatile.

[0103] A further embodiment of the inventive method is therefore a data stream or a sequence of signals representing the computer program for performing any of the methods described herein, the data stream or the sequence of signals being for example adapted to be transmitted via a data communications link, for example via the Internet.

[0104] A further embodiment comprises a processing means, for example a computer, or a programmable logic device, configured to or adapted to perform any of the methods described herein.

[0105] A further embodiment comprises a computer having installed thereon the computer program for performing any of the methods described herein.

[0106] Further embodiments according to the invention include a device or a system configured to transmit a computer program for performing at least one of the methods described herein to a receiver. The transmission may be, for example, electronic or optical. The receiver may be, for example, a computer, a mobile device, a memory device or a similar device. The device or the system may, for example, comprise a file server for transmitting the computer program to the receiver.

[0107] In some embodiments, a programmable logic device (e.g., a field programmable gate array, FPGA) may be used to perform some or all of the functions of the methods described herein. In some embodiments, a field programmable gate array may cooperate with a microprocessor to perform any of the methods described herein. In general, the methods are performed in some embodiments by any hardware device. The hardware device may be any universally applicable hardware, such as a computer processor (CPU), or may be method-specific hardware, such as an ASIC.

[0108] The above-described embodiments merely represent an example of the principles of the present invention. It is understood that other skilled in the art will recognize modifications and variations of the arrangements and details described herein. Therefore, it is intended that the present invention should be limited only by the scope of protection of the following claims, and not by the specific details presented herein based on the description and explanation of the embodiments.

[0109] term An anemometer is a measurement device for measuring local wind speed. Anemometers may include different designs (mechanical anemometers), hot wire anemometers, etc.

[0110] CML Commercial Microwave Link (CML) describes commercial directional radio paths between radio towers operating primarily at frequencies between 187 and 27 GHz. The density distribution of this wireless network roughly follows the population density.

[0111] The atmospheric boundary layer, also known as the peplosphere, represents the lowest layer of the Earth's atmosphere immediately adjacent to the Earth's surface.

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[10] EP 3071999 A.

[11] RU 2016112082 A.

[12] CN 212008640 U.

[13] US 5528224 A.

[14] KR 101961633 B1.

[15] CN 111916089 A.

[16] CA 1104245 A.

Claims

1. one or more audio transducers including at least one audio sensor (110) configured to identify sound pressure information; a processing unit (120) configured to determine meteorological information in response to the sound pressure information identified by the at least one sound sensor (110); Including, the one or more audio transducers are configured to be mounted to a mobile unit; system.

2. the at least one sound sensor (110) is configured to discern sound pressure information at least in an inaudible frequency range and an audible frequency range; and / or the at least one sound sensor (110) is configured to discern sound pressure information at least in the audible and ultrasonic frequency ranges; The system of claim 1 .

3. the at least one sound sensor (110) is configured to discern sound pressure information in the inaudible sound frequency range, the audible sound frequency range, and the ultrasonic frequency range. The system of claim 2.

4. The at least one sound sensor (110) is configured to discern sound pressure information in a frequency range f, 0≦f≦x (100 kHz≦x≦1 MHz). A system according to any one of claims 1 to 3.

5. the processing unit (120) is configured to determine precipitation information and / or wind information and / or temperature information in response to the sound pressure information identified by the at least one sound sensor (110) in order to determine the weather information. A system according to any one of claims 1 to 4.

6. The processing unit (120) for determining the meteorological information is configured to determine the precipitation information depending on the sound pressure information identified by the at least one sound sensor (110), The processing unit (120) determines the precipitation information by: - Precipitation type, - Precipitation droplet size and / or particle size; - composition of precipitation; - kinetic energy of precipitation, - Direction of precipitation origin configured to determine at least one of The system of claim 5.

7. The processing unit (120) is configured to determine at least a kinetic energy of the precipitation and / or at least a raindrop size of the precipitation to determine the precipitation information; the processing unit (120) being configured to determine an estimate of cloud height and / or information about condensation nuclei and / or particulate pollution of air as a function of the kinetic energy of the precipitation and / or as a function of the raindrop size of the precipitation, The system of claim 6.

8. The processing unit (120) for determining the weather information is configured to determine the wind information depending on the sound pressure information identified by the at least one sound sensor (110), To determine the wind information, the processing unit (120) may include the following wind information: - horizontal and / or vertical speed of the wind, - one or more directional vectors for the wind, - Wind type configured to determine at least one of A system according to any one of claims 5 to 7.

9. The processing unit (120) for determining the meteorological information is configured to determine the temperature information in response to the sound pressure information identified by the at least one sound sensor (110), The processing unit (120) is configured to determine an acoustic virtual temperature to determine the temperature information. A system according to any one of claims 5 to 8.

10. The system includes a noise suppression module (215) configured to apply a method for reducing noise to the sound pressure information identified by the at least one sound sensor (110) to obtain one or more noise-suppressed sound signals; the noise suppression module (215) is configured to forward the one or more noise suppressed signals to the processing unit (120); the processing unit (120) is configured to determine the weather information in response to the one or more noise suppression signals. A system according to any one of claims 1 to 9.

11. 11. The system of claim 10, wherein the noise suppression module (215) is configured to apply one or more noise suppression filters to at least one received audio signal comprising a signal representation of the sound pressure information identified by the at least one sound sensor (110) to determine the one or more noise suppression signals.

12. the processing unit (120) is configured to determine the weather information in response to the sound pressure information identified by the at least one sound sensor (110) by a machine training module trained by machine learning or by deep learning, A system according to any one of claims 1 to 11.

13. the one or more audio transducers include at least one sound wave generator (305) for generating sound waves; A system according to any one of claims 1 to 12.

14. the at least one sound wave generator (305) is further configured to identify sound pressure information; and / or The at least one sound sensor (110) is further configured to generate sound waves. The system of claim 13.

15. the at least one sound sensor (110) in the system is arranged to identify sound pressure information in response to the sound waves generated by the at least one sound wave generator (305); the processing unit (120) is configured to determine the weather information as a function of the sound pressure information dependent on the sound waves generated by the at least one sound wave generator (305) and identified by the at least one sound sensor (110).

15. A system according to claim 13 or 14.

16. The at least one audio sensor (110) is a plurality of audio sensors forming a two-dimensional or three-dimensional array; the processing unit (120) is configured to determine direction-dependent information in response to the sound pressure information identified by the plurality of sound sensors and in response to the two-dimensional or three-dimensional array of the plurality of sound sensors; the processing unit (120) is configured to determine the weather information in response to the direction information. The system of claim 15.

17. the processing unit (120) is configured to determine the weather information depending on a distance between the at least one sound wave generator (305) and the at least one sound sensor (110).

17. A system according to claim 15 or 16.

18. the acoustic waves generated by the at least one acoustic wave generator (305) are irradiated ultrasonic waves and / or irradiated inaudible acoustic waves and / or irradiated audible acoustic waves, the processing unit (120) is configured to determine a wind speed and / or a wind direction vector and / or an acoustic fictive temperature and / or a raindrop size and / or a precipitation amount depending on the sound pressure information dependent on the ultrasonic waves and / or the inaudible sound waves and / or the audible sound waves generated by the at least one sound wave generator (305). A system according to any one of claims 15 to 16.

19. The processing unit (120) processes the following precipitation information for determining the wind speed, and / or for determining the direction vector of the wind, and / or for determining the acoustic virtual temperature, and / or for determining the raindrop size, and / or for determining the amount of precipitation: - Precipitation type, - Precipitation droplet size and / or particle size; - composition of precipitation; - kinetic energy of precipitation, - a direction of origin of precipitation, 20. The system of claim 18.

20. the at least one processing unit (120) is configured to determine an aeroacoustic signature of the airflow by the sound pressure information identified by the at least one sound sensor (110) and to determine the meteorological information depending on the aeroacoustic signature.

20. A system according to any one of claims 1 to 19.

21. The system includes a housing in which a selectively guided air flow is generated.

21. A system according to any one of claims 1 to 20.

22. the one or more audio transducers include at least one vibroacoustic audio receiver for identifying vibroacoustic sound waves; the processing unit (120) is configured to determine the weather information in response to the vibroacoustic sound waves.

22. A system according to any one of claims 1 to 21.

23. the noise suppression module (215) is configured to perform the noise suppression in response to the vibroacoustic sound waves identified by the at least one vibroacoustic sound receiver.

23. The system of claim 22 further dependent on claim 10 or 11.

24. the processing unit (120) is configured to determine information relating to precipitation in response to the vibroacoustic sound waves.

24. A system according to claim 22 or 23.

25. the processing unit (120) is configured to recognize one or more acoustic events in response to the sound pressure information identified by the at least one sound sensor (110).

25. A system according to any one of claims 1 to 24.

26. the processing unit (120) is configured to classify the sound pressure information identified by the at least one sound sensor (110); 26. A system according to any one of claims 1 to 25.

27. the processing unit (120) is configured to recognize the one or more acoustic events by a machine training unit trained by machine learning or deep learning; 27. A system according to claim 25 or 26.

28. The system includes a transmitting interface (412) configured to receive the sound pressure information from the at least one sound sensor (110) and to forward the sound pressure information to a receiving interface (418); The system includes a receiving interface (418) configured to receive the sound pressure information from the transmitting interface (412) and forward the sound pressure information to the processing unit (120).

28. A system according to any one of claims 1 to 27.

29. The sound pressure information is transmitted wirelessly from the transmitting interface (412) to the receiving interface (418).

30. The system of claim 28.

30. The sound pressure information is transmitted from the transmitting interface (412) to the receiving interface (418) via a wire.

30. The system of claim 28.

31. The system includes the mobile unit, said at least one audio sensor (110) being mounted on said mobile unit; 31. A system according to any one of claims 1 to 30.

32. The system includes two or more mobile units including the mobile unit; the at least one audio sensor (110) being at least two audio sensors mounted on different mobile units of the two or more mobile units; 32. The system of claim 31.

33. the mobile unit is an aircraft; 33. A system according to any one of claims 1 to 32.

34. the mobile unit is a mobile robot unit; 34. A system according to any one of claims 1 to 33.

35. The mobile unit is an aerial drone.

35. A system according to any one of claims 1 to 34.

36. Identifying sound pressure information by using at least one sound sensor (110); determining, by a processing unit (120), meteorological information in response to the sound pressure information identified by the at least one sound sensor (110); Including, one or more audio transducers including the at least one audio sensor (110) are configured to be mounted on a mobile unit; method.

37. 37. A computer program having a program code for performing the method according to claim 36.

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