Systems and methods for determining particulate contamination

Abstract

The present invention relates to a system and method for determining particulate contamination, a method for determining particulate contamination in a measurement environment, wherein individual particles in the measurement environment are detected (S1); wherein at least one estimate of the number of particles per volume in the measurement environment is determined (S2); wherein at least one estimate of the number of particles per volume and characterization information describing at least one particle source in the measurement environment are used as a basis for an output value for determining particulate contamination in the measurement environment (S3); and wherein context-related data can be used and the characterization information is estimated based on the context-related data that can be used (S4). The estimation of the characterization information based on the context-related data that can be used is used to avoid the conventional limitation of the characterization information that can be evaluated to fixed specified information and, instead, enables the characterization information to be evaluated to be flexibly adjusted for the context-related data.

Description

Technical Field

[0001] The present invention relates to a system for determining particulate contamination. Similarly, the present invention relates to a method for determining particulate contamination in a measurement environment. Background Art

[0002] Many areas, especially densely populated areas, are severely contaminated by suspended particulate matter. This particulate contamination is at least partially caused by humans, especially mainly by industry, road traffic or air traffic, shipping and rail transport, and the combustion of carbon compounds in private households. Due to the geographical distribution of the various sources of suspended particulate matter, significant differences in local particulate contamination can be observed. This is the case both outdoors and in enclosed spaces.

[0003] It is known that suspended particulate matter can cause damage to health depending on its volume and composition, and the respirable fraction of suspended particulate matter is the main cause. The individual health risk basically depends on the degree and duration of the individual's exposure to the type of particulate contamination. Therefore, it is necessary to quantify local and current particulate contamination in each case.

[0004] The US particulate matter (PM) "National Ambient Air Quality" standard classifies suspended particulate matter into PM x fraction, this classification takes into account the size or diameter x of the dust particles, and thus takes into account the penetration depth of these dust particles into an individual's airways and body. In this case, in particular, a distinction is made between coarse dust PM 10 , fine dust PM 2.5 , and ultrafine dust PM1. Coarse dust PM 10 includes particles with a diameter of up to 10 μm, fine dust PM 2.5 has particles with a diameter of up to 2.5 μm, and ultrafine dust PM1 has particles with a diameter of 1 μm.

[0005] This PM standard is often used to quantify suspended particulate matter or particulate contamination. This involves the mass of dust particles per unit volume recorded over a period of time indicated for at least one of the above-mentioned fractions PM x . The increasing sensitivity to the problem of particulate contamination is creating a need for opportunities to perform rapid, local, and autonomous measurements of particulate contamination, especially in larger cities that are particularly severely contaminated by suspended particulate matter. Therefore, not only national or scientific institutions, but also private individuals are interested in finding the current particulate contamination at their current location. Therefore, there is a need for portable, miniaturized sensors for recording particulate contamination.

[0006] An exemplary optical particle sensor is known from WO 2017 / 198699 A1. The particle sensor includes a laser sensor module having at least two lasers for sending appropriate optical measurement laser beams that are reflected by particles in the environment of the particle sensor. The reflected measurement laser beams are detected by a common detector, and an appropriate measurement signal is output by the detector. The detection principle is based on the self-mixing interference method (SMI method), which must be understood to mean that the reflected measurement light beam interferes with the sent measurement laser beam. The interference causes changes in the optical and electrical properties of the laser, and these properties can be detected and used to draw conclusions about the properties of the particles in the environment of the particle sensor.

[0007] Therefore, the quantification of particle contamination discussed here is based on the number of dust particles in the recording volume. Thus, based on the PM classification and known size and mass distribution models of dust particles, a very good estimate of the particle contamination in terms of "mass of dust particles per volume" can be determined.

[0008] However, this "mass of dust particles per volume" information only very inadequately conveys the harmful nature of the suspended particulate matter, because the dangerous nature of dust particles is not only determined by their size and weight. These properties only allow statements about the depth to which they may penetrate into the body. In addition, the toxicity of dust particles is basically determined by their physical and chemical properties, i.e., by their surface conditions and / or chemical composition. Therefore, as known to the applicant himself in the prior art, when determining the particle contamination in the current measurement environment, characterization information describing at least one particle source in the corresponding measurement environment is also considered. Summary of the Invention

[0009] The present invention provides a system for determining particle contamination and a method for determining particle contamination in a measurement environment.

[0010] Advantages of the Invention

[0011] The present invention provides the opportunity to more precisely and reliably determine particle contamination in a variety of different measurement environments. The opportunity provided by the present invention to estimate (separate) characterization information of at least one particle source in the corresponding measurement environment allows for the evaluation of more and more accurate characterization information for determining particle contamination in the corresponding measurement environment. When using the present invention, the relatively high possibility of incorrect estimation of the characterization information is excluded. Therefore, the present invention allows for a more reliable determination of the particle contamination in the corresponding measurement environment, and thus also helps the person present in the corresponding measurement environment to better adjust his behavior based on a more accurate awareness of the particle contamination.

[0012] One advantageous embodiment of a system for determining particulate contamination is characterized by at least one sensor for capturing at least some situation - relevant data. Thus, the situation - relevant data can be measured at least in part by means of at least one sensor with high measurement accuracy and a relatively low error rate, and on the basis of this situation - relevant data, the characterization information of at least one particulate source in the measurement environment can be estimated. The at least one sensor can in particular be an inertial sensor, a pressure sensor, a temperature sensor, a humidity sensor, a gas sensor, a wind sensor, a light sensor, a camera, and / or a microphone. Thus, relatively inexpensive sensor types can be used as at least one sensor of a system for determining particulate contamination.

[0013] In another advantageous embodiment, a system for determining particulate contamination has at least one time information transmitter, which enables the time of day, the day - of - the - week information, and / or the date information to be used as at least some situation - relevant data for a particulate source estimation device. Such time information can also be used frequently to estimate the characterization information of at least one particulate source in the measurement environment more precisely and reliably.

[0014] Similarly, a system for determining particulate contamination can also have at least one interface for externally provided situation - relevant data. In this case, when estimating the characterization information of at least one particulate source in the measurement environment, the particulate source estimation device can also consider the externally provided situation - relevant data. Thus, the situation - relevant data that can be evaluated by the particulate source estimation device is not limited to the situation - relevant data determined by the components of the system for determining particulate contamination. The at least one interface can in particular be an interface to a positioning system and / or a navigation system for obtaining location data as at least some externally provided situation - relevant data, and / or an interface to a data provider, in particular for obtaining local weather data, information on local seismic and / or volcanic activity, local traffic information, and / or additional local active particulate sources as at least some externally provided situation - relevant data. Thus, a variety of situation - relevant data suitable for estimating the characterization information of at least one particulate source can be queried through the at least one interface.

[0015] In an equally very advantageous embodiment, a system for determining particulate contamination is characterized by at least one user interface for user - initiated input of at least some situation - relevant data. Thus, a user of a system for determining particulate contamination can also use their input to provide at least some situation - relevant data. As an example, the user can use their input to select at least some situation - relevant data from a variety of proposed example data and / or indicate the data by means of an appropriate description of the particulate source estimation device.

[0016] In addition, a system for determining particulate contamination may further include at least one storage medium for characterization information from at least two different known particulate sources, wherein the particulate source estimation device is able to access the at least one storage medium and is designed to use the available context-related data as a basis for the following processing: for selecting at least one known particulate source and making the characterization information describing the at least one selected particulate source available to the evaluation device for determining an output value of the particulate contamination. However, it is expressly noted here that, in addition to or as an alternative to the embodiments described here, the particulate source estimation device may also be designed to estimate at least one unknown particulate source in the respective measurement environment.

[0017] For example, the characterization information may include information on the size distribution of the particles, information on the mass distribution of the particles, information on the distribution of the specific material density of the particles, information on the material composition of the particles, information on at least one surface state of the particles, and / or information on at least one optical property of the particles. The information described here allows for a more reliable and accurate detection of the toxicity / hazard potential of the respective particles. Therefore, taking this information into account when determining the particulate contamination in the respective measurement environment also helps to more precisely and reliably specify the output value of the particulate contamination.

[0018] In another advantageous embodiment of the system for determining particulate contamination, the detector device is an optical particulate sensor device. In this case, the detector device includes a transmitting device for sending at least one measurement laser beam into the measurement environment and a detecting device for detecting the light of the at least one measurement laser beam scattered by the particles in the measurement environment. Such a detector device is very suitable for providing a detection signal based on which at least one estimate of the number of particles per volume in the measurement environment can be reliably specified.

[0019] Furthermore, the detector device may be installed in a mobile device equipped with at least one processor, wherein at least part of the functions of the evaluation device and / or the particulate source estimation device are performed by the at least one processor of the mobile device. Thus, the user of this embodiment of the system for determining particulate contamination can easily carry the detector device with them and thus always use the detector device in their current environment to determine the specific particulate contamination present.

[0020] As an improvement, the mobile device may further include at least one sensor for capturing at least some context-related data, at least one time information transmitter, at least one interface for externally provided context-related data, and / or at least one user interface for user-initiated input of at least some context-related data. Thus, the particulate source estimation device is able to access the context-related data thus captured and made available. Therefore, these context-related data can also always be taken into account when determining the particulate contamination in the current environment of the mobile device.

[0021] In addition, the mobile device may include at least one storage medium for characterization information from at least two different known particle sources and / or be able to access at least one external storage medium storing characterization information from at least two different known particle sources. Thus, integrating a system for determining particle contamination into the mobile device is not an obstacle to using the stored characterization information.

[0022] In an advantageous embodiment of the method for determining particle contamination, for at least some of the situation-related data an evaluation is made in order to estimate individual characterization information about at least one particle source in the current measurement environment. Such method steps can be carried out easily and relatively quickly.

[0023] In another advantageous embodiment of the method for determining particle contamination, the characterization information is made available for a group of at least two different known particle sources; for determining a characteristic quantity describing the current measurement situation, an evaluation is made for at least some of the situation-related data, and the determined characteristic quantity is used as a basis for identifying at least one particle source from the group of at least two different known particle sources as the most likely particle source for the current measurement situation; and the output value of the particle contamination is determined based on the characterization information of the at least one most likely particle source. This embodiment of the method for determining particle contamination in a corresponding measurement environment also allows the output value of the particle contamination to be specified precisely and reliably. Description of the Drawings

[0024] The following explains other features and advantages of the invention with reference to the drawings, in which:

[0025] Figure 1 a schematic illustration of an embodiment of a system for determining particle contamination is shown; and

[0026] Figure 2 a flow chart explaining an embodiment of the method for determining particle contamination in a measurement environment is shown. Detailed Description

[0027] Figure 1 A schematic illustration of an embodiment of a system for determining particle contamination is shown.

[0028] In Figure 1The system for determining particulate contamination schematically shown in [description] has a detector device 10 for detecting individual particles in the measurement environment of the detector device 10. Thus, the detector device 10 can also be referred to as a particle sensor. In particular, the detector device 10 can be an optical particle sensor device. Preferably, in this case, the detector device 10 includes a transmitter device (not shown) for sending at least one measurement laser beam into the measurement environment and a detector device (not shown) for detecting the light of at least one measurement laser beam scattered by the particles in the measurement environment. However, it is explicitly pointed out that the designability of the detector device 10 is not limited to a specific detector type.

[0029] The system for determining particulate contamination also has an evaluation device 12 for the detection signal 14 output by the detector device 10. The evaluation device 12 is designed to determine at least one estimate of the number of particles per unit volume in the measurement environment. In particular, at least one estimate can be specified in the unit "mass of dust particles per unit volume".

[0030] Similarly, the evaluation device 12 is designed to determine (and output) an output value x of the particulate contamination in the measurement environment, where the output value x of the particulate contamination is based on at least one estimate of the number of particles per unit volume and on characterization information 16 that describes at least one particle source in the measurement environment. The characterization information 16 that describes at least one particle source in the measurement environment can be understood to particularly also mean information related to the particles emitted by at least one particle source present in the measurement environment. The characterization information 16 can be, for example, information about the size distribution of the particles (emitted by at least one particle source present in the measurement environment), about the mass distribution of the particles, about the distribution of the specific material density of the particles, about the material composition of the particles, about at least one surface state of the particles, and / or about at least one optical property of the particles. Such information is applicable not only to detecting the possible penetration depth of the corresponding particles into the human body, but also to detecting the toxicity / hazard potential of the corresponding particles. Therefore, the characterization information 16 is also considered, allowing for the optimization of the specification of the output value x of the particulate contamination for an individual health risk, which is based on the corresponding particles actually prevalent for the people in the measurement environment.

[0031] The evaluation device 12 can be in the form of at least one algorithm on a processor, which is used to estimate at least one estimate of the number of particles per unit volume in the measurement environment by considering the detection signal 14 of the detector device 10, and to specify the output value x of the particulate contamination in the measurement environment by considering the at least one estimate and the characterization information 16. Thus, the evaluation device 12 can be manufactured inexpensively and has a relatively low installation space requirement.

[0032] In addition, the system for determining particulate contamination further has a particulate source estimation device 18, which can access context-related data 20. The particulate source estimation device 18 is designed to use the context-related data 20 as a basis for estimating characterization information 16, which relates to at least one particulate source in the measurement environment or to the particulates emitted by at least one particulate source present in the measurement environment. Compared with the prior art, the opportunity to estimate the characterization information 16 of at least one particulate source in the measurement environment by means of the context-related data 20 additionally provided by the particulate source estimation device 18 allows the evaluation device 12 to have more and / or more accurate characterization information 16. As will be explained in more detail below, the evaluation device 12 can use the above-mentioned more and / or more accurate characterization information 16 to specify the output value x. This is also a fundamental advantage over considering fixedly specified characterization information, which is usually the only possibility.

[0033] For example, the system for determining particulate contamination, due to its equipped particulate source estimation device 18, can also be advantageously used in a measurement environment in which at least one particulate source present therein was previously unknown, because the characterization information 16 of at least one particulate source in the corresponding measurement environment can be estimated based on the context-related data 20. That is, even if the system for determining particulate contamination has basically no available information about at least one particulate source in the corresponding measurement environment, the particulate source estimation device 18 can be used to quickly and reliably estimate the characterization information 16 of at least one particulate source in the corresponding measurement environment even for such an "unknown" measurement environment. As will be explained more precisely below, the system for determining particulate contamination can also additionally respond to time- and / or situation-dependent differences in the corresponding measurement environment by appropriately adjusting the characterization information 16 that the evaluation device 12 is capable of. The situation-dependent differences in the corresponding measurement environment to which the particulate source estimation device 18 can respond by appropriately adjusting the characterization information 16 can be understood to particularly mean weather-dependent differences and / or traffic volume-dependent differences. Then, the appropriate adjustment of the characterization information 16 can also be used to more precisely specify the output value x for particulate contamination for such differences. Therefore, the system for determining particulate contamination can always be reliably used in a variety of measurement environments that vary according to their local particulate contamination.

[0034] As Figure 1Schematically depicted in, the particle source estimation device 18 can, in particular, estimate at least one particle source in the measurement environment based on context-related data 20, and output an appropriate output signal 22 for at least one estimated particle source in the measurement environment to a storage medium 24 that stores specific characterization information 16 for a variety of particle sources for the particle source. Then, the storage medium 24 responds to the output signal 22 output by the particle source estimation device 18 by outputting relevant characterization information 16. In this way, the particle source estimation device 18 makes the characterization information 16 available for the evaluation device 12 to determine the output value x of particle contamination. However, it is expressly noted that equipping the system for determining particle contamination with the storage medium 24, as in Figure 1 Schematically depicted in, must be explained only by way of example. As will become clear from the following description, the particle source estimation device 18 can also be designed to use the context-related data 20 as the basis for the characterization information 16 of at least one particle source for which the particle source estimation device 18 previously had no available information.

[0035] In Figure 1 the embodiment of, the system for determining particle contamination also has at least one sensor 26 that captures at least some of the context-related data 20. The advantage of the design of the system with at least one sensor 26 is that the at least one sensor 26 can be used to determine the context-related data 20 of any measurement environment. In addition, the context-related data 20 that can be acquired by the at least one sensor 26 can always be re-measured for the corresponding measurement environment. Therefore, the system for determining particle contamination can also use the at least one sensor 26 to respond to changes in the corresponding measurement environment of at least one particle source affecting the measurement environment by re-estimating the characterization information 16 output to the evaluation device 12.

[0036] The at least one sensor 26 can, for example, be an inertial sensor (motion sensor). In this case, the inertial sensor can be used to determine whether the inertial sensor is at rest or moving at a specific speed or with a specific acceleration. The motion data that can be determined by means of the inertial sensor allows conclusions to be drawn about the type of motion of the inertial sensor, for example, the motion of the inertial sensor at walking speed, running speed, cycling speed, car speed, and / or train speed. Therefore, the detected type of motion of the inertial sensor can be used to infer the current measurement environment. This allows the at least one particle source present in the current measurement environment to be reliably estimated by the particle source estimation device 18.

[0037] Similarly, at least one sensor 26 may also be a pressure sensor. The pressure value measured by the pressure sensor can be used to infer the altitude of the current measurement environment. Such "geolocation" also allows for a reliable estimate of the characterization information 16 of at least one particle source in the current measurement environment by means of the particle source estimation device 18.

[0038] Alternatively or additionally, at least one sensor 26 may also be a temperature sensor. The temperature value output by the temperature sensor or its fluctuations can be used to infer the local climate, the current time of day (e.g., morning, noon, evening or night), the current season (e.g., summer or winter, rainy or dry season) and / or the presence of any heat sources in the measurement environment, such as a fire, a switched-on stove and / or a running internal combustion engine. Such climate, time and / or environmental information can be readily evaluated by the particle source estimation device 18 to specify the characterization information 16 to be output to the evaluation device 12.

[0039] Thus, at least one sensor 26 may also be a humidity sensor (e.g., an air humidity sensor). The measured value output by the humidity sensor also allows conclusions to be drawn about the prevailing climate / weather in the current measurement environment. Similarly, a specific environment can be detected based on the air humidity usually present therein. For example, relatively high air humidity usually occurs in swimming pools, while the air in offices is usually relatively dry.

[0040] If at least one sensor 26 is a gas sensor, the chemical properties of the air present in the current measurement environment can also be detected as context-related data 20 and evaluated by means of the particle source estimation device 18. A wind sensor can also be used to draw conclusions about the prevailing climate / weather in the current measurement environment. Information related to the distribution of the particle source can additionally advantageously be used to evaluate the wind direction of the prevailing wind in the current measurement environment determined by the wind sensor in order to determine the likelihood that particles from a specific particle source are blown into the measurement environment.

[0041] In another advantageous embodiment, the system for determining particle contamination also has a light sensor as at least one of its sensors 26. The light sensor can be understood to mean a brightness sensor or a spectrometer. The brightness value determined by the brightness sensor allows conclusions to be drawn about the time of day and / or the weather (e.g., sunny or rainy) prevailing in the current measurement environment. The spectrum measured by the spectrometer allows a distinction to be made between an open environment with relatively high-intensity low-wavelength radiation during the day and a closed environment (e.g., inside a house or a vehicle) where low-wavelength radiation is usually "filtered out" by at least one glass window even during the day as a rule.

[0042] As a favorable embodiment, at least one sensor 26 can also be a camera. The image data transmitted by the camera often allows the graphical detection of at least one particle source, such as a burning cigarette, an activated stove, a (steam) cooking vessel, a fire, a grill, a running internal combustion engine, a vehicle, and / or a chimney. In particular, the amount of particles released by the corresponding particle source can often be estimated by means of the image evaluation of the image data transmitted by the camera. Thus, the image data, which is context-related data 20 transmitted by the camera, allows the reliable estimation of the characterization information 16 by means of the particle source estimation device 18.

[0043] Furthermore, at least one sensor 26 can also be a microphone. Many particle sources (such as a moving vehicle, a running internal combustion engine, a running industrial facility, an activated vacuum cleaner, and / or a burning fire) produce typical sounds that can be identified based on the evaluation of the sound data collected by the microphone. Similarly, various different environments can be identified based on the sounds typically present therein. As an example, the interior of a living room can be reliably identified as the current measurement environment based on the sound of a television, a forest or park can be reliably identified as the current measurement environment based on the chirping of birds, the interior of a kitchen can be reliably identified as the current measurement environment based on the clicking and / or cooking sounds in the kitchen, a road can be reliably identified as the current measurement environment based on the sound of vehicles, and a public place can be reliably identified as the current measurement environment based on numerous footsteps and / or voices. Such information can also be evaluated by the particle source estimation device 18 in order to estimate the characterization information 16 of at least one particle source in the measurement environment.

[0044] In summary, it can thus be said that at least one sensor 26 of the system for determining particle contamination generally allows the estimation / identification of the time, weather / climate, "geographical location", physical characteristics of the current measurement environment, chemical characteristics of the current measurement environment, at least one action performed in the current measurement environment, at least one particle source present in the current measurement environment, and / or the type of the current measurement environment (e.g., urban environment or rural environment, natural environment or industrial environment, coastal or inland). All of these allow conclusions to be drawn about the characterization information 16 of at least one particle source in the measurement environment.

[0045] As an alternative to or in addition to the at least one sensor 26, the system for determining particulate contamination may also include at least one time information transmitter 28 that enables information about the time of day, the day of the week, and / or date information to be used by the particulate source estimation device 18 as at least some context-related data 20. Instead of inferring information about the time of day, the day of the week (e.g., weekday or weekend), and / or date information (e.g., spring, summer, fall, or winter) from the measured values measured by the at least one sensor 26, the above information may also be provided directly to the particulate source estimation device 18 by the at least one time information transmitter 28. Then, for example, the measured values measured by the at least one sensor 26 may be used to evaluate the time data transmitted by the at least one time information transmitter 28.

[0046] Advantageously, the system for determining particulate contamination may also have at least one interface 30 for externally provided context-related data. The at least one interface 30 may be, for example, an interface to a positioning system and / or to a navigation system for obtaining location data as at least some externally provided context-related data. Examples of positioning systems and / or navigation systems suitable for providing at least some externally provided context-related data are GPS systems (Global Positioning System), satellite navigation systems such as the GLONASS system, the Galileo system, or the Beidou system (Chinese satellite navigation system, e.g., Beidou-2), mobile phone antenna tower positioning systems (cell tower ID), triangulation positioning systems, and / or wireless access point systems. Similarly, the at least one interface 30 may also be an interface to a data provider (i.e., a provider of externally provided context-related data). Such data providers may be used in particular to obtain local weather data, information about local seismic and / or volcanic activity, local traffic information, and / or additional local active particulate sources as at least some externally provided context-related data. Thus, a variety of context-related data 20 may also be queried externally and subsequently evaluated by the particulate source estimation device 18 to estimate the characterization information 16 of at least one particulate source in the current measurement environment.

[0047] Thus, the at least one sensor 26, the at least one time information transmitter 28, and / or the at least one interface 30 may be used to capture and / or query a variety of context-related data 20 that are well-suited for estimating the characterization information 16. As an alternative to or in addition to the components 26 to 30, the system for determining particulate contamination may also have at least one user interface 32 for user-initiated input of at least some context-related data. Thus, a user of the system for determining particulate contamination may also, for example, provide at least some context-related data 20 to the particulate source estimation device 18 himself by selection from a table and / or input of a description.

[0048] As Figure 1 shown in the figure, it is not necessary to directly arrange components 26 to 32 on the particle source estimation device 18. Instead, components 26 to 32 can also be arranged on at least one device at a certain distance from the particle source estimation device 18. In this case, at least some of the context-related data 20 can be provided to the particle source estimation device 18 via a wireless connection.

[0049] Preferably, the detector device 10 of the system for determining particle contamination is installed in a mobile device. The mobile device can be understood to refer to, for example, a smart phone, a mobile phone, a tablet device, or an iPad. Advantageously, the mobile device is equipped with at least one processor, which means that the functions of the evaluation device 10 and / or the particle source estimation device 18 can be at least partially executed by at least one processor of the mobile device. At least one sensor 26 for capturing at least some of the context-related data 20, at least one time information transmitter 28, at least one interface 30 for externally provided context-related data 20, and / or at least one user interface 32 for user-initiated input of at least some of the context-related data 20 can also be installed on and / or in the mobile device. This ensures that the particle source estimation device 18 or at least one processor performing the functions of the particle source estimation device 18 can access the context-related data 20 captured and available thereby. Additionally, the mobile device usually already has at least one of components 26 to 32. However, as already explained above, it is generally not necessary to integrate components 26 to 32 into the mobile device either.

[0050] The mobile device can also have the above-mentioned storage medium 24. However, similarly, the mobile device can also access at least one external storage medium storing characterization information from at least two different known particle sources. Therefore, integrating the storage medium 24 into the mobile device is optional.

[0051] Figure 2 A flowchart showing an embodiment of a method for determining particle contamination in a measurement environment is shown.

[0052] When performing the method for determining particle contamination in a measurement environment, method step S1 involves detecting individual particles in the measurement environment. For example, detection of particles in the measurement environment can be implemented optically. In particular, the measurement environment can be probed with at least one measurement laser beam while detecting the light of at least one measurement laser beam scattered by particles in the measurement environment. However, the ability to perform method step S1 does not presuppose a specific measurement method.

[0053] Then, method step S2 involves determining at least one estimate of the number of particles per volume in the measurement environment, for which at least one measurement value obtained by method step S1 is evaluated. Based on at least one estimate of the number of particles per volume, subsequently as in method step S3, an output value of particle contamination in the measurement environment is determined. The determination of the output value of particle contamination in the measurement environment is also achieved based on the characterization information describing at least one particle source in the measurement environment. Examples of the characterization information have been listed above.

[0054] Before method step S3, method step S4 is also performed, in which the situation-related data is made available and the characterization information is estimated based on the available situation-related data. Thus, method step S4 avoids the conventional limitation of the characterization information that can be evaluated in method step S3 to fixedly specified information, but allows for a flexible adjustment of the characterization information to be evaluated according to the situation-related data.

[0055] As an example, at least some of the situation-related data are evaluated to estimate the individual characterization information about at least one particle source in the current measurement environment. In a possible implementation of method step S4, at least some of the situation-related data can be evaluated to determine the characteristic quantity describing the current measurement situation (of method step S1). Thereafter, by using the characterization information available for a set of at least two different known particle sources, at least one particle source in the set (of at least two different known particle sources) can be identified as the most likely particle source of the current measurement situation based on the determined characteristic quantity. This also allows for the determination of the output value of particle contamination by considering the characterization information of at least one most likely particle source.

[0056] The method for determining particle contamination in the measurement environment described here also brings the above advantages. However, these advantages are not listed again at this time.

Claims

1. A system for determining particulate contamination, the system comprising at least: a detector device (10) for detecting individual particles in the measurement environment of the detector device (10); at least one sensor (26); and an evaluation device (12) for the detection signal (14) of the detector device (10), the evaluation device (12) being designed to: - determine at least one estimate of the number of particles per volume in the measurement environment, and - determine an output value (x) of the particulate contamination in the measurement environment, wherein the output value (x) of the particulate contamination is based on at least one estimate of the number of particles per volume and on characterization information (16) describing at least one particle source in the measurement environment; The system is characterized in that: the at least one sensor (26) is an inertial sensor, a pressure sensor, a temperature sensor, a humidity sensor, a wind sensor, a brightness sensor, a camera and / or a microphone, and the system for determining particulate contamination comprises a particle source estimation device (18), the particle source estimation device (18): - is able to access context-related data (20), wherein the context-related data (20) comprises: motion data measured by the inertial sensor, pressure values measured by the pressure sensor, temperature values measured by the temperature sensor, values measured by the humidity sensor, wind direction determined by the wind sensor, brightness values determined by the brightness sensor, image data transmitted by the camera and / or sound data collected by the microphone, and - uses the context-related data (20) as a basis for: estimating the characterization information (16) of at least one particle source in the measurement environment, wherein the characterization information (16) comprises information on the size distribution of the particles, information on the mass distribution of the particles, information on the distribution of the material density of the particles, information on the material composition of the particles, information on at least one surface state of the particles and / or information on at least one optical property of the particles, and - makes the characterization information available to the evaluation device (12) in order to determine the output value (x) of the particulate contamination.

2. The system for determining particulate contamination according to claim 1, characterized in that at least one time information transmitter (28), the at least one time information transmitter (28) enabling information on the time of day, the day of the week and / or date information to be used as at least some of the context-related data (20) for the particle source estimation device (18).

3. The system for determining particulate contamination according to claim 1 or 2, characterized in that at least one interface (30) for externally provided context-related data, the at least one interface (30) comprising: - an interface to a positioning system and / or to a navigation system for obtaining position data as at least some of the externally provided context-related data, and / or - Interface to a data provider for obtaining local weather data, information on local seismic and / or volcanic activity, local traffic information, and / or additional local active particulate sources as at least some of the externally provided context-related data.

4. The system for determining particulate contamination according to claim 1, characterized in that at least one user interface (32) for user-initiated input of at least some of the context-related data (20).

5. The system for determining particulate contamination according to claim 1, wherein the system comprises at least one storage medium (24) for the characterization information from at least two different known particulate sources, wherein, The particulate source estimation device (18) is able to access the at least one storage medium (24) and is designed to use the available context-related data (20) as a basis for the following processing: for selecting at least one of the known particulate sources and making the characterization information describing at least one selected particulate source available to the evaluation device (12) to determine the output value (x) of the particulate contamination.

6. The system for determining particulate contamination according to claim 1, wherein The detector device (10) is an optical particulate sensor device, the optical particulate sensor device including a transmitting device for sending at least one measurement laser beam into the measurement environment and a detecting device for detecting the light of the at least one measurement laser beam scattered by the particulate in the measurement environment.

7. The system for determining particulate contamination according to claim 1, characterized in that, The detector device (10) is installed in a mobile device equipped with at least one processor, wherein the functions of the evaluation device (12) and / or the functions of the particulate source estimation device (18) are at least partially executed by the at least one processor of the mobile device.

8. The system for determining particulate contamination according to claim 7, wherein, The mobile device includes: - At least one sensor (26) for capturing at least some of the context-related data (20); - At least one time information transmitter (28); - At least one interface (30) for externally provided context-related data; and / or - At least one user interface (32) for user-initiated input of at least some of the context-related data (20); wherein the particulate source estimation device (18) is able to access the captured and available context-related data (20).

9. The system for determining particulate contamination according to claim 7, characterized in that, The mobile device includes at least one storage medium (24) for characterization information (16) from at least two different known particulate sources and / or is able to access at least one external storage medium storing characterization information (16) from at least two different known particulate sources.

10. A method for determining particulate contamination in a measurement environment, Among them, Detecting (S1) individual particulates in the measurement environment; wherein determining (S2) at least one estimate of the number of particulates per volume in the measurement environment; and wherein the at least one estimate of the number of particulates per volume and the characterization information (16) describing at least one particulate source in the measurement environment are used as a basis (S3) for determining the output value (x) of the particulate contamination in the measurement environment; characterized in that enable the motion data measured by the inertial sensor, the pressure value measured by the pressure sensor, the temperature value measured by the temperature sensor, the value measured by the humidity sensor, the wind direction determined by the wind sensor, the brightness value determined by the brightness sensor, the image data transmitted by the camera, and / or the sound data collected by the microphone to be used as at least part of the context-related data (20), and estimate (S4) information about the size distribution of the particles, information about the mass distribution of the particles, information about the distribution of the material density of the particles, information about the material composition of the particles, information about at least one surface state of the particles, and / or information about at least one optical property of the particles, based on the available context-related data (20), as the characterization information (16).

11. The method for determining particle contamination in a measurement environment according to claim 10, characterized in that - enable the characterization information (16) to be available for a set of at least two different known particle sources; - evaluate the context-related data (20) to determine characteristic quantities describing the current measurement situation, - the determined characteristic quantities are used as a basis for identifying at least one particle source from the set of at least two different known particle sources as the most likely particle source in the current measurement situation; and - the determination of the output value (x) of the particle contamination is based on the characterization information (16) of at least one most likely particle source.

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