System for real-time air quality monitoring

Abstract

System (100) for real-time air quality monitoring, including: • at least one mobile sensor unit (110), installed on a vehicle or for retrofitting on a vehicle; • at least one stationary sensor unit (120) at a fixed location; • an integration platform (130), ◯ trained to fusion the acquired sensor data with external data sources (140), including at least meteorological data and / or satellite-based environmental data, ◯ for automated anomaly detection (150) using threshold comparison and / or machine learning, ◯ for generating alarm signals (160), ◯ to provide the processed air quality data (170) with time and location reference via interfaces to external technical applications (180).

Description

[0001] The invention relates to a system for real-time monitoring of air quality according to the preamble of the first claim. In particular, the system detects air pollutants.

[0002] The invention relates in particular to the field of environmental and health monitoring, especially systems and methods for the real-time detection, analysis, and evaluation of air pollutants. Furthermore, the invention relates to the integration and technical processing of data from various sources and their use for anomaly detection, early warning, and cross-sectoral processing in technical systems.

[0003] This is done by incorporating mobile, stationary and external data sources, as well as for anomaly detection and cross-sectoral use. Various systems for recording and evaluating air quality parameters are known from the state of the art, especially in the vehicle sector or for point-based environmental monitoring.

[0004] German patent DE102022125784A1 (GM Global Technology) discloses a system for vehicle-based acquisition of air quality and noise data with transmission to mapping software. Integration of external data sources or further evaluation processes are not provided.

[0005] DE102022101243A1 (Ford Global Technologies) describes a system for detecting air pollutants inside the vehicle with measures based on this to improve air quality within the passenger compartment.

[0006] DE102020210013A1 (Volkswagen AG) concerns a method for estimating air pollution based on driving data, without direct sensor measurement and without incorporating external environmental or weather data.

[0007] German patent DE102020209860A1 (Siemens AG) discloses a mobile measuring vehicle for the temporary recording of environmental parameters. The system is designed for point measurements and is not intended for continuous, network-based monitoring.

[0008] German patent DE102020202827A1 (Robert Bosch GmbH) describes an environmental measurement system capable of recording general environmental parameters. However, the patent does not focus on the technical integration of heterogeneous data sources or cross-sectoral data processing.

[0009] Furthermore, there are known international projects that collect air quality data using mobile sensors. One example is the "Sniffing Bike" project in Belgium, where bicycles are equipped with simple particulate matter sensors to collect local environmental data. The "Breathe London" project also uses mobile measurements on taxi fleets. Similarly, Google employs sensor-equipped vehicles for data collection in its "Street View Air Quality Project." In all cases, these are visualization or citizen science initiatives, without automated processing or response logic.

[0010] What these projects have in common is that while they collect environmental data using mobile devices, they lack the technical infrastructure for real-time data fusion with external sources, automated anomaly detection, response mechanisms, or cross-sector system integration.

[0011] The known solutions have, in particular, the following technical limitations: 1. Limited system architecture: The systems are mostly designed as standalone devices or vehicle-integrated components, without an overarching infrastructure for data synchronization and networking. 2. Lack of data fusion from heterogeneous sources: Technical integration of measurement data with external environmental or weather data sources, such as meteorological services or satellite information, is not planned. 3. Limited target direction: The existing systems are typically designed for map-based visualizations, indoor protection or point-based measurement, but not for system-wide real-time monitoring or early warning. 4. No cross-sectoral reuse: The data will not be processed or made available for medical, insurance-related or quality-of-life applications such as sports or smart home systems. 5. Lack of connection to control systems: Technical integration for the automated control of external infrastructure facilities, such as in the transport or building sectors, is not implemented in the known solutions. 6. No modular or scalable system approach: The existing systems are not designed for easy retrofitting or network-wide scaling, which prevents comprehensive data collection.

[0012] The object of the present invention is to provide a technically integrated system that enables comprehensive, high-resolution, real-time acquisition, evaluation and use of air pollutant data and provides technically usable information for downstream systems.

[0013] The problem is solved by a system having the features of claim 1. Advantageous embodiments are described in the dependent claims and the following description.

[0014] The system comprises retrofittable mobile sensor units, which can be mounted on vehicles in particular, stationary measuring units at fixed locations, and an integration platform for fusing environmental data with external data sources, especially meteorological information and satellite-based environmental data. The platform is designed to detect anomalies using threshold comparison and / or machine learning, to generate early warnings for authorities and infrastructure providers, and to automatically request further analyses when predefined thresholds are exceeded. Furthermore, the processed air quality data is intended for medical, insurance-related, infrastructure, and health-related applications.

[0015] The invention is explained in more detail below using an exemplary embodiment and an accompanying drawing. Fig. Figure 1 shows the diagram of a System 100.

[0016] The system (100) for real-time air quality monitoring includes in particular: • at least one mobile sensor unit (110), preferably in the form of modular, retrofittable sensor boxes (111), attached to vehicles for the comprehensive collection of air quality parameters; • at least one stationary sensor unit (120) for reference data collection at fixed locations, e.g. in urban areas or at industrial plants; • an integration platform (130) for data fusion with external data sources (140), comprising at least meteorological data (e.g. wind direction, temperature) and / or satellite-based environmental data (e.g. air pollutant measurements from Copernicus services); • a component for automated anomaly detection (150) using threshold comparison and / or machine learning; • a function for generating alarm signals (160) in the event of detected anomalies; • a component for providing the technically processed air quality data (170) with assigned time and location stamps via interfaces to external technical applications (180).

[0017] Preferred applications include: • Automatic initiation of laboratory analyses (190) when limit values ​​are exceeded, • AI-supported pattern recognition (200) for continuous system optimization, • Detection and notification of hazardous chemical, biological or radiological substances (210), • Output of control signals (220) to infrastructure facilities (230), e.g. traffic lights or ventilation systems, • Technical processing of data for sports-related applications (240) with interfaces via API (250), • Use of structured technical data in medical systems (260), e.g. for symptom analysis, • Pharmacies (270) for forecasting the demand for medications (280), • Insurance (290) for technology-based risk assessment (291) and preventive action planning (292), • Integration into smart home systems (300) or wearables (310) with recommendations (320) to end users.

[0018] As in Fig. Figure 1 shows a schematic process example of the system (100) according to the invention for real-time monitoring of air quality.

[0019] A mobile sensor unit (110), in particular in the form of a modular sensor box (111), records location- and time-related environmental data, especially air pollutant concentrations. The recorded measurement data are transmitted to a central integration platform (130).

[0020] The integration platform (130) performs technical preprocessing and automated anomaly detection (150). This can be based on static thresholds or on dynamically learned decision rules. To continuously improve detection performance, an AI component can be used, which enhances pattern recognition based on historical and current data using machine learning (200).

[0021] As part of the analysis, potentially hazardous chemical, biological, or radiological substances are also identified by a detection unit (210). If there is sufficient suspicion, further laboratory analyses (190) can be automatically triggered, for example, by activating external laboratory protocols or sampling systems.

[0022] The processed air quality data (170) generated in the platform (130), including metadata such as geoposition and timestamp, and, if applicable, a generated alarm signal (160), are made available to external technical systems via a programming interface (250).

[0023] An example of such a connected application is an infrastructure facility (230), for example a municipal traffic management system. There, a system-specific risk assessment (291) is carried out using the provided technical data.

[0024] Based on this assessment, a recommendation (320) or an automated action can be issued. In a preferred embodiment, this action relates to the optimized control of traffic signal systems (e.g., traffic light sequences) to influence traffic flows depending on air quality and to reduce local emission peaks in real time.

[0025] In a preferred embodiment, the system (100) for real-time air quality monitoring comprises at least one mobile sensor unit (110), which is either permanently attached to a vehicle or designed as a retrofittable component. Additionally, at least one stationary sensor unit (120) is provided, which is installed at a fixed location for continuous environmental data acquisition.

[0026] Furthermore, the system includes an integration platform (130) which is designed for data fusion of the sensor data acquired by the mobile and stationary units with external data sources (140), wherein the external data sources include at least meteorological information (e.g. wind direction, temperature) and / or satellite-based environmental data.

[0027] Furthermore, the integration platform (130) is trained for automated anomaly detection (150), whereby the detection can be based on a threshold comparison and / or on machine learning methods.

[0028] If an anomaly is detected, the system generates a corresponding alarm signal (160), which is transmitted to external technical applications (180) via suitable communication interfaces.

[0029] Furthermore, the platform technically processes the air quality data (170) and makes it available to downstream systems, specifying time and location stamps. Reference symbol list 100 complete air quality monitoring system 110 Mobile Sensor Unit 111 Modular Sensor Box 120 Stationary sensor unit 130 Integration platform 140 External data source 150 anomaly detection 160 Alarm signal 170 processed air quality data points 180 External technical application 190 Further laboratory analysis 200 Machine Learning 210 Hazardous substance detection 220 control signal 230 infrastructure facilities 240 sports application 250 Programming interface (API) 260 Medical Application 270 Pharmacy 280 Drug Prognosis 290 insurance companies 291 Risk assessment 292 Prevention planning 300 Smart Home System 310 Wearable 320 recommendations for users QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] DE 102022125784A1

[0004] DE 102022101243A1

[0005] DE 102020210013A1

[0006] DE 102020209860A1

[0007] DE 102020202827A1

[0008]

Claims

[1] System (100) for real-time monitoring of air quality, comprising: • at least one mobile sensor unit (110), installed on a vehicle or for retrofitting on a vehicle; • at least one stationary sensor unit (120) at a fixed location; • an integration platform (130), ◯ trained to fusion the acquired sensor data with external data sources (140), including at least meteorological data and / or satellite-based environmental data, ◯ for automated anomaly detection (150) using threshold comparison and / or machine learning, ◯ for generating alarm signals (160), ◯ to provide the processed air quality data (170) with time and location reference via interfaces to external technical applications (180). [2] System according to claim 1, wherein the integration platform (130) initiates the performance of further laboratory analyses (190) when a threshold is exceeded. [3] System according to one of the preceding claims, wherein machine learning (200) is used to detect patterns or unknown anomalies. [4] System according to one of the preceding claims, wherein the mobile sensor units (110) are designed as interchangeable, modular sensor boxes (111). [5] System according to any of the preceding claims, wherein radiological, chemical or biological agents (210) are detected and corresponding early warnings (160) are triggered. [6] System according to one of the preceding claims, wherein the integration platform (130) outputs automatic control signals (220) to infrastructure facilities (230). [7] System according to one of the preceding claims, wherein the platform (130) processes the air quality data for sports-related applications (240) and makes it available to external systems via a programming interface (250). [8] System according to one of the preceding claims, wherein the data (170) are used to support medical applications (260), in particular symptom analysis and resource planning. [9] System according to one of the preceding claims, wherein pharmacies (270) use the provided data (170) to forecast the demand for medicines (280). [10] System according to any of the preceding claims, wherein insurance undertakings (290) use the data for risk assessment (291) and prevention planning (292). [11] System according to any of the preceding claims, wherein the integration platform (130) communicates with smart home systems (300) or portable devices (310) to provide alerts (160) or recommendations (320) to end users.

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