Mobile air quality monitoring system with scalable data architecture and real-time processing platform

Abstract

A mobile environmental monitoring system comprising one or more vehicle-mounted sensor units configured to acquire environmental data, including air quality parameters (101), meteorological parameters (102) and geolocation information (103) while in motion, a communication subsystem (104) for transmitting the acquired data (105) and a central data processing platform (106) for receiving (107), processing (108) and storing (109) this data, the system enabling dynamic and spatially distributed environmental monitoring.

Description

Technical field of expertise: The present invention relates generally to the field of environmental monitoring, data management, and IoT-enabled sensor systems. In particular, the invention relates to a system and method for mobile air quality monitoring using vehicle-mounted sensors integrated into a scalable data architecture for real-time data acquisition, processing, geosynchronization, and visualization. The invention further relates to distributed sensor networks, cloud-based data platforms, and intelligent environmental analysis systems designed for urban planning, public health assessment, and traffic optimization. The invention also falls within the scope of smart city infrastructure and advanced data-driven environmental decision support systems. Background of the invention; Air quality monitoring has become essential in modern urban environments due to increasing levels of pollution and its direct impact on human health, climate, and environmental sustainability. Traditionally, environmental monitoring relied on permanently installed air quality monitoring stations strategically distributed across cities and industrial areas. These stations are equipped with high-precision instruments capable of measuring pollutants such as particulate matter (PM2.5 and PM10), nitrogen oxides (NOx), sulfur dioxide (SO2), ozone (O3), and other atmospheric parameters. While such systems provide reliable and standardized measurements, they suffer from significant limitations in terms of spatial coverage, operating costs, and operational flexibility. Fixed monitoring stations are typically sparsely populated due to their high installation and maintenance costs. As a result, they cannot capture local fluctuations in air quality caused by traffic congestion, industrial emissions, construction work, or microclimatic conditions. Urban air pollution is highly dynamic and varies considerably over short distances and time intervals; however, stationary systems cannot accurately reflect this variability. Consequently, policymakers often rely on incomplete or generalized data, limiting the effectiveness of environmental policies and public health measures. Recent advances in sensor technology and IoT systems have led to the development of cost-effective environmental sensors that can be deployed in larger numbers. These sensors have enabled distributed monitoring approaches, including citizen science initiatives and local sensor networks. However, many such systems are still limited by their static nature, fragmented deployments, and a lack of integration across platforms. The data collected by these sensors often remains isolated, inconsistent, and difficult to process due to the lack of standardized data architectures and processing pipelines. Additionally, the emergence of mobile sensor platforms, such as sensors mounted on vehicles, drones, or public transportation systems, has demonstrated the potential to improve the spatial coverage of environmental data. These systems can collect data across larger geographic areas during normal movement. However, existing implementations primarily focus on data acquisition hardware and do not adequately address the challenges associated with managing large datasets, real-time processing, spatial synchronization, and integration with contextual data sources such as video or traffic information. Another major limitation of current technologies lies in processing the large volumes of heterogeneous data generated by mobile sensor systems. Without a structured framework for data collection, validation, storage, and analysis, it will be difficult to utilize such data effectively. Furthermore, most existing platforms lack advanced analytics capabilities, real-time visualization tools, and personalized data access mechanisms tailored to diverse stakeholders such as urban planners, environmental researchers, healthcare professionals, and transportation operators. Therefore, there is a need for an integrated and scalable system that combines mobile environmental sensors with a robust data architecture capable of handling real-time data acquisition, processing, spatial orientation, contextual enrichment, and user-specific visualization. Such a system should overcome the limitations of conventional stationary monitoring and fragmented IoT solutions while enabling dynamic, high-resolution environmental monitoring and data-driven decision-making. Objectives of the invention; 1. To provide a mobile air quality monitoring system capable of collecting environmental data using vehicle-mounted sensor units at various geographic locations. 2. To develop a structured and scalable data architecture for the efficient collection, validation, processing, storage, and management of heterogeneous environmental data. 3. To enable real-time or near-real-time geosynchronization and contextual enrichment of environmental data, including integration with location and visual information. 4. To provide an interactive and role-based data visualization and analysis platform for various stakeholders, including environmental experts, public health professionals, and transportation operators. Summary of the invention: The present invention discloses a comprehensive system and method for mobile air quality monitoring that integrates vehicle-mounted environmental sensor units with a scalable and structured data architecture designed for real-time data processing and analysis. The invention introduces a dynamic approach to environmental monitoring by replacing conventional stationary measurement systems with mobile sensor platforms capable of collecting data over large geographical areas during routine vehicle movement. This significantly improves spatial coverage and enables high-resolution mapping of environmental conditions. In one aspect, the invention comprises mobile sensor units mounted on vehicles or other movable platforms, wherein the sensor units are configured to continuously or periodically measure environmental parameters such as air quality indicators, temperature, humidity, atmospheric pressure, and optionally noise levels. These sensor units are also equipped with geolocation modules for capturing precise positional data and may include imaging devices for capturing contextual visual information about the monitored environment. The collected data are time-stamped and linked with location information, thereby creating spatially distributed environmental datasets. The invention further provides a communication framework through which the captured data is transferred from the mobile units to a central data processing platform. Depending on operational requirements, this transfer can be carried out via web-based services, streaming mechanisms, or alternative data transmission protocols. The central platform is implemented with a containerized infrastructure, ensuring scalability, modularity, and efficient resource utilization. A key feature of the invention lies in its structured data flow architecture, which defines a complete pipeline for processing heterogeneous data streams. Upon receipt, the data undergoes automated acquisition, validation, and transformation processes. Environmental measurements are synchronized with geospatial coordinates, and where applicable, visual data is processed to extract meaningful contextual information. The system is capable of identifying relevant frames from video streams and extracting objects or features that can be linked to environmental observations, thereby enriching the dataset. The processed and enriched data are stored in a central database management system in a structured and queryable format. The invention supports both continuous data, such as numerical sensor readings, and discrete data, such as extracted objects or events. This unified storage approach enables advanced analytical capabilities by allowing for the correlation between environmental parameters and contextual factors. Furthermore, the invention includes a user interface layer comprising web-based applications and application programming interfaces (APIs) that facilitate data access, visualization, and analysis. Users can interact with the system via dashboards, geomaps, and analysis tools to gain insights into environmental conditions across different regions and time periods. The system supports role-based access control, enabling different user categories to access customized views and datasets according to their specific needs. By integrating mobile sensing, structured data processing, geospatial analysis, and user-centric visualization into a unified platform, the invention offers a robust and scalable solution for real-time environmental monitoring. It overcomes the limitations of traditional monitoring systems and fragmented IoT solutions, enabling data-driven decision-making in urban planning, public health, and environmental sustainability. Brief description of the drawing Fig. 1 shows a block diagram of the system according to the invention. Detailed description of the invention The present invention relates to an integrated system and process architecture for dynamic environmental monitoring using mobile sensor platforms, combining vehicle-mounted sensor units with a scalable infrastructure for data acquisition, processing, storage, and visualization. The invention is designed to enable continuous, high-resolution, and spatially distributed monitoring of air quality and related environmental parameters, while simultaneously ensuring a structured data flow, real-time processing, and interoperability with analytical systems. The invention addresses the technical challenges associated with fragmented sensor networks, the limited spatial coverage of stationary monitoring systems, and the lack of unified data processing architectures. In one embodiment, the invention comprises a mobile sensor subsystem configured for mounting on vehicles or other moving platforms operating in urban, suburban, or transportation environments. The sensor subsystem is housed in a special enclosure designed for secure attachment to the vehicle, preferably by magnetic or mechanical fastening devices, while simultaneously protecting the internal components from environmental conditions such as dust, vibrations, and temperature fluctuations. The mobile sensor unit operates autonomously during vehicle movement and is capable of acquiring environmental data either continuously or at predefined intervals. The sensor subsystem comprises one or more environmental sensors configured to measure air quality parameters such as particulate matter concentrations, gaseous pollutants, and other atmospheric indicators. In addition to air quality measurement, the subsystem can include sensors for temperature, humidity, air pressure, and ambient noise, enabling multidimensional environmental monitoring. The sensor unit is also equipped with a positioning module, such as a receiver from a global navigation satellite system, configured to capture real-time geolocation coordinates for each measurement event. This geolocation capability ensures that all environmental data collected by the system is spatially referenced, allowing for route-based and location-specific analysis. In a preferred embodiment, the sensor unit can also include an imaging system consisting of one or more cameras configured to capture video or image data of the monitored environment. The imaging subsystem operates synchronously with the sensor and positioning components, enabling contextual mapping between environmental data and visual observations. The captured visual data can include raw video streams, time-synchronized still images, or selectively sampled images, which can later be processed to extract contextual information such as traffic conditions, roadside features, or environmental anomalies. The mobile sensor unit also includes a communication subsystem configured to transmit the collected data to a central data processing platform. This communication subsystem can utilize wireless communication technologies such as cellular networks, wireless internet, or dedicated communication channels. In one implementation, environmental sensor data is transmitted via web-based service interfaces, while large data volumes, such as video streams, can be transmitted via streaming protocols or buffered for batch upload, depending on network availability and bandwidth. The system can also integrate local storage within the sensor unit to temporarily buffer data during connectivity interruptions, thus ensuring data continuity and preventing data loss. The central aspect of the invention lies in the structured data architecture implemented within the server-side platform. The central platform is configured as a scalable computing environment consisting of several software components deployed in containerized form. The use of containerization technology enables modular deployment, service isolation, efficient resource management, and easy scaling across different computing environments. The platform includes dedicated components for data acquisition, processing, storage, analysis, and user interaction. After transmission from the mobile sensor units, the incoming data is received by a data acquisition subsystem configured to accept heterogeneous data streams from multiple devices. This subsystem supports various data input mechanisms, including web service endpoints, streaming interfaces, and file-based uploads. Once received, the data undergoes validation processes to ensure integrity, consistency, and accuracy. Validation may include checks for data completeness, format compliance, timestamp synchronization, and the plausibility of the sensor readings. Following validation, the data is processed through a structured data flow pipeline, which represents a key innovative feature of the system. Within this pipeline, environmental measurements are correlated with corresponding geolocation coordinates to create spatially indexed datasets. For visual data, video streams or captured still images are synchronized with positional data to establish a relationship between the visual context and environmental data. The system is further configured to selectively extract relevant frames based on temporal or spatial criteria, thereby optimizing storage and processing efficiency. In one embodiment, the processing subsystem includes algorithms for extracting objects or features from visual data. Such objects can include vehicles, elements of road infrastructure, or environmental features that provide contextual insights into the observed conditions. The extracted objects are transformed into structured datasets and stored together with environmental data in the central database. This integration of continuous sensor data with discrete contextual data enables advanced analytical capabilities and supports multidimensional environmental assessment. The processed data is stored in a central data storage subsystem, preferably implemented with a relational database management system. The database is configured to store raw data, processed data, enriched datasets, and metadata in a structured format that supports efficient queries and retrievals. The storage subsystem is designed to handle large volumes of data generated by multiple simultaneously operating sensor units, ensuring scalability and high performance. Indexing mechanisms and data partitioning strategies can be employed to optimize data access and processing speed. The invention further comprises an analysis and visualization subsystem that enables users to interact with the collected and processed data. This subsystem includes web-based applications and visualization tools that provide graphical representations of environmental conditions. Users can access dashboards that display time-series data, geospatial maps, route-based profiles, and analytical summaries. Continuous data, such as pollutant concentrations, can be visualized as dynamic charts or heatmaps, while discrete data, such as extracted objects, can be displayed as annotated map elements or event markers. The system is designed to support multiple user categories, each with different access requirements and analytical needs. To facilitate this, the invention incorporates a role-based access control mechanism that governs user authentication and authorization. Different user roles, such as administrators, data providers, and end users, are granted specific permissions that determine the scope of accessible data and functions. This ensures secure and controlled access to sensitive environmental data while simultaneously enabling sharing across various stakeholder groups. In addition to direct user interaction via web interfaces, the invention provides application programming interfaces (APIs) that allow external systems to access and use the collected data. These APIs support interoperability by enabling integration with third-party analytics tools, urban planning systems, public health platforms, and other data-driven applications. The system can also support data export in standardized formats, thereby facilitating further analysis and research. The invention is further distinguished by its ability to process both continuous and discrete data within a unified framework. Continuous data includes numerical measurements obtained from sensors, while discrete data comprises categorized or extracted information derived from contextual inputs. By combining these two data types within a single platform, the system enables comprehensive analysis that considers both quantitative environmental parameters and qualitative contextual factors. Scalability is a key feature of the invention, enabling the system to accommodate a growing number of sensor units, data streams, and users without any loss of performance. The use of containerized services allows individual system components to scale independently based on demand. The system is also designed to handle fluctuations in data load, network conditions, and operational requirements, thus ensuring robustness and reliability. To ensure operational continuity, the system includes mechanisms for handling network interruptions, system failures, and data recovery. Local buffering within the sensor units allows for the temporary storage of data and its transmission once connectivity is restored. The central platform includes monitoring and management tools that track system performance, resource utilization, and operational status, thus enabling proactive maintenance and fault detection. Security is an integral aspect of the invention. The system relies on multiple security layers, including encrypted data transmission, secure communication protocols, user authentication, and access control mechanisms. Data transmitted between the sensor units and the central platform is protected by secure protocols, while the server-side infrastructure is secured by firewall configurations, secure access controls, and monitoring systems. These measures ensure the confidentiality, integrity, and availability of environmental data. In operation, the invention enables a vehicle equipped with the sensor unit to traverse a geographical area while continuously collecting environmental data. The collected data is transmitted to the central platform, processed via the structured data pipeline, and made available for visualization and analysis. The resulting system provides high-resolution, real-time insights into environmental conditions across large geographical areas, thus supporting informed decision-making. The invention is suitable for a wide variety of applications, including urban air quality monitoring, transport route analysis, environmental research, and public health assessment. By providing a unified platform that integrates mobile sensors, data processing, and analysis, the invention significantly improves the ability to monitor and understand environmental conditions in dynamic and complex environments. Thus, the present invention offers a technically advanced and scalable solution for mobile environmental monitoring that overcomes the limitations of conventional systems and enables efficient, data-driven environmental management. Reference symbol list 100 System 101 Air quality parameters 102 Meteorological parameters 103 Geolocation information 104 Communication subsystem 105 of the recorded data 106 Central data processing platform 107 for recording 108 Processing 109 Storage

Claims

A mobile environmental monitoring system comprising one or more vehicle-mounted sensor units configured to acquire environmental data, including air quality parameters (101), meteorological parameters (102) and geolocation information (103) while in motion, a communication subsystem (104) for transmitting the acquired data (105) and a central data processing platform (106) for receiving (107), processing (108) and storing (109) this data, the system enabling dynamic and spatially distributed environmental monitoring. System according to claim 1, wherein the central data processing platform comprises a structured data flow architecture configured for automated data acquisition, validation, spatial synchronization, enrichment and storage of heterogeneous environmental data received from the mobile sensor units. System according to claim 1, wherein the mobile sensor units further comprise an imaging subsystem configured to acquire visual data, and the central platform configured to process the visual data in order to extract contextual information and to link the extracted information with the relevant environmental data. System according to claim 1, wherein the central platform is implemented using containerized computing components, including database services, processing modules, application interfaces and visualization tools, thereby enabling scalable data processing, real-time analytics and user interaction via dashboards and application programming interfaces. System according to claim 1, wherein the system further comprises a role-based access control and interoperability framework configured to enable secure, differentiated access to environmental data for multiple users and to enable integration with external systems via standardized interfaces and data services.

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