Description:[0017] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words “comprising,” “having,” “containing,” and “including,” and other forms thereof, are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
[0018] Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the preferred, systems and methods are now described. Embodiments of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings in which like numerals represent like elements throughout the several figures, and in which example embodiments are shown. Embodiments of the claims may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. The examples set forth herein are non-limiting examples and are merely examples among other possible examples.
[0019] The present invention discloses a method for monitoring air quality specifically designed for the MSME sector, enabling industries to monitor and maintain compliance with emission standards through accurate, real-time AQI readings.
[0020] FIG. 1 illustrates a flow chart of a method (100) for monitoring air quality, according to an embodiment of the present invention.
[0021] The method (100) comprises steps of collecting real-time air quality data using low-cost air quality sensors. These sensors are deployed in key areas within industrial clusters, particularly in pollution hotspots, where MSMEs are located. The sensors continuously monitor levels of particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and volatile organic compounds (VOCs), among other pollutants. Data is transmitted wirelessly to a centralized server for further analysis.
[0022] The method (100) also comprises steps of analyzing the collected air quality data using an artificial intelligence (AI) algorithm. The AI-driven model analyzes the data to detect patterns, identify pollution sources, and predict air quality trends in real-time. The method (100) also generates alerts for sudden increases in pollutant levels, enabling quick responses to address air quality breaches.
[0023] The method (100) further comprises steps of deploying an unmanned aerial vehicle with AI-powered navigation. The unmanned aerial vehicles dynamically adjust their flight paths based on the AQI data collected by the sensors in the targeted areas. The unmanned aerial vehicles are equipped with additional air quality sensors to collect more granular data, enabling highly localized monitoring within industrial clusters housing MSMEs. This ensures more accurate identification of pollution hotspots and helps industries address specific emission issues.
[0024] Additionally, the method (100) includes interactive dashboards that present the analyzed air quality data in a user-friendly manner. These dashboards convert complex air quality metrics into simple, easy-to-understand insights, allowing MSME owners to monitor air quality trends, assess operational impacts, and take corrective measures to maintain compliance with emission standards.
[0025] In some embodiments, the method (100) is designed to provide MSMEs with cost-effective and scalable air quality monitoring solutions, addressing their limited resources for environmental compliance. The method (100) can be customized to meet the specific needs of different industrial clusters, ensuring comprehensive coverage and precise data collection.
[0026] In conclusion, the method (100) for monitoring air quality enables MSMEs to improve operational efficiency, maintain environmental sustainability, and comply with emission standards. By offering AI-driven analysis, dynamic unmanned aerial vehicle monitoring, and interactive dashboards, the method (100) ensures that pollution hotspots are quickly identified and addressed, mitigating environmental impact in industrial regions.
[0027] It should be noted that the method (100) for monitoring air quality in any case could undergo numerous modifications and variants, all of which are covered by the same innovative concept; moreover, all of the details can be replaced by technically equivalent elements. In practice, the components used, as well as the numbers, shapes, and sizes of the components can be of any kind according to the technical requirements. The scope of protection of the invention is therefore defined by the attached claims. , Claims:WE CLAIM:
1.A method (100) for monitoring air quality, the method (100) comprises:
determining via a plurality of sensors, an air quality index (AQI) of an area;
transmitting, via at least one processor, a data comprising the determined AQI to a central server; and
displaying, via a user interface, the determined AQI to enable monitoring emissions from the area and compliance with environmental standards.

2.A method (100) as claim in claims 1, wherein the area correspond to clusters of MSME industries.

3.A method (100) as claimed in claim 1, wherein the plurality of sensors are installed on an unmanned aerial vehicle.