Description:[0001] Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0002] Air in its purest stat is best suited for the essential task sustaining life. Air pollution is a major environmental risk to health. Breathing clean air can lessen the possibility of disease from stroke, heart disease, lung cancer as well as chronic and acute respiratory illness such as asthma.
[0003] A number of different types of air pollution prediction systems that are known in the prior art. For example, the following patents are provided for their supportive teachings and are all incorporated by reference.
[0004] US7302313B2 An air monitoring system is disclosed having an air monitoring unit with at least one sensor for measuring data of an air quality parameter and a computer for storing the air quality parameter data received from the sensor. The air monitoring unit may use an installed or a portable system, or a combination of both, for measuring the air quality parameters of interest. A remote data centre may be provided, and the data may be uploaded to the data centre from the unit by a communications media such as the Internet. Information or instructions may also be downloaded from the data centre to the unit via the communications media for controlling or modifying the function of the unit. An expert system may be provided with the air monitoring system for controlling the unit. The information or instructions downloaded to the unit may be generated by the expert system.
[0005] Air pollution can damage crops and trees in a variety of ways. If air pollution is not controlled, the air will become poisonous that it will be necessary to use an oxygen kit to breathe easily. The proposed invention focuses on designing a framework of machine learning integrated with IOT to monitor and control air pollution.
[0006] Above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, no assertion is made, and as to whether any of the above might be applicable as prior art with regard to the present invention.
[0007] In the view of the foregoing disadvantages inherent in the known types of air pollution detection systems now present in the prior art, the present invention provides an improved system. As such, the general purpose of the present invention, which will be described subsequently in greater detail, is to provide a new and improved system to predict the air pollution using the algorithms of machine learning that has all the advantages of the prior art and none of the disadvantages.
SUMMARY OF INVENTION
[0008] In the view of the foregoing disadvantages inherent in the known types of air quality prediction systems now present in the prior art, the present invention provides an improved one. As such, the general purpose of the present invention, which will be described subsequently in greater detail, is to provide a new and improved machine learning based approach to analyze the air quality and predict the percentage of air pollution which has all the advantages of the prior art and none of the disadvantages.
[0009] The Main objective of the proposed invention is to design and implement a framework of ML to monitor the vehicle and air quality. The invention aims at predicting the air pollution and alerting the concerned official through IOT unit.
[0010] Yet another important aspect of the proposed invention is to design and implement a framework that a particular road is considered. The vehicles that pass through the particular road is monitored. The air quality and content of air pollution is predicted by predictive algorithms of ML unit. The IOT unit will send alert messages in the concerned official’s mobile phone.
[0001] In this respect, before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not limited in its application to the details of construction and to the arrangements of the components set forth in the following description or illustrated in the various ways. Also, it is to be understood that the phraseology and terminology employed herein are for the purpose of description and should not be regarded as limiting.
[0002] These together with other objects of the invention, along with the various features of novelty which characterize the invention, are pointed out with particularity in the disclosure. For a better understanding of the invention, its operating advantages and the specific objects attained by its uses, reference should be had to the accompanying drawings and descriptive matter in which there are illustrated preferred embodiments of the invention.
BREIF DESCRIPTION OF DRAWINGS
[0003] The invention will be better understood and objects other than those set forth above will become apparent when consideration is given to the following detailed description thereof. Such description makes reference to the annexed drawings wherein:
Figure 1 illustrates the schematic view of a machine learning and IOT based approach monitoring and prediction of Air Quality Pollution, according to the embodiment herein.
DETAILED DESCRIPTION OF INVENTION
[0004] In the following detailed description, reference is made to the accompanying drawings which form a part hereof, and in which is shown by way of illustration specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, and it is to be understood that the embodiments may be combined, or that other embodiments may be utilized and that structural and logical changes may be made without departing from the spirit and scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined by the appended claims and their equivalents.
[0005] While the present invention is described herein by way of example using several embodiments and illustrative drawings, those skilled in the art will recognize that the invention is neither intended to be limited to the embodiments of drawing or drawings described, nor intended to represent the scale of the various components. Further, some components that may form a part of the invention may not be illustrated in certain figures, for ease of illustration, and such omissions do not limit the embodiments outlined in any way. It should be understood that the drawings and detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the invention covers all modification/s, equivalents and alternatives falling within the spirit and scope of the present invention as defined by the appended claims. The headings are used for organizational purposes only and are not meant to limit the scope of the description or the claims. As used throughout this description, the word "may" be used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Further, the words "a" or "a" mean "at least one” and the word “plurality” means one or more, unless otherwise mentioned. Furthermore, the terminology and phraseology used herein is solely used for descriptive purposes and should not be construed as limiting in scope. Language such as "including," "comprising," "having," "containing," or "involving," and variations thereof, is intended to be broad and encompass the subject matter listed thereafter, equivalents, and any additional subject matter not recited, and is not intended to exclude any other additives, components, integers or steps. Likewise, the term "comprising" is considered synonymous with the terms "including" or "containing" for applicable legal purposes. Any discussion of documents, acts, materials, devices, articles and the like are included in the specification solely for the purpose of providing a context for the present invention.
[0006] In this disclosure, whenever an element or a group of elements is preceded with the transitional phrase "comprising", it is understood that we also contemplate the same element or group of elements with transitional phrases "consisting essentially of, "consisting", "selected from the group consisting of”, "including", or "is" preceding the recitation of the element or group of elements and vice versa.
[0007] Air pollution is the contamination of air due to the presence of substances in the atmosphere that are harmful to the health of humans and other living beings or cause damage to the climate or to materials. Both Human activity and natural processes can generate air pollution. Individual reactions to air pollutants depend on the type of pollutant a person is exposed to the degree of exposure and the individual’s health status and genetics.
[0008] Pollution prevention seeks to prevent pollution such as air pollution and could include adjustments to industrial and business activities such as designing sustainable manufacturing processes and related legal regulations. Also, the vehicles that pass through a particular road is monitored for air pollution.
[0009] Reference will now be made in detail to the exemplary embodiment of the present disclosure. Before describing the detailed embodiments that are in accordance with the present disclosure, it should be observed that the embodiment resides primarily in combinations arrangement of the system according to an embodiment herein and as exemplified in FIG. 1
[0010] Figure 1 illustrates the schematic view of a machine learning and IOT based approach monitoring and prediction of Air Quality Pollution 100. The proposed system 100 includes a Road 101 which is considered for analysis and monitoring. The vehicles that are moving on the road 101 are monitored through monitoring unit 102. The pollution analysis unit 103 will monitor the air quality and contents of air pollution. The data form unit 102 and 103 are fed as input to machine learning unit 104. The predictive algorithm will predict the air pollution that will be caused from road 101. The results of prediction 105 are analyzed by IOT unit 106. The alert messages from IOT unit 106 are sent to the mobile phone 107 of the concerned official.
[0011] In the following description, for the purpose of explanation, numerous specific details are set forth in order to provide a thorough understanding of the arrangement of the system according to an embodiment herein. It will be apparent, however, to one skilled in the art that the present embodiment can be practiced without these specific details. In other instances, structures are shown in block diagram form only in order to avoid obscuring the present invention.
, Claims:1. Machine learning and IOT based approach monitoring and prediction of Air Quality Pollution comprises of
machine learning unit;
pollution unit and
resultant unit.
2. Machine learning and IOT based approach monitoring and prediction of Air Quality Pollution, according to claim 1, includes a machine learning unit, wherein the machine learning unit will analyze the data sets of air quality and air pollution against the trained data set.
3. Machine learning and IOT based approach monitoring and prediction of Air Quality Pollution, according to claim 1, includes a pollution unit, wherein the pollution unit will measure the amount of pollution caused in a particular geographical location.
4. Machine learning and IOT based approach monitoring and prediction of Air Quality Pollution, according to claim 1, includes a resultant unit, wherein the resultant unit will store information regarding the air quality and air pollution.