AU2021101214A4 - Air pollution monitoring system using iot and machine learning - Google Patents
Air pollution monitoring system using iot and machine learning Download PDFInfo
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- AU2021101214A4 AU2021101214A4 AU2021101214A AU2021101214A AU2021101214A4 AU 2021101214 A4 AU2021101214 A4 AU 2021101214A4 AU 2021101214 A AU2021101214 A AU 2021101214A AU 2021101214 A AU2021101214 A AU 2021101214A AU 2021101214 A4 AU2021101214 A4 AU 2021101214A4
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0031—General constructional details of gas analysers, e.g. portable test equipment concerning the detector comprising two or more sensors, e.g. a sensor array
- G01N33/0034—General constructional details of gas analysers, e.g. portable test equipment concerning the detector comprising two or more sensors, e.g. a sensor array comprising neural networks or related mathematical techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0073—Control unit therefor
- G01N33/0075—Control unit therefor for multiple spatially distributed sensors, e.g. for environmental monitoring
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y20/00—Information sensed or collected by the things
- G16Y20/10—Information sensed or collected by the things relating to the environment, e.g. temperature; relating to location
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
- H04W84/10—Small scale networks; Flat hierarchical networks
- H04W84/12—WLAN [Wireless Local Area Networks]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
- Y02A50/20—Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters
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Abstract
AIR POLLUTION MONITORING SYSTEM USING IOT AND MACHINE
LEARNING
Aspects of the present disclosure relate to system (100) which is used for monitoring air
5 pollution using IoT and machine learning. The system (100) employs array or plurality of
sensor for collecting the data related to the gas level in the environment and process that data
and send back to the central server wirelessly as the system (100) is IoT enabled. The
pollution levels are increasing due to the development that stereotypically occurs as
countries become technically advanced and urbanized. Cumulative air pollution level leads
10 to many hazards such as global warming, acid rains, skin and Chronic Obstructive
Pulmonary Disease, etc. The present system (100) can help over come the air pollution by
providing better tool for analysis.
(FIG. 1 will be the reference figure)
100 102
Main Power Module
106
110
SGPS Module eno
Array
Arduino Board
SWiFi
104 Communication
Module
108
15 FIG. 1 IoT block diagram
-9-
Description
[0001] The present disclosure relates to a air pollution monitoring system and in particular to the air pollution monitoring system using IoT and machinelearning.
[0002] The pollution levels are increasing due to the development that stereotypically occurs as countries become technically advanced and urbanized. Cumulative air pollution level leads to many hazards such as global warming, acid rains, skin and Chronic Obstructive Pulmonary Disease, etc.
[0003] Over time people have become more energy-conscious. Because of this, the construction industry started building structures that are far "tighter" than their predecessors, with respect to air leakage. Buildings are now carefully designed to provide occupants with a precisely metered exchange between indoor and outdoor air. The exchange between indoor and outdoor air is selected to provide a healthy quality of indoor air, with a minimum of energy usage for heating or cooling the outdoor air introduced into the building. However, inevitably the tradeoff sometimes results in unacceptable indoor air quality. Moreover, the use of new building materials having many superior and desirable properties in both renovations of old buildings and new construction sometimes aggravates the air quality problems because the building materials outgas undesirable substances.
[0004] With respect to air quality in the home or in schools, incidence rate of asthma, which is often triggered by poor indoor air quality, is growing exponentially. It has more than doubled since the eighties, with the current level of 17 million American sufferers projected to double again in two decades. A recent national survey reported that 56% of all households now contain at least one member with allergies or asthma. In all, over 90 million Americans are reported sufferers of asthma or allergies, with direct costs of about $19 billion annually for medical care, pharmaceuticals, and asthma and allergy products. For example, air cleaners are now one of the fastest growing household products, with over 16 million households using at least one unit. Particular aspects of indoor air quality are a concern, such as toxic molds, dust mites, carbon monoxide poisoning, allergens, and various chemical pollutants.
[0005] Millions of people are believed to die prematurely due to air pollution and it is the world's largest environmental health hazard as discussed by the World Health Organization (WHO). Highly industrialized cities like Beijing and New Delhi often experience high Air Quality Index (AQI) values. Reducing air pollution has an additional benefit of mitigating exorbitant healthcare costs. According to the statistics obtained from the World Health Organization, in 2012, the indoor air pollution deaths accounts of 3.3 million and 2.6 million deaths linked to outdoor air pollution.
[0006] In order to avoid such situations, monitoring of the quality of air in atmosphere is highly required. Air quality monitoring is a systematic approach for observing and studying the condition of environment. The purpose of monitoring the air quality is not only to collect the data but also provide the information which is required by the researchers to make a decision on developing and managing the environment.
[00071 Extensive systems and methods are applied to estimate the harmful gases to mitigate the environmental pollution. Nowadays, the air quality monitoring systems using wireless communication modes are said to be more expensive. A Chinese patent CN105243632A describes about the cloud management-based air pollution monitoring system. It consists of an air pollution monitoring unit,4cloud data management unit and a mobile station control unit' From the pollution monitoring unit, by using the sensors. the level of the pollution is monitored and the collected data are stored in the cloud data management unit. By using mobile station monitoring unit the real time data's can be continuously monitored. This invention has a mobile station control unit, which may require manual intervention, thus increasing cost of the application.
[00081 Another patent US489096932 describes about the air quality monitoring in indoors. By using gas sensors, the quality of the air is detected and also machine learning technique is used as artificial intelligence in this method. The selected data from the sensors are stored in a cloud server. The existing system proposes implementation of the system only in indoors.
[0009] Another prior-art U820170300818A1 describes about the pollution monitoring system with acoustic sensor to estimate pollution level by using the sound of an automobile and a trained exhaust gas model unit, and then the data is stored in the cloud server. In this system, machine learning is arranged to train an exhaust gas model using a machine learning algorithm. thus obtaining a trained exhaust gas model. The proposed system uses gas sensors which provide more accurate pollution level measurement, rather than the acoustic sensors used in this system. Also, this system is aimed mainly for motor vehicle-based implementation.
[0010] Beyond the use of an industrial hygienist employing sophisticated air measurement instruments, there have been only limited options to help the building owner or occupant obtain information about the air quality of their environment. One such device is described in U.S. Pat. No. 5,553,006. This patent discloses a system that is limited to gathering air quality data and transmitting the data through a network, serial interface or phone line to a user. There are also systems, as discussed in U.S. Pat. No. 5,892,690, that gather air quality data from a building and then send the data through the Internet to a customer accessible website, where it is archived and available to the customer in graphically displayed form. Although convenient for a customer, there is no analysis of the data, nor is there any way for the system to adapt its operation or to be customized automatically based on the specific building being measured or the data that is gathered. U.S. Pat. No. 6,125,710 discloses a networked air measurement system and describes a method for inexpensively gathering air quality or environmental data. However, it does not describe any methods for customizing the data taking process to a given building or analyzing the data that is taken.
[0011] Some available devices measure and data log some environmental air parameters and then send emails to a customer based on predetermined levels being exceeded, but do not take into account anything more sophisticated in their analysis of the data. Nor do these devices employ any method to reprogram or modify the testing program remotely. U.S. Pat. No. 4,226,115 describes an outdoor air monitoring device, held aloft by a balloon, that employs remote radio wave communication for triggering the taking of a sample of ambient air. However, this device is not designed for indoor use, requires intervention of a trained operator to decide when to take the sample and involves expensive technology with limited range due to the use of radio wave communication for transmission to the device.
[0012] It is an object of the present disclosure which provides a monitoring and recording the concentration of gases and other parameters using novel gas sensors.
[0013] It is an object of the present disclosure which provides a system to store information in cloud database.
[0014] The present concept of the present invention is directed towards a monitor the gas level in polluted environments, especially automobiles and industrial emissions which can be achieved with the help of Internet of Things (IoT) and Machine learning.
[0015] In another aspect, An air pollution monitoring system to monitor the gas levels in polluted environment using IoT devices and machine learning, wherein the system comprises of: a main power module, wherein the main power module powers the system; a microcontroller unit, wherein the microcontroller controls all the process in the system, wherein the microcontroller unit comprise of an Arduino board; a communication module, wherein the communication module facilitates the communication, wherein the communication module comprises of a GPS module and WIFI communication module; a sensor array, wherein the sensor array comprises atleast a gas sensor, wherein the gas sensor can sense the gases present in the environment.
[00161 FIG. 1 illustrates an IoT block diagram.
[0017] FIG. 2 illustrates total IoT system block diagram.
[0018] In an embodiment of the present disclosure, FIG. 1 illustrates an exemplary system (100) overview. The system (100) comprises of a microcontroller (104) unit, a communication module, a main power module (102), a sensor array (110).
[0019] In an aspect of the present invention, the power module can be used to power the system (100). The power module can have maximum input voltage of 18V and a maximum of 90 Amps and it can also be capable of providing 5.37V and 2.25 Amp power supply to the microcontroller (104).
[0020] In yet another aspect of the present invention, the microcontroller (104) unit can be Arduino UNO V3.
[0021] In yet another aspect of the present invention, the communication module comprises of a GPS (106) module and a WIFI (108) communication module where the WIFI (108) communication module can be ESP8266 WIFI (108).
[0022] In yet another aspect of the present invention, the sensor array (110) can comprise of plurality of sensors and atleast gas sensor. The gas sensor can be MQ2 gas sensor.
[0023] In yet another aspect of the present invention, the microcontroller (104) can have the capacity to provide power by connecting a few modules into the board hear the pertinent sensors can be appended and the fundamental codes are given in a header so when speaking with the WIFI (108) module no problem must be finished.
[00241 In yet another aspect of the present invention, the microcontroller (104) has the assistance for some modules accessible in the market yet the issue is that the Arduino board doesn't have any driving module in this examination we have utilized another different controlling module to the gadget so as to flexibly the force as per the fundamental prerequisites of the modules.
[0025] In yet another aspect of the present invention, GPS (106) module was joined to the microcontroller (104).
[00261 In yet another aspect of the present invention, the minimal effort ESP8266 WIFI (108) communication module was utilized in this framework as the correspondence module. This Module had the option to associate with the WIFI (108) passages in city and send information to the unified worker.
[00271 In yet another aspect of the present invention, in the Arduino code there is a header to send all the information as indicated by the clients wish so the code was wrapped and could be effortlessly utilized with some random number of modules.
[00281 In yet another aspect of the present invention, the communication module and the sensor array (110) can be electronically coupled with the microcontroller (104) unit, wherein the microcontroller (104) unit can control the communication module and the gas sensor.
[0029] In yet another aspect of the present invention, FIG. 2 illustrates total IoT system block diagram which comprises of Server, where the code was written in Python where the information was sent to the Python Server Socket the attachment at that point made a string and put away the sent information. This worker is likewise can be redone by the code and new boundaries could be included into the database and the database additionally could be extended.
[00301 In yet another aspect of the present invention, the server is very flexible and many parameters are easily added or removed according to the users need.
[00311 In yet another aspect of the present invention, the information was sent by the individual WIFI (108) modules set everything straight by the worker and put away in the database for the further use.
[0032] In yet another aspect of the present invention, cloud computing services can be deployed the services IoT, Machine Learning and Web Service Interface.
[00331 In yet another aspect of the present invention, Al programming does the expectation of the air contamination levels utilizing the directed learning. This was finished utilizing python and tensorflow Al bundle to make the diagram of the forecast of a given area.
[0034] In yet another aspect of the present invention, the straight relapse was utilized generally in stock value expectation, and thusly, it was additionally utilized in this undertaking to plot the chart and anticipate the air contamination factors.
[00351 In yet another aspect of the present invention, the liner relapse is a measurement-based Al calculation and the air contamination focus change was thought to be straight when they change. It was the best fit line of the plotted chart and the line could be utilized to anticipate the qualities
[00361 In yet another aspect of the present invention, the system (100) is used to predict the air pollution and helps government and organization in city planning.
Claims (5)
1. An air pollution monitoring system (100) to monitor the gas levels in polluted environment using IoT devices and machine learning, wherein the system (100) comprises of:
A main power module (102), wherein the main power module (102) powers the system (100);
A microcontroller (104) unit, wherein the microcontroller (104) controls all the process in the system (100), wherein the microcontroller (104) unit comprise of an Arduino board;
A communication module, wherein the communication module facilitates the communication, wherein the communication module comprises of a GPS (106) module and WIFI (108) communication module;
A sensor array (110), wherein the sensor array (110) comprises atleast a gas sensor, wherein the gas sensor can sense the gases present in the environment.
2. The system (100) as claimed in claim 1, wherein the said cloud computing services has deployed the services IoT, Machine Learning and Web Service Interface.
3. The system (100) as claimed in claim 1, wherein the communication module and the sensor array (110) is electronically coupled with the microcontroller (104) unit, wherein the microcontroller (104) unit control the communication module and the gas sensor.
4. The system (100) as claimed in claim 1, wherein the server is very flexible and many parameters are easily added or removed according to the users need.
5. The system (100) as claimed in claim 1, wherein the system (100) is used to predict the air pollution and helps government and organization in city planning.
Application no.: Total no. of sheets: 2 Applicant name: Page 1 of 2 08 Mar 2021 2021101214
FIG. 1 IoT block diagram
Application no.: Total no. of sheets: 2 Applicant name: Page 2 of 2 08 Mar 2021 2021101214
FIG. 2 total IoT system block diagram
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| AU2021101214A AU2021101214A4 (en) | 2021-03-08 | 2021-03-08 | Air pollution monitoring system using iot and machine learning |
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| AU2021101214A AU2021101214A4 (en) | 2021-03-08 | 2021-03-08 | Air pollution monitoring system using iot and machine learning |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113252851A (en) * | 2021-05-19 | 2021-08-13 | 安徽理工大学环境友好材料与职业健康研究院(芜湖) | Atmospheric pollution monitoring system based on NB-IoT and edge calculation |
-
2021
- 2021-03-08 AU AU2021101214A patent/AU2021101214A4/en not_active Ceased
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113252851A (en) * | 2021-05-19 | 2021-08-13 | 安徽理工大学环境友好材料与职业健康研究院(芜湖) | Atmospheric pollution monitoring system based on NB-IoT and edge calculation |
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