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http://hdl.handle.net/10603/475804
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DC Field | Value | Language |
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dc.coverage.spatial | A study in identification of an optimized framework for pollution free path using wireless sensor network | |
dc.date.accessioned | 2023-04-12T12:02:12Z | - |
dc.date.available | 2023-04-12T12:02:12Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/475804 | - |
dc.description.abstract | Air pollution is a combination of airborne solid particles and gases. Car emissions, factory chemicals, dust; pollen and mold spores may be suspended in the form of particles. As it leads to many adverse effects on human health, ecosystems and the climate, air pollution is both an environmental and social problem. The most important factor directly influencing the incidence of diseases and reducing the quality of life is the air quality in cities and urban areas. Making appropriate decision-making promptly depends on the measurement and analysis of air parameters, which creates the need for real-time air quality monitoring development. The use of multi-parameter monitoring systems for air quality enables a detailed level analysis of major pollutants and their sources to be carried out. In many smart city projects, these monitoring systems are important components for monitoring the air quality and controlling the main concentrations of pollutants in urban areas. These works has considered three specific problems in air pollution monitoring and have come up with appropriate solutions to overcome these issues. The objectives include finding a) Optimal path identification based on air quality index and other related parameters under the condition of air pollution, b) As the data grows in size, there is a need for effective big data processing using different models. Main research motive is to analysis the pollution nodes across the city and select the pollution less nodes for routing application. By harnessing the combined power of hybrid cloud computing and big data analytics, areas with bad air quality and possible action solutions can now be found. Current monitoring systems are inferior inaccuracy, have low sensitivity and require laboratory examination. Therefore, improved monitoring systems are required that provides a low cost and real-time monitoring system using the Internet of Things (TOT) technology newline | |
dc.format.extent | xv,158p. | |
dc.language | English | |
dc.relation | p.147-157 | |
dc.rights | university | |
dc.title | A study in identification of an optimized framework for pollution free path using wireless sensor network | |
dc.title.alternative | ||
dc.creator.researcher | Preethi, K | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Information Systems | |
dc.subject.keyword | pollution free | |
dc.subject.keyword | wireless sensor | |
dc.subject.keyword | optimized framework | |
dc.description.note | ||
dc.contributor.guide | Tamilarasan, R | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2021 | |
dc.date.awarded | 2021 | |
dc.format.dimensions | 21cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 244.54 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.68 MB | Adobe PDF | View/Open | |
03_content.pdf | 202.67 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 1.92 MB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 395.96 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 1.12 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 1.54 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.51 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.31 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 121.53 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 91.36 kB | Adobe PDF | View/Open |
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