Iot Enabled Solutions For Monitoring And Management Of Smart And Sustainable Environment
| dc.contributor.guide | Pattanayak, B K and Pattnaik, Saumendra | |
| dc.coverage.spatial | ||
| dc.creator.researcher | Laha, Suprava R | |
| dc.date.accessioned | 2024-12-16T12:05:36Z | |
| dc.date.available | 2024-12-16T12:05:36Z | |
| dc.date.awarded | 2024 | |
| dc.date.completed | 2024 | |
| dc.date.registered | ||
| dc.description.abstract | The Internet of Things (IoT) has catalyzed a paradigm shift in global communication newlinenetworks, permeating diverse sectors and offering innovative solutions to pressing newlineenvironmental challenges. This thesis investigates the intersection of IoT technology and newlineenvironmental monitoring, presenting a series of groundbreaking frameworks and newlinecontributions to foster sustainability and enhance resource management practices. newlineOur first contribution introduces advanced environmental monitoring systems newlineempowered by IoT technology and sophisticated sensor modules. Through a newlinecomprehensive examination of air quality, water pollution, and waste management newlineresearch, we delineate distinct categories based on methodologies and findings, laying newlinethe groundwork for holistic environmental monitoring solutions. newlineBuilding upon this foundation, our second endeavor focuses on developing a Smart newlineWaste Management Framework. This framework integrates IoT and Long Range (LoRa) newlinetechnology to enable real-time monitoring of bin statuses and optimize garbage newlinecollection routes, thereby fostering sustainable waste management practices. Expanding newlineon this work, our third contribution extends into waste collection, route optimization, and newlinewaste management using RecycleCnn, achieving an exceptional accuracy rate of 98%. newlineTransitioning to water quality monitoring, our fourth work addresses the challenges newlineposed by contamination in the Mahanadi River. Leveraging IoT-based monitoring newlinesystems and the XGBoost machine learning model, we gain crucial insights into the newlinedynamics of water pollution, empowering the formulation of effective management newlinestrategies to sustain the river ecosystem. Cutting-edge technology facilitates real-time newlinedata collection on pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), newlinechemical oxygen demand (COD), and total coliforms (TC). The study delves into newlineintricate relationships between variables, geographical regions, belts, and seasonal newlinechanges, providing a nuanced understanding of the dynamics of water pollution. newlineIncorporating so | |
| dc.description.note | ||
| dc.format.accompanyingmaterial | DVD | |
| dc.format.dimensions | ||
| dc.format.extent | ||
| dc.identifier.uri | http://hdl.handle.net/10603/607191 | |
| dc.language | English | |
| dc.publisher.institution | Department of Computer Science | |
| dc.publisher.place | Bhubaneswar | |
| dc.publisher.university | Siksha O Anusandhan University | |
| dc.relation | ||
| dc.rights | university | |
| dc.source.university | University | |
| dc.subject.keyword | Computer Science | |
| dc.subject.keyword | Computer Science Artificial Intelligence | |
| dc.subject.keyword | Engineering and Technology | |
| dc.title | Iot Enabled Solutions For Monitoring And Management Of Smart And Sustainable Environment | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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