Environmental monitoring with the help of Internet of Things (loT) and machine learning

Environmental monitoring with the help of Internet of Things (loT) and machine learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Bibliografische gegevens
Hoofdauteurs:	Alam, Md. Sakirul, Ahsan, Farshid, Sarker, Anik
Andere auteurs:	Islam, Md. Motaharul
Formaat:	Thesis
Taal:	English
Gepubliceerd in:	Brac University 2021
Onderwerpen:	IoT Air monitoring Multi-Layer Perception Principal Com- ponent Analysis Long Short Term Memory Machine Learning Internet of Things
Online toegang:	http://hdl.handle.net/10361/14636

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Implementation of machine learning to estimate the air pollutants such as Carbon dioxide, methane, nitrous oxide and total greenhouse gas emissions in Bangladesh
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The application of Internet Of Things (IoT) to the traditional power grid
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Investigation of energy harvesting in Cognitive Internet of Things (CIOT) network
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Implementation of an IoT based home automation system using real time sensors
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Air pollution monitoring system for smart city
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IoT based maternal health risk detection system
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IoT based medicine dispenser for improving medication adherence
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IoT based brain-wave assistive system for paralyzed individuals
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A highly efficient solar powered IoT based irrigation system
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Real time traffic analysis using decentralized SIOT
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Modeling and simulation of a gas detecting device for providing safety; and reducing the risk of accidents due to gas explosion or fire
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Fog based service oriented IOT infrastructure
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Machine learning based data processing and latency reduction in the internet of things for agriculture
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IoT based real-time synchronized clock
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Multi-layer security analysis and implementation of smartphone based ATM
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Investigation of cognitive wireless and power line network using internet of things
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IoT based automated entry system with integration of Covid-19 symptom detection
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IoT based smart biofloc monitoring and maintenance system
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