Water quality monitoring using machine learning and Internet Of Things (IoT)

Water quality monitoring using machine learning and Internet Of Things (IoT)

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021.

Bibliografiske detaljer
Main Authors:	Rahman, Naveed, Nir, Riaz Uddin Ahmed, Tithi, Saila Hasan, Shupti, Baishakhi Rani Das
Andre forfattere:	Mohsin, Abu S.M.
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2021
Fag:	Water quality monitoring(WQM) Water pollution pH TDS Turbidity Machine learning and future prediction Machine learning Internet of things
Online adgang:	http://hdl.handle.net/10361/14935

Lignende værker

Smart measurement of water quality parameters and monitoring fish health
af: Talukder, Ali Ahmed Rezvee, et al.
Udgivet: (2021)

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
af: Tasnim, Anika, et al.
Udgivet: (2022)

Fault detection and predictive maintenance in IoT-based building management system using machine learning
af: Sabuj, Khaja Sheikh Imran, et al.
Udgivet: (2022)

Flood monitoring and warning system for embankment using IoT
af: Dutta, Aparup, et al.
Udgivet: (2022)

Botnet detection In IoT devices using machine learning
af: Rouf, Shakir, et al.
Udgivet: (2020)

A classification and prediction based approach for real-time ETP outlet monitoring through E-IoT and remote sensing using machine learning and deep learning
af: Hossain, Md. Mehedi, et al.
Udgivet: (2021)

Bio-sorption studies of chromium (VI) ions with modified chicken feathers
af: Shaima, Nabila Afrin
Udgivet: (2022)

Machine learning as an indicator for breast cancer prediction
af: Shadman, Tahsin Mohammed, et al.
Udgivet: (2019)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
af: Toufique, S.M, et al.
Udgivet: (2024)

Use of machine learning and weather predictions to bridge the gap between consumer demands and the market requirements of food crops
af: Hasan, Raad, et al.
Udgivet: (2021)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
af: Alhossen, Md., et al.
Udgivet: (2021)

IoT based automated entry system with integration of Covid-19 symptom detection
af: Ruhin, Rubaiyat Alam, et al.
Udgivet: (2024)

An effective real-time flood disaster management with automated GSM warning system
af: Faruk, Omar, et al.
Udgivet: (2024)

IoT based air components collection for machine learning reinforcement
af: Islam, Tanjima, et al.
Udgivet: (2024)

Anomaly detection In IoT using machine learning algorithms
af: Arko, Aritro Roy, et al.
Udgivet: (2019)

Predicting climate induced floods using machine learning
af: Saleh, Chowdhury Nafis, et al.
Udgivet: (2022)

Explainable artificial intelligence and model calibration for water quality prediction
af: Hellen, Nakayiza
Udgivet: (2022)

Investigation assistant with suspect anticipating intelligence
af: Abdullah, Saqueeb, et al.
Udgivet: (2019)

Developing a machine learning based prognostic model and a supporting web-based application for predicting the possibility of early diabetes and diabetic kidney disease
af: Amin, M.M. Shahriar, et al.
Udgivet: (2021)

Health monitoring IoT device with risk prediction using cloud computing and machine learning
af: Das, Anindya, et al.
Udgivet: (2021)

Weather Pattern Extraction using Statistical Methods & Machine Learning Techniques
af: Habib, Adria Binte
Udgivet: (2021)

An implementation and analysis of deep learning models for the detection of wheat diseases
af: Zubair, Ahmad, et al.
Udgivet: (2024)

Identification of multi drug resistant bacteria from local fresh juice and industrially processed juice
af: Abanti, Rifah Tasnia, et al.
Udgivet: (2023)

Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
af: Islam, Zahedul, et al.
Udgivet: (2023)

Demystifying second hand car market in Bangladesh using multimodal machine learning techniques
af: Islam, Roman, et al.
Udgivet: (2024)

Use of machine learning and IoT for monitoring and tracking of livestock
af: Aunindita, Rudaba Farhin, et al.
Udgivet: (2023)

Intrusion of Malware (DDoS) detection in IoT devices using Machine Learning on Cyberspace
af: Al Amin, Istiak, et al.
Udgivet: (2022)

Forecasting Dhaka stock exchange prices using machine learning models: a Performance analysis
af: Alam, Md. Iftekharul, et al.
Udgivet: (2024)

N.P.K. based crop suggesting model
af: Iftekher, Asif, et al.
Udgivet: (2020)

Application of CNN based architectures in detection of distracted drivers
af: Arafin, Irfana, et al.
Udgivet: (2023)

Emotion analysis using machine learning model and deep learning model on DEAP dataset
af: Hasan, Anita, et al.
Udgivet: (2022)

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
af: Ahmed, Md. Sabbir, et al.
Udgivet: (2021)

Machine learning based data processing and latency reduction in the internet of things for agriculture
af: Rahman, Sajeed Ur, et al.
Udgivet: (2019)

Exploration of yeast candida zeylonoides with special references to probiotic activity isolated from mozzarella cheese
af: Shamshad, Ritwika
Udgivet: (2021)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
af: Maliha, Miftahul Zannat, et al.
Udgivet: (2023)

A counseling system to predict the study path for freshmen
af: Usha, Rowshni Tasneem, et al.
Udgivet: (2019)

Share market forecasting with LSTM neural network and sentimental trend prediction
af: Rony, Ismail Hossain, et al.
Udgivet: (2020)

Heart disease prediction using machine learning algorithms
af: Ali, Musfiq, et al.
Udgivet: (2019)

Machine learning for stress prediction
af: Salehin, Sherajus, et al.
Udgivet: (2023)

Enhancing underwater object detection through water artifact removal and using ensemble transfer learning
af: Saikat, Nayem Hossain, et al.
Udgivet: (2024)