Essays about: "monitoring system process"

Showing result 1 - 5 of 312 essays containing the words monitoring system process.

  1. 1. Data analysis for predictive maintenance and potential challenges associated with the technology integration of steel industry machines.

    University essay from Högskolan i Gävle/Elektronik

    Author : Pradip Nath; [2024]
    Keywords : Data Science; Data processing; Industrial Manufacturing; System Identification; Predictive maintenance; Conditional monitoring; Statistical Analysis; Signal processing; Hydraulic System; IoT; Sustainable Maintenance; Data vetenskap; Databehandling; Industriell tillverkning; System identifiering; Prediktivt underhåll; Tillståndsövervakning; Statistisk analys; Signal behandling;

    Abstract : The recharge is the focus of data analysis of the different situations with the integration of the system and development of the two-stage 2/2 proportional cartridge valve for the steel industry machine. Using the statistical analysis technique to visualize the valve signal data behavior identify the accuracy of the machine data and apply the statistical feature extracting model using classification and clustering algorithms of real-time data analysis for the manufacturing. READ MORE

  3. 2. Iot-based Saline Volume Monitoring and Alert System

    University essay from Blekinge Tekniska Högskola

    Author : Kotti Dinesh; Narendra Velpula; [2023]
    Keywords : IoT; MIT App Inventor; NodeMCU; Saline Monitoring; and ThingSpeak.;

    Abstract : This project presents a comprehensive study on the design and implementationof an Internet of Things (IoT)-based system for monitoring and alerting salinevolumes in healthcare environments.Background: In healthcare settings, the accurate monitoring of saline volumesin Intravenous (IV) drip systems is crucial for ensuring patient safety and effectivetreatment. READ MORE

  4. 3. Production of natural pigments from A. platensis grown on wastewater from local treatment facility.

    University essay from Lunds universitet/Teknisk mikrobiologi; Lunds universitet/Bioteknik

    Author : Hana Faulds; [2023]
    Keywords : Cyanobacteria; pigments; microalgae; wastewater treatment; biotechnology; Technology and Engineering; Biology and Life Sciences;

    Abstract : Although microalgae have been considered for the biological treatment of wastewater since the 1950’s, their potential to efficiently remove pollutants from various streams remains largely untapped and is yet to be utilized at large scale. The production of algal biomass and extraction of high-value compounds has, however, become increasingly popular with large scale farms and biorefineries around the world producing many promising alternatives to petroleum-based products and processes. READ MORE

  5. 4. Anomaly Detection in the EtherCAT Network of a Power Station : Improving a Graph Convolutional Neural Network Framework

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Niklas Barth; [2023]
    Keywords : Unsupervised Learning; Multivariate Time Series; Graph Convolutional Neural Networks; Anomaly Detection; Industrial Control System; EtherCAT; Power Station; Electricity Grid;

    Abstract : In this thesis, an anomaly detection framework is assessed and fine-tuned to detect and explain anomalies in a power station, where EtherCAT, an Industrial Control System, is employed for monitoring. The chosen framework is based on a previously published Graph Neural Network (GNN) model, utilizing attention mechanisms to capture complex relationships between diverse measurements within the EtherCAT system. READ MORE

  6. 5. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods

    University essay from KTH/Fysik

    Author : Jeanette Marie Victoria Skeppland Hole; [2023]
    Keywords : ECG; ECG-analysis; QRS detector; Artificial Intelligence; Machine Learning; Deep neural networks; Long short-term memory; Convolutional neural network; Multilayer perceptron; EKG; EKG-analys; QRS detektor; Artificiell intelligens; Maskininlärning; Djupa neurala nätverk; Long short-term memory; Convolutional neural network; Multilayer perceptron;

    Abstract : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). READ MORE