Essays about: "Interactive Anomaly Detection"

Found 3 essays containing the words Interactive Anomaly Detection.

  1. 1. Automating Root Cause Analysis of Anomalies in Ericsson Wallet Platform using Machine Learning

    University essay from Blekinge Tekniska Högskola

    Author : Simron Padhi; Devi Priya Battina; [2023]
    Keywords : Anomaly detection; Isolation forest algorithm; K-means algorithm; Local Outlier Factor algorithm; One class Support Vector Machine;

    Abstract : Background: In this era of mobile wallet platforms, to ensure key requirements like high availability and performance, the company must have mechanisms in place to detect anomalies at any given point in time. Ericsson Wallet Platform(EWP), a mobile wallet platform, is facing the problem of manually analyzing all the logs and reports and taking comprehensive action decisions accordingly. READ MORE

  3. 2. Enabling Smartphones to act as IoT Edge Devices via the Browser-based ’WebUSB API’ : The future of the browser and the smartphone in home electronics IoT systems

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

    Author : Ruben Lindström; [2021]
    Keywords : IoT; Edge Device; Smartphone; WebUSB API; Browser; Home Electronics; IoT; Edge Device; Smartphone; WebUSB API; Webbläsare; Hemelektronik;

    Abstract : This degree project proposes a novel architecture for IoT systems, utilizing smartphones as edge devices and running the value-creating software such as preprocessing, anomaly detection, and deriving data-based insights in the web browser as opposed to natively on the device. Utilizing the smartphone as an edge device reduces cost of adoption for IoT technologies since less hardware has to be included in the system compared to bundling a device for processing with the system. READ MORE

  4. 3. Interactive Anomaly Detection With Reduced Expert Effort

    University essay from Högskolan i Halmstad

    Author : Lingyun Cheng; Sadhana Sundaresh; [2020]
    Keywords : Interactive Anomaly Detection; Outlier Detection; User Feedback; Expert Effort;

    Abstract : In several applications, when anomalies are detected, human experts have to investigate or verify them one by one. As they investigate, they unwittingly produce a label - true positive (TP) or false positive (FP). READ MORE