Dataset for anomalies detection in 3D printing

04/19/2020
by   Joanna Sendorek, et al.
0

Nowadays, Internet of Things plays a significant role in many domains. Especially, Industry 4.0 is making a great usage of concepts like smart sensors and big data analysis. IoT devices are commonly used to monitor industry machines and detect anomalies in their work. In this paper we present and describe a set of data streams coming from working 3D printer. Among others, it contains accelerometer data of printer head, intrusion power and temperatures of the printer elements. In order to gain data we lead to several printing malfunctions applied to the 3D model. Resulting dataset can therefore be used for anomalies detection research.

READ FULL TEXT
research
10/04/2022

Detecting Anomalies within Smart Buildings using Do-It-Yourself Internet of Things

Detecting anomalies at the time of happening is vital in environments li...
research
11/18/2022

Intrusion Detection in Internet of Things using Convolutional Neural Networks

Internet of Things (IoT) has become a popular paradigm to fulfil needs o...
research
10/06/2022

Network Intrusion Detection System in a Light Bulb

Internet of Things (IoT) devices are progressively being utilised in a v...
research
02/02/2021

Real-time detection of uncalibrated sensors using Neural Networks

Nowadays, sensors play a major role in several contexts like science, in...
research
04/22/2021

An Efficient One-Class SVM for Anomaly Detection in the Internet of Things

Insecure Internet of things (IoT) devices pose significant threats to cr...
research
06/09/2022

Smart System: Joint Utility and Frequency for Pattern Classification

Nowadays, the environments of smart systems for Industry 4.0 and Interne...
research
05/10/2020

Correct and Control Complex IoT Systems: Evaluation of a Classification for System Anomalies

In practice there are deficiencies in precise interteam communications a...

Please sign up or login with your details

Forgot password? Click here to reset