Data analysis and visualization

The field of health monitoring has undergone advancements shifting from long term methods to more frequent and integrated approaches. This change allows for an more understanding of an individual’s health. At the time the rise of Industry 4.0 has introduced the concept of digital twins. Virtual repl...

Full description

Saved in:
Bibliographic Details
Main Author: Tam, Kai Feng
Other Authors: Shen Zhiqi
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/173181
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary:The field of health monitoring has undergone advancements shifting from long term methods to more frequent and integrated approaches. This change allows for an more understanding of an individual’s health. At the time the rise of Industry 4.0 has introduced the concept of digital twins. Virtual replicas that are continuously updated with real world sensor data. This report explores the developments, in technology with a specific focus on its applications in smart manufacturing. It also delves into its capabilities, such as replication, real time synchronization and seamless integration throughout the lifecycle. The combination of twins and sensor data holds potential for transformation particularly in healthcare. We recognize the impact that twin technology can have on capturing, interpreting, and utilizing health information. With this recognition in mind our project aims to develop a web-based platform using Djangos ORM that enables visualization and analysis of sensor data from sources, within rooms of a house. This platform streamlines data collection, storage, retrieval, and filtering processes. Ultimately contributing to an understanding of environments.