IoT-Based DigitalTwin Frameworkfor environmentalmonitoring in theIndoor Environment:Design and Implementation
2022 (engelsk)Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hp
Oppgave
Abstract [en]
Purpose: This thesis aims to describe how to design and implement an IoT-Based digital twin framework for environmental monitoring in the indoor environment. To fulfill the purpose of the study, the following research question is answered. How to create a digital twin solution utilizing AWS to establish interaction and convergence between the physical environment in a classroom and the virtual environment?
Method: As a research method, the research has conducted design science research (DSR). DSR is a new method, and it is an effective tool for enhancing engineering education research methods.
Results: The study describes in detail the steps required to create the framework. The framework enabled interaction and convergence between the physical and virtual environments in a particular location.
Implications: The research contributes to broadening the knowledge on using the Internet of things (IoT), digital twin (DT), and Amazon web services (AWS). The study provides future research with reference data and a framework to build upon.
Research Limitation: Due to time constraints, the study's scope and limitations are limited to the technologies that the participating company, Knowit, provides. Knowit AB is a Swedish IT consulting company that supports companies and organizations with services in digital transformation and system development. The study aims to create an AWS-based IoT framework, not improve the digital twin concept. The framework was implemented at Jönköping University. This work is also limited to temperature and light intensity as environmental parameters.
sted, utgiver, år, opplag, sider
2022. , s. 49
Emneord [en]
Amazon web services (AWS), Cloud Computing, Digital Twin solution (DT), Environmental Data, Environmental Monitoring Sensors, IoT (Internet of Things), Smart Building.
HSV kategori
Identifikatorer
URN: urn:nbn:se:hj:diva-58010ISRN: JU-JTH-DTA-1-20220171OAI: oai:DiVA.org:hj-58010DiVA, id: diva2:1684189
Eksternt samarbeid
Knowit AB
Fag / kurs
JTH, Computer Engineering
Veileder
Examiner
2022-08-042022-07-212025-10-13bibliografisk kontrollert