Abstract
Internet of Things (IoT) is a new vision of an integrated network covering physical objects that are able to collect and exchange data. It enables previously unconnected devices and objects to become connected using equipping devices with communication technology such as sensors and radio frequency identification tags (RFID). As technology progresses towards new paradigm such as IoT, there is a need for an approach to identify the significance of these projects. Conventional simulation modeling and data analysis approaches are not able to capture the system complexity or suffer from a lack of data needed that can help to build a prediction. Agent-based Simulation (ABM) proposes an efficient simulation scheme to capture the structure of this dimension and offer a potential solution. Two case studies were proposed in this research. The first one introduces a conceptual case study addressing the use of agent-based simulations to verify the effectiveness of the business model of IoT. The objective of the study is to assess the feasibility of such application, of the market in the city of Orlando (Florida, United States). The second case study seeks to use ABM to simulate the operational behavior of refrigeration units (7,420) in one of largest retail organizations in Saudi Arabia and assess the economic feasibility of IoT implementation by estimating the return on investment (ROI).
Notes
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Graduation Date
2017
Semester
Fall
Advisor
Rabelo, Luis
Degree
Doctor of Philosophy (Ph.D.)
College
College of Engineering and Computer Science
Department
Industrial Engineering and Management Systems
Degree Program
Industrial Engineering
Format
application/pdf
Identifier
CFE0006855
URL
http://purl.fcla.edu/fcla/etd/CFE0006855
Language
English
Release Date
12-15-2018
Length of Campus-only Access
1 year
Access Status
Doctoral Dissertation (Open Access)
STARS Citation
Basingab, Mohammed, "A Methodology for Internet of Things Business Modeling and Analysis using Agent-Based Simulation" (2017). Electronic Theses and Dissertations. 5721.
https://stars.library.ucf.edu/etd/5721