Document Type

Closed Project

Publication Date

Spring 2017

Instructor

Ramin Neshati

Course Title

Decision Making

Course Number

ETM 530/630

Abstract

We’re entering a new era of computing technology that many are calling the Internet of Things (IoT) and its foundation is the intelligence that embedded processing provides. Integrated Microcontroller devices, which can provide the “real-time” embedded processing is a key requirement of most IoT applications. However the task of selecting the appropriate Microcontroller for an IoT application is more difficult than it seems. Traditional microcontroller selection and management practices are inadequate. This paper proposes a new methodology of selecting a Microcontroller for an IoT application. A hierarchical decision model (HDM) is utilized in the decision making activity and qualified expert's opinions are used as measurements. There are four levels in the hierarchy: objective, criteria, sub-criteria, and alternatives. Expert panel is formed based on their background and expertise in order to minimize and balance any possible biases among the members. The criteria, sub-criteria and alternatives are evaluated and prioritized, according to their contribution to the objective, by quantifying the expert’s judgments. The results are validated using Inconsistency measure for the reliability of the experts and group agreement. The final decision from this new model will help in better selection methodology for assisting embedded designers to make the right decision and select the most suitable Microcontroller required for the design from the large pool of the Microcontrollers available in the market. This model can be improved in any future work by including other criteria maintainability, flexibility, Scalability, adding more alternatives and more expert panels.

Description

This project is only available to students, staff, and faculty of Portland State University

Persistent Identifier

http://archives.pdx.edu/ds/psu/21431

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