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 MX in Internet of Things & Embedded Systems

MX in Internet of Things & Embedded Systems

All candidates for the MX in Internet of Things & Embedded Systems must satisfy the overall requirements of KFUPM in addition to the following:

a)      The general requirements for the professional Master are as follow:

  1. A Grade-Point Average (GPA) of 2.5 or higher on a scale of 4.00
  2. Completion of TOFEL with a minimum score of 525 (PBT), 194 (CBT) or 70 (IBT). IELTS is also acceptable with a minimum of 6.0. (TOEFL is not required for Students who graduated from KFUPM)
  3. At least two letters of recommendation

b)      The technical backgrounds needed for Admission are:

  1. B.SC degree in Computer Engineering, Computer Science, Software Engineering, Electrical Engineering, or Control and Instrumentation System Engineering, or related fields.
  2. Basic knowledge in Programming.
  3. Basics of mathematics and Probability and Statistics.

Satisfying the minimum admission requirements does not guarantee admission into the program, as final admission is subject to an evaluation of the entire application, and the personal interview. Based on the assessment of the applicant file and the personal interview, the admission committee might offer conditional acceptance for students who need to take deficiency courses.

The MX in Internet of Things & Embedded Systems consists of 9 core courses from different disciplines.

Core Courses

Sr.Course Code and Title
1COE 515: Introduction to Smart Systems
2COE 550: Introduction to Internet of Things
3SCE 548: Industrial Internet of Things
4COE 558: Cloud and Edge Computing
5SWE 555: Embedded Software Engineering
6ICS 574: Big Data Analytics
7COE 597: Real-Time Systems
8COE 516: Internet of Things Security
9COE 619: Project

Course Description

COE 515: Introduction to Smart Systems (3-0-3)

Introduction to smart systems. Sensors and actuators: working principles, classifications, performance, characteristics, interfacing with feedback control, and data acquisition. Embedded systems: types, architectures, memory management, and interfacing. Concurrency: software and hardware interrupts, timers. Embedded operating systems: components, considerations, configuration, and resource management. Embedded systems integration and programming, profiling and code optimization. Power management and energy harvesting.

Prerequisite: Graduate Standing

COE 550: Introduction to Internet of Things (3-0-3)

IoT systems design and architecture: elements of IoT system, potentials, constraints, and applications. IoT access technologies. IoT networking protocols such as 6LoWPAN. IoT application layer protocols such as MQTT and CoAP, Wireless Personal Area Network (WPAN) such as ZigBee. Low Power Wide Area Network (LPWAN) such as LoRaWAN. IoT network architecture: cloud, fog, and edge layers.

Prerequisite: Graduate Standing

SCE 548: Industrial Internet of Things (3-0-3)

Internet of Things (IoT) technology and Industrial Control Systems (ICS) for Industry 4.0, IoT/IIoT reference architectures and data flow, industrial communication technologies and networking protocols, highly distributed system architectures and computing platforms, digital twins, ICS security, predictive analytics, maintenance, and system optimization. Embedded intelligence in end devices to perform local analytics and optimization. Applications of IIoT in various areas such as energy sector, manufacturing, and smart cities.

Prerequisite: Graduating Standing

COE 558: Cloud and Edge Computing (3-0-3)

Internet   and web protocols and technologies. Basics of web development: frontend, backend, and full-stack. Web services and RESTful APIs. Introduction to utility computing: Cloud and Edge computing. Cloud Service-oriented architecture and microservices. The XaaS pyramid. Serverless computing. Cloud resource management. Automated deployment and operations techniques. Virtualization and containerization. Cloud data storage: block storage, object storage, and file storage. Cloud "Big data" processing : MapReduce and Hadoop, Spark, BigTable. Cloud-native applications. Security of Cloud computing.

Prerequisite: Graduate Standing

SWE 555: Embedded Software Engineering (3-0-3)

Software development process, software specification and modeling techniques, software architecture and design for embedded & IoT systems, software construction and implementation guidelines, software testing techniques, software quality for embedded & IoT systems, safety-critical software development for embedded & IoT systems, security for embedded & IoT systems, and software development tools.

Prerequisite: Graduate Standing

ICS 574: Big Data Analytics (3-0-3)

Introduction and foundation of big data and big-data analytics. Sources of big data. Smart clouds. Hadoop file system and Apache Spark. Storage management for big data. Machine learning and visualization with big data. Applications of big data. Big data and security, privacy, societal impacts.  

Prerequisite: Graduate Standing

COE 597: Real-Time Systems (3-0-3)

Introduction to real-time systems, concurrency and timing constraints, real-time programming: task model and specification, event loop, never-ending tasks, periodic and aperiodic tasks, thread synchronization, inter-task communication, synchronization, memory management, scheduling: rate-monotonic scheduling, EDF, resource sharing, priority inheritance, sporadic servers, multiprocessor scheduling, reliability and fault tolerance. Digital feedback control systems as example RTS, implementation strategies, sampling rate and effect of task scheduling on control latency, case studies.

Prerequisite: COE 515 or Consent of Instructor

COE 516: Internet of Things Security (3-0-3)

Introduction to security principles and technologies related to the Internet of Things (IoT) and its components: devices, operating systems, sensors, data storage, networking and communication protocols, and system services. IoT vulnerabilities, attacks and mitigation techniques. Hands-on and case studies.

Prerequisite: Graduate Standing

COE 619: Project (0-0-6)

A graduate student will arrange with a faculty member to conduct an industrial project related to their field of the study in professional master degree. Subsequently the students shall acquire skills and gain experiences in developing and running actual industry-based project. This project culminates in the writing of a technical report, and an oral technical presentation in front of a board of professors and industry experts.

Prerequisite: Graduate Standing.

Degree Plan

Course #
TitleLTLBCR
Fall Semester ​ ​ ​ ​ ​
COE
515Introduction to Smart Systems303
COE
550Introduction to Internet of Things303
SWE555Embedded Software Engineering303
ICS574Big Data Analytics303
 12012
Spring Semester ​ ​ ​ ​ ​
SCE548
Industrial Internet of Things303
COE558Cloud and Edge Computing303
COE597Real-Time Systems303
COE619Project00IP
 909
Summer Semester ​ ​ ​ ​ ​
COE516Internet of Things Security
303
COE619Project006
 309
Total Credit Hours ​ ​ ​ ​30

Course Flow Chart

Course Flow Chart-MX in IoT and ES.png

Degree Plan-MX in IoT and Embedded Systems.pdf

Course Flow Chart-MX in IoT and ES.pdf

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