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COMP_SCI 396, 496: Mobile and Ubiquitous Computing


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Prerequisites

No prerequisite. Basic courses like CS 110, CE 203 would be helpful, but not needed.

Description

Mobile and ubiquitous computing represents the third generation of computing—characterized by interconnected systems seamlessly embedded within the environment and integrated with human activities. These computing systems operate in the background, while enhancing everyday experiences. This course introduces students to the principles and technologies that underpin mobile and ubiquitous computing and wearables, including sensing, computation, and communication, which together enable seamless and continuous interaction. This is a fun class with lectures, labs and a group project. Students will gain hands-on experience by working on practical projects that address real-world challenges, leveraging mobile and ubiquitous computing to develop innovative solutions. In addition to building a strong technical foundation, the course will emphasize designing, deploying, and evaluating mobile and ubiquitous computing systems in real-world contexts.  

Course Objectives:
  • This course will help you creatively apply CS/CE knowledge learned in HCI, systems, networking, algorithms, and AI courses to real-world IoT or Wearable Computing applications, or vice versa, provide a reason to study your other CS/CE courses more deeply.
  • Develop a strong foundation in mobile and ubiquitous computing and their practical applications.
  • Evaluate the capabilities of various mobile and wearable computing components to make informed decisions about their suitability and technical constraints.
  • Leverage mobile and ubiquitous computing techniques to address real-world challenges.
  • Analyze and critically engage with the principles of the third generation of computing—Mobile and Ubiquitous Computing.
  • Apply mobile and ubiquitous computing methods in innovative, real-world scenarios.
Course Topics:
  • History of Ubiquitous Computing: Famous personalities and example technologies
  • Sensors and sensor data analysis including applied machine learning
  • Location and networking technologies: GPS, BLE, LoRa
  • Wearable computing: Challenges and design processes
  • Context aware computing
  • IoT Low-power and energy harvesting technologies
  • Evaluation of mobile and ubiquitous computing systems
  • Privacy in mobile and ubiquitous computing
  • Real world applications: health, biodiversity monitoring, urban infrastructure etc.

Grades:
  • Class participation: 10%
  • Individual Assignment: 10%
  • Group Labs/Activities: 30%
  • Quizes: 20%
  • Projects (Proposal, video presentation, report, demo): 30%


  • This course fulfills the Technical Elective area.
  • This course cross-list with CE 395-3/CE 495-3.

Course Coordinator: Prof. Arora
Course Instructor: Prof. Nivedita Arora