This course explores the principles and practice of smart physical places and things (Smart-X). New devices have been added to cities, homes, factories, cars, and even to human (inside and out), hoping that this influx of technology will help us solve pressing societal issues in all facets of life such as energy, personal health, environment, or safety. The challenges, however, remain in designing and scaling the hardware platforms, networking protocols, and sensing algorithms to enable this new class of computing. This course will cover state-of-the-art research papers that address various visions of the future platforms supporting Smart-X. It will also stress the cyber physical aspects of these systems, providing safe, secure, and efficient interaction with the physical world. This course will offer significant hands-on experience through a semester-long project, paper critiques, lab sessions, and overview of the commercial landscapes of the topics covered in class.
This class is open to PhD and Master students as well as advanced undergraduate students. It would be helpful if you have taken a class in computer networks, embedded systems, mobile computing, or IoT. If you are not sure about the pre-requisites, please contact the instructor.
This class will cover the following topics with a focus on Smart-X:
|Week||Date||Day 1||Date||Day 2|
|1||08/23||Getting Started||08/25||What Makes "Things" Smart?|
|2||08/30||Basic of Embedded Computing
Sensors and Actuators
|09/01||Lab Session I
Speed Review Practice
|3||09/06||Smart City, Town, Street, & Beyond!
Commercial Landscape of Smart Cities
Low-power, wide-area, long-range...
Synchronization, Time, and Order
|09/15||Lab Session II
Reviewing Embedded Platforms: RPi, Arduino, MSP430
|5||09/20||Project Proposal Discussion||09/22||Project Proposal Discussion|
|6||09/27||Smart Manufacturing, Retail, Vehicle & Beyond!
Commercial Landscape of Smart Retails
|7||10/04||Real-time Communication||10/06||Lab Session III
Build a Smart Security Camera
|8||10/11||Smart Buildings: Residential, Commercial & Beyond!
Commercial Landscape of Smart Homes
|10/13||Extremely High Frequency
|9||10/18||Location, Location, Location!
Localization and Context Awareness
|10/20||Lab Session IV
RSSI-based Localization of Hidden Spying Cameras
|10||10/25||Midterm Project Presentation||10/27||Midterm Project Presentation|
|11||11/01||Smart Extended Reality: VR, AR, MR & Beyond!
Commercial Landscape of Mixed Reality Systems
|12||11/08||No Class (Election Day)||11/10||Lab Session V
Build an Augmented Reality Camera Finder App
|13||11/15||Smart Devices, Wearable, Objects & Beyond!
Commercial Landscape of Smart Wearables
|11/17||Extremely Low Power
|14||11/22||Fall Break||11/22||Fall Break|
|15||11/29||Learning to Perceive the World!
ML at the edge
|12/01||Future of Smart-X
|16||12/06||Final Project Demo||12/08||Final Project Demo|
The class requires three main deliverables from students:
Each lecture class will have a reading assignment which will be posed before the class. The students are expected to read the paper and submit a small summary including the intellectual merit, strengths and weaknesses of the paper. No late reading submission is allowed.
Every two-week period will explore a particular smart-X. The first day of the week will cover the application drivers and a commercial scan of the topic. The second and third day will provide a deep dive overview of underlying challenges and technologies. We will wrap up each smart-X with a lab session in the fourth day of the two-week period that offers in-class activities and hands-on experience through mini project.
Every student will lead at least one discussion in the class and can choose between a commercial landscape presentation or a research paper presentation. In your research paper presentation, try to answer the following questions:
In the commercial scan presentations, try to answer the following questions:
In the research project, you will get to build your own smart-X, ideally connecting the topics in this class with your own research. Students can form teams of 2 or 3 to execute on projects. The project checkpoints are as follows:
The intent of this section is to raise student and instructor awareness of the ongoing threat of bias and racism and of the need to take personal responsibility in creating an inclusive learning environment.
The Grainger College of Engineering is committed to the creation of an anti-racist, inclusive community that welcomes diversity along a number of dimensions, including, but not limited to, race, ethnicity and national origins, gender and gender identity, sexuality, disability status, class, age, or religious beliefs. The College recognizes that we are learning together in the midst of the Black Lives Matter movement, that Black, Hispanic, and Indigenous voices and contributions have largely either been excluded from, or not recognized in, science and engineering, and that both overt racism and micro-aggressions threaten the well-being of our students and our university community.
The effectiveness of this course is dependent upon each of us to create a safe and encouraging learning environment that allows for the open exchange of ideas while also ensuring equitable opportunities and respect for all of us. Everyone is expected to help establish and maintain an environment where students, staff, and faculty can contribute without fear of personal ridicule, or intolerant or offensive language. If you witness or experience racism, discrimination, micro-aggressions, or other offensive behavior, you are encouraged to bring this to the attention of the course director if you feel comfortable. You can also report these behaviors to the Bias Assessment and Response Team (BART) (https://bart.illinois.edu/). Based on your report, BART members will follow up and reach out to students to make sure they have the support they need to be healthy and safe. If the reported behavior also violates university policy, staff in the Office for Student Conflict Resolution may respond as well and will take appropriate action.