Internet of Things
DISCLAIMER
Before purchasing, review the rules of your licensing or certifying entity. It is your responsibility to confirm this course meets your CE requirements. See the credit tab on the course page for details.
What’s Included: Full webinar recording, written course materials, expert instruction, a mandatory quiz, and a certificate upon completion.
Deliverability Timeline: All courses are generally available within 1-2 weeks after the live presentation.
CE Credits: AIA and/or LA/CES accreditation is available by request for courses recorded prior to March 11, 2026. All courses after that date include those accreditations by default, if applicable. With these accreditations, our courses qualify for credit in nearly all states for engineers, surveyors, architects, and landscape architects.
Learn more about the on-demand format in our FAQ or contact us at (715) 835-5900 or customerservice@halfmoonseminars.org
Agenda
Registration: 8:00 – 8:30 am
Morning Session: 8:30 – 11:45 am
Lunch (On your own): 11:45 am – 12:45 pm
Afternoon Session: 12:45 – 4:00 pm
RFID Sensing Applications for Internet of Things
H. Li
Understanding daily activities by detecting user object interactions
Enhancing localization of COTS radio frequency identification (RFID) leveraging other sensing modalities
Fabricating lightweight, battery-free, tangible interfaces combining COTS RFID with conductive ink printing
Enabling Powerful IOT Applications Using Computer Vision
J. Fromm
Enabling powerful IOT applications using computer vision; what needs to be done to state of the art algorithms to make them practical?
Binarization of convolutional neural nets and other optimizations
Guide to designing custom IOT computer vision applications
Looking forward: CNNs on FPGAs
Smartphone as a Multipurpose Health Monitor
E. Wang
Measuring health more like we measure the weather: comprehensively, frequently, and predictively
Smartphone as a multipurpose health monitor to reduce cost and coverage
Measuring properties of the blood using the smartphone camera
Wearables as a new way to continuously track blood pressure and activities
How our lifestyle can change with a more predictive healthcare
Smartphone as a Multipurpose Health Monitor (Part 2)
A. Mariakakis
An inexpensive, unpowered hardware attachment that enables non-expert physicians to measure intraocular pressure
Using convolutional neural networks and a 3D-printed box to allow EMTs and football team doctors
to measure pupil dilation as a proxy for traumatic brain injury
Using computer vision and a custom pair of color-calibration glasses to measure jaundice in the eye more precisely than a human can
Opportunities for other senses to be quantified using smartphones and other embedded sensors
Credits
Continuing Education Credit Information
This seminar is open to the public and offers 6.0 PDHs to professional engineers in all states. Continuing education is not mandatory for license renewal in Washington.
HalfMoon Education is an approved continuing education sponsor for engineers in Florida, Indiana, Louisiana, Maryland, New Jersey (Approval No. 24GP00000700), New York (NYSED Sponsor No. 35), North Carolina, and North Dakota. All other states with continuing education requirements do not preapprove educators or courses.
Attendance will be monitored, and attendance certificates will be available after the seminar for most individuals who complete the entire event. Attendance certificates not available at the seminar will be mailed to participants within fifteen business days.
Speakers
Josh Fromm
University of WashingtonPhD student, University of WashingtonMr. Fromm is a PhD student in Electrical Engineering at the University of Washington. His work focuses on enabling computer vision algorithms on commodity hardware such as the Raspberry Pi. He also is interested in developing novel applications that leverage these technologies. Previously, Mr. Fromm worked on ultra low power system design.
Hanchuan Li
University of WashingtonPhD student, University of WashingtonMr. Li is a PhD student in Computer Science and Engineering at the University of Washington. His research focuses on creating user-centered, context-aware Internet of Things applications leveraging passive sensing technology. More specifically, he is interested in creating tangible interfaces, locating and identifying objects and users, and understanding everyday activities through combining commercial off-the-shelf radio frequency identification with conductive ink printing, signal processing, machine learning, and computer vision. Mr. Li received the Qualcomm Innovation Fellowship and the Disney Research Scholarship for his graduate study.
Alex Mariakakis
University of WashingtonPhD student, University of WashingtonMr. Mariakakis is a PhD student in Computer Science and Engineering at the University of Washington. He develops mobile health diagnostic applications that quantify qualitative measurements, particularly focusing on conditions related to the eye. Mr. Mariakakis’ work has been published at top-tier conferences like ACM CHI and UbiComp. Previously, he worked on indoor localization, including work that has been patented and commercialized by HP. Mr. Mariakakis is an NSF Graduate Research Fellow.
Edward Wang
University of WashingtonPhD student, University of WashingtonMr. Wang is a PhD student in Electrical Engineering at the University of Washington. He develops novel health monitoring technologies that are cheaper, easier to disseminate, and more capable of continuous monitoring by leveraging everyday devices like phones, watches, and glasses. Mr. Wang’s work spans from monitoring conditions in the blood to tracking daily activities. He is an NSF Graduate Research Fellow.