Sensors , Data, and Intelligent Systems

Course philosphy

This course addresses the emergence of sensors “smart” systems across science and engineering. We will learn how sensors, internet-connected devices, and real-time data analytics are being used to build “smart” cities, smart homes, robots, and a new generation of scientific experiments. Students will acquire practical and theoretical knowledge of sensing technologies, with the ability to directly apply these modern tools to their projects or interests. Sensor physics will be discussed to illustrate how physical processes can be measured through electrical signals and converted to digital information. Extensive theory behind leading sensing technologies and data acquisition systems will be discussed. Large-scale wireless sensor networks will be covered and we’ll talk about data can be transmitted to the Internet. We will also learn about signal processing and practical machine learning methods to analyze and act upon data collected by sensor networks.


date description
9.3.19 Syllabus
9.3.19 Intro Slides
9.17.19 Resistive Sensors Notes
9.17.19 Resistive Sensors Slides
9.30.19 Capacitive Sensors Notes
9.30.19 Capacitive Sensors Slides
11.12.19 Inductive Sensors Notes
11.12.19 Inductive Sensors Slides
11.12.19 4_Piezoelectric Sensors Notes
11.12.19 4_Piezoelectric Sensors Slides
11.12.19 Misc. Sensors Slides
11.12.19 ADCs Notes
11.12.19 ADCs Slides
11.12.19 Fourier Analysis Notes
11.12.19 Fourier Analysis Slides
11.12.19 Fourier Series Typed Notes
11.12.19 Fourier Transform Typed Notes


post date due date
Oct 1, 2019 HW1
Oct 23, 2019 HW2
Nov 5, 2019 HW3


There is no required textbook. Notes will be provided. Here are some additional resources that may be useful throughout the semester:

- Lyons Richard, Understanding Digital Signal Processing, Third Edition (free online through UM)
-Fraden, Jacob (2006) AIP Handbook of Modern Sensors, 2nd. edition. AIP Press; Springer. (free online through UM)
- Van Putten A.F.P. (1996) Electronic Measurement Systems, 2nd. edition; Institute of Physics Publishing.
- Karl, J.H. (1989) An Introduction to Signal Processing; Academic Press.
- Nyce David (2004), Linear Position Sensors - Theory and Application (free online through UM)
- The Measurement, Instrumentation and Sensors Handbook (free online through UM)
- Carl Rasmussen (2006), Gaussian Processes for Machine Learning, MIT Press (free online access).
- Jordan (2009), Practical machine learning, Course Notes.
- Raginsky Maxim (2008), Signals and Systems, Course Notes.

post notes
More on thermocouples by pyromation, PDF
Thermocouple theory and selection by Omega, PDF
Strain gage positioning by Omega, PDF
Strain gage theory and selection by Omega, PDF
Geotechnical load cells
General load cells
external links
ADXL Theory
Selecting accelerometers
More on selecting accelerometers
Measuring capacitance
Fiberoptic strain measurements
Solar radiation measurements
Sonic anemometers
More op-amps
Delta sigma ADCs
On ADC noise

Times and Location

Mon. and Wed. 11:30AM - 1PM, 2153 GGB


Office Hours

Tue. 2-3PM and Thu. 4PM-5PM, but I generally have an open door policy (or can meet by appointment).