EE100

Engineering Laboratory - Intelligent Sustainable Systems

Instructors

Instructor: Abubakr Muhammad, Hassan Jaleel

Email: abubakr@lums.edu.pk, hassan.jaleel@lums.edu.pk

Office: 2nd Floor, SBASSE Building

TA: Wasim Hassan

Email: wasim.hassan@lums.edu.pk 

Office: 9-257. Tesla Wing, 2nd Floor, SBASSE Building 

Course Description

The course introduces the use of systems engineering to solve problems related to sustainability. After familiarizing students with Matlab as the computational environment of choice, the lab course will take a top-down problem-oriented approach to teach students basic concepts in data handling and systems thinking. The students will be introduced to problems, applications, and case studies flavored from a wide variety of modern engineering domains, in particular those related to water, agriculture, and the environment. Moreover, students will be exposed to guest lectures in sister domains (such as biomedical engineering) where systems thinking is equally effective. In dealing with problems from these domains, students will learn to use Matlab for applying basic signals and systems techniques such as system modeling, filtering and smoothing, time-frequency analysis, design optimization, and closed-loop control, to name a few.

Course Details

Offering

  • Year: 2020-21
  • Semester: Spring
  • Open for Student Categories: Freshman
  • Credits Hours: 3

Prerequisites

  • None

Textbooks/Supplementary Readings

  • Original material; notes and Slides

Course Delivery

  • Teaching Methodology: All lab lectures will be conducted in a synchronous fashion.
  •  Lecture details: Lab lectures will be conducted live, but will be recorded and made available to students. All other interaction sessions (e.g., help sessions, office hours etc.) will also be live and in-person (if and when allowed by university policy).

Lecture Breakdown

Labs

Topics

Mode

Lab 1

 

Course Overview

  

Lab 2

 

Introduction to the Matlab (online) platform; signing up etc.
Matlab Onramp

  •  Entering Commands
  •  Naming, saving and loading variables
  •  Using built-in functions and constants
  • Matlab scripts
  • Arrays, matrices and associated operations
  • Programming constructs (if statements and for loops)

 

 

Lab 3

Visualizing and Analyzing Datasets
Data: Visualizing and Importing in MATLAB
Matlab Onramp

  • Plotting signals/data and visualization
  •  Importing data
  

Lab 4

Introduction to Systems Thinking: From Data to Models
First-order difference equations; choosing and interpreting time-constants;
Simulating and interpreting system inputs and outputs;
Application in agriculture

  • Modeling soil-moisture dynamics induced by rain
  

Lab 5

 

Collecting real-world Data: Understanding Sensors
Sampling, resolution, energy consumption in computing devices

  • Soil moisture sensors; weather stations
  • Optimizing battery design of environmental sensors
  

Lab 6

Making Decisions: Introducing Closed-Loop control
System interconnections; feedback; robustness; predictions;

  • Irrigation decisions with smart sensors
  • Using weather forecasts to minimize disturbances
  

Lab 7

Interpreting Cyclic Data: Time-Frequency Analysis
Frequency domain processing, Low-pass / High-pass filtering; understanding noise sources; modeling oscillators;

  • Understanding daily and yearly variations in hydrological and environmental phenomena.
  • Predicting cyclic variations in soil temperature, lake water levels, etc.
  

Lab 8

Acoustic Event Detection and Localization
Common Data Processing Techniques: Correlation, Event Detection

  • Tracking dolphins via echo-location
  • Acoustic event localization using time-difference-of-arrival
  

Lab 9

Biomedical Signal Processing
Common Data Processing Techniques: Smoothing, Peak Counting, Filtering

  • Estimating heart rate from PPG Data
  • SpO2 measurement

 

Lab 10

A Whirlwind Tour of Biomedical Imaging
Basic image processing techniques

  • Imaging application
  

Lab 11

From Lab to Practice: Socio-Technical Systems
Designing complex engineering systems; Human-in-the-loop Design; Social impacts of Engineering;

  • Irrigation infrastructures; water management; challenges
  • Understanding flow dynamics using simple models

 

 

Lab 12

Project 

  

Lab 13

Project (contd.)

  

Lab 14

Project (contd.)

  

 

 Dead week and review period  

 

 Final Examination