CS546: Introduction to Agriculture Cyber Physical Systems
Semester II, 2020-21

 

Course Information Lectures/Calendar Project Labs

Course Information

Instructors

Dr. Mukesh Saini (Email: mukesh@iitrpr.ac.in)
Dr. Neeraj Goel (Email: neeraj@iitrpr.ac.in)

Lectures

Thu-Fri, 12:00 to 12:50 PM

Labs

TBA

Tutorials

None

Contents

Introduction to crop life cycle, precision agriculture, and CPS, Proximal sensing, Proximal sensing applications, No-contact proximal sensing and applications, Remote sensing and applications, Communication technologies, Global Navigation Satellite System, Agriculture robots, Autonomous vehicles, Robot applications in sowing and harvesting, AI/ML for pest identification, AI/ML for weed identification, Agriculture information system - applications, Case studies.

Outcomes

The main objective of this course is to introduce the cyber physical system applications in the field of agriculture, including sensing, analysis, and control.

Prerequisite

Basic programming knowledge.

Course Requirements

Student are required to attend two lectures per week and appear in two exams. In addition, there will be lab sessions, quizzes, and project. The lab assignments will be design and/or implementation based.

Grading Policy

There will be approximately 3 lab assignments, approximately 3 quizzes, a mid-sem exam, an end-sem exam, a project, and a seminar. The tentative grade distribution is as follows:
Quizzes: 10%
Lab assignments: 10%
Project: 25%
Mid-sem exam: 20%
End-sem exam: 30%
Seminar: 5%
A student must score at least 30% marks to pass the course.

Attendance Requirement

In online mode, there is no attendance requirement. In offline mode, minimum attendance requirement is 75%. Each lecture, and lab will count as one unit irrespective of the contact hours. The students with attendance less that 75% will get an 'F' grade.

Code of Ethics & Professional Responsibility

It is expected that students who are taking this course will demonstrate a keen interest in learning and not mere fulfilling the requirement towards their degree. Discussions that help the student understand a concept or a problem is encouraged. However, each student must turn in original work. Plagiarism/copying of any form, will be dealt with strict disciplinary action. This involves, copying from the internet, textbooks and any other material for which you do not own the copyright. Copying part of the code will be considered plagiarism. Lending the code to others will be considered plagiarism too, for it is difficult to investigate who copied whose code. Students who violate this policy will directly receive a failing grade in the course. Remember - Your partial submission can fetch you some points, but submitting other's work as your own can result in you failing the course. Please talk to the instructor if you have questions about this policy. All academic integrity issues will be handled in accordance with institute regulations.

Textbooks

  1. Shannon, D. K., Clay, D. E., & Kitchen, N. R. (2020). Precision agriculture basics (Vol. 176). John Wiley & Sons. [Link].
  2. Song, H., Rawat, D. B., Jeschke, S., & Brecher, C. (Eds.). (2016). Cyber-physical systems: foundations, principles and applications. Morgan Kaufmann. [Link].

Language/Tools

C/C++/Python/Matlab. Students will be mostly free to choose programming language according to their convenience.

Teaching Assistant

Pratibha Kumari (Email: 2017csz0006@iitrpr.ac.in)

Contact Me

By appointment.

Lectures and Calendar

Lectures Week Tipics Readings Events
L1, 2 Jan 27- Jan 29 Introduction to crop life cycle, precision agriculture, and CPS
Feb 2 - 6 Proximal sensing
Feb 8 - 12 Proximal sensing applications in irrigation
Feb 15 - 19 No-contact proximal sensing and applications Quiz 1, Online, 3- 3:50 PM, Tuesday
Feb 22 - 26 Remote sensing and applications Lab assignment 1 deadline
Mar 1 - 5 Communication technologies Project proposal due
Mar 8 - 12 Global Navigation Satellite System Quiz 2, Online, Online, 3- 3:50 PM, Tuesday
Mar 15 - 19 Autonomous vehicles Lab assignment 2 deadline
Mar 22 - 26 Mid semester examination
Mar 29 - Apr 2 Agriculture robots
Apr 5 - 9 Robot applications in sowing and harvesting
Apr 12 - 16 AI/ML for pest identification
Apr 19 - 23 AI/ML for weed identification
Apr 26 - 30 Agriculture information system - applications Quiz 3, Online, 3- 3:50 PM, Tuesday
May 3 - 7 Case studies
May 7 - 16 End semester examination

*This is a tentative list of topics that will be covered during the semester. The topics and schedule can change according to the need at the discretion of the instructor.

Project

Project is an extremely important part of this course. The projects can be done individually or in a group of 2 (max). Each project design would contain sensing, communication, analysis, and control. Depending on the scope of the work, we can discuss and reduce the scope of the project in the development phase. Further instructions:

  • Each teaam needs to submit the project proposal around mid-semester. Try to be as creative and wild in design as possible. There are 10% marks just for the creativity or innovativeness of the project.
  • There will be multiple weekly evaluations of the project.
  • There will be a final design expo where you have to publically demonstrate you product.

Labs

The labs will be mostly about data analysis (collection part is omitted due to online mode). You will be asked to implement analysis algorithms and system prototypes for agriculture applications.