Course syllabus

Course-PM

MMS210 Connected fleets in data-driven engineering - lp4 (7.5 hp)

The course is offered by the Department of Mechanics and Maritime Sciences.

Contact details

Please contact the course staff for any further questions about the teaching or course subjects. If a meeting is required, please make contact by email to request an appointment (during office hours).

Examiner and lecturer

Ola Benderius, 031-772 2086, ola.benderius@chalmers.se

Teaching assistant

Tarun Kadri Sathiyan, tarun.sathiyan@chalmers.se

Study administrator

Jamal Nasir, jamal.nasir@chalmers.se

Course purpose

The purpose of the course is to aid engineers in data-driven decisions connected to vehicle features and development. By also adding continuous experimentation and remote system monitoring, the course will be vital in engineering processes around functional safety. Finally, as fully connected fleets also represent structural changes to transportation in society, it also includes deep and thorough discussion around automated data-collection connected to human activities, as a way to shift previous collect-all strategies into sound ethical engineering principles as endorsed by our governments through recent legislation such as GDPR. 

Course design

The course consist of lectures, group work/discussion, and a lab assignment including field work. In the lectures the theoretical parts will be covered which will provide the students with a broad overview of the subject area. Then, the students are expected to apply the knowledge from the lectures in the group work/discussion and the lab work. The exercises involves instruction for the lab assignment and related field work.

The group work sessions are mandatory, as well as the lab work. All parts are graded by submitted reports.

Note: Group work and lab field work needs to be done on-site. Remote presence will not be accepted.

Schedule

TimeEdit

Lectures:

Mon	24/3	10:00-11:45	HC2	Lecture 1: Introduction
Mon	31/3	10:00-11:45	HC2	Lecture 2: Data-driven engineering
Mon	7/4	08:00-09:45	HC2	MOVED TO 30/4
Wed	9/4	10:00-11:45	HC2	Lecture 3: Connected fleets frontend–backend
EASTER
Mon	28/4	08:00-09:45	HC2	Lecture 4: DevOps and software engineering with connected fleets
Wed	30/4	10:00-11:45	HC2	Guest lecture: Building the boats of tomorrow using AIS
Mon	5/5	13:15-15:00	HC2	Lecture 5: Data enrichment and sensor fusion
Mon	12/5	10:00-11:45	HC2	Lecture 6: Introduction to cybersecurity and ethics
Mon	19/5	10:00-11:45	HC2	Lecture 7: Operational design and data-driven requirements engineering
Mon	26/5	10:00-11:45		NO TEACHING, FOCUS ON LAB REPORT

Exercises/Lab work:

Wed	26/3	10:00-11:45	HC2	Exercise 1: Forming groups, project proposal
Wed	2/4	10:00-11:45	HC2	Exercise 2: Handing out hardware, initial tests and enclosure
Mon	7/4	10:00-11:45	HC2	Exercise 3: WIP project presentations
EASTER
Wed	23/4	10:00-11:45	HC2	Exercise 4
Mon	28/4	10:00-11:45	HC2	Exercise 5
Mon	5/5	10:00-11:45	HC2	Exercise 6
Wed	14/5	10:00-11:45	HB2	Exercise 7
Wed	21/5	10:00-11:45	HC2	Project presentations
Wed	21/5	13:15-15:00	HC2	Project presentations
Wed	28/5	10:00-11:45		NO TEACHING, FOCUS ON LAB REPORT

Group work:

Wed	26/3	13:15-15:00	HC2	Group work 1
Wed	2/4	13:15-15:00	HC2	Group work 2
Wed	9/4	13:15-15:00	HC2	Group work 3
EASTER
Wed	23/4	13:15-15:00	HC2	Group work 4
Wed	7/5	13:15-15:00	HA3	Group work 5
Wed	14/5	13:15-15:00	HA3	Group work 6
Wed	28/5	13:15-15:00		NO TEACHING, FOCUS ON LAB REPORT

Course literature

Lecture notes, source code templates, and web material. The material will be made available via the course web page.

Learning objectives and syllabus

• Apply large-scale fleet monitoring, and describe involved technologies and how logged data can be used in the engineering process
  Describe properties of hardware components needed in each unit of a connected fleet, including their software life-cycles.
• Describe properties of core software components needed in a backend environment, connected to the engineering process.
• Apply and monitor over-the-air updates to a fleet of mobile systems, and describe limitations from different underlying technologies.
• Apply software development connected to continuous integration and continuous deployment in heterogeneous ECU networks.
• Describe relevant cybersecurity measures to safeguard the connected fleet and the its generated data.
• Describe ethical aspects of fleet monitoring and over-the-air updates, and how such concepts can be combined with ethical engineering related to governmental intentions as defined by, for example, GDPR.
• Define complete engineering process involving all learning outcomes from the course.

Examination form

The examination consists of graded lab work, and a series of group work.

See the following subsections for details regarding assessment and grading. Refer also to the below section regarding plagiarism and the use of tools such as ChatGPT.

Grades

The grades that are given in this course are the following: 5, 4, 3, U (not passed).

Lab assignment including field work

The mandatory lab assignment will be carried out in groups of 4-5 students, where each group focuses on one specific type of vehicle (e.g. ferry, bicycle, e-scooter, car, truck, tram, train, drone) chosen by the students (with some set conditions from the course examiner). The lab involves field work that is scheduled by each group separately. Groups are responsible to acquire access to relevant vehicles for field measurements, but in special cases the course staff can provide help. Measurements should ONLY be done on vehicles in normal and safe traffic conditions, and relevant driver's licenses should be ensured! A report explaining the work process and work outcome, including pictures from active field work showing all group members, should be submitted before the deadline, and will be graded with 3, 4, or 5. A minimum grade of 3 is required in order to pass the course. The lab assignment correspond to 60% of the final course grade. For late submissions, the grade may be affected. Groups can be suggested by students, but the examiner will ultimately decide group compositions based on vehicle selection.

Group work

There are six scheduled mandatory group work/discussion in the course. The group work correspond to 40% of the final course grade, where the five best results are averaged. The groups will be randomized, and different every time. To pass you need to attend at least five group assignments. The grade of the group work is the mean grade on all group submissions. After each group discussion, two groups will be selected on random to present their key points in class. Each group work session is outlined as: 10 min introduction, 60 min of discussion and report writing (including break), 20 min of wrap up and student presentations (two groups).

Final course grade

The student’s final course grade will be determined according to the grade of the lab work (3, 4, or 5) and the mean grade of the five best exercises (3, 4, or 5), combined as 0.6*<lab assignment> + 0.4*<group work mean>. The resulting value, rounded to the nearest integer value, is the final individual grade of the course.

Regarding plagiarism

Briefly, plagiarism occurs when someone present ideas, concepts, texts, or other structures from someone else, as their own. I.e. without appropriately acknowledging the original source. See further in the document about Academic integrity and honesty at Chalmers (link).

The reports (and other submitted materials such as e.g. programming code) should be original work in order to be passed. Therefore, all reports and texts that you submit for grading and examination will be checked with Ouriginal, a tool to detect plagiarism.

Avoid using tools like ChatGPT without understanding the underlying principles. It's very likely that you will get errors in your solution by trusting such tool. If you use such tools, you MUST document and submit ALL dialogue with the bot, and how the answers were incorporated in your solution.

Note: All suspected cases of plagiarism (not only those detected by Ouriginal) will be reported to the university disciplinary committee (disciplinnämnden)!