CIVIL 763 : Smart Infrastructure Analytics

Engineering

2022 Semester Two (1225) (15 POINTS)

Course Prescription

Develops fundamental knowledge in the use of computer programming and data analytics to solve real-world infrastructure problems, such as reducing traffic congestion, predicting water usage and infrastructure failures. Group and independent projects are undertaken in which students study complex smart infrastructure analytics problems using real-world data.

Course Overview

Data analytics is an essential skill in modern engineering where all disciplines now involve large-scale data collection and digitalisation. A key challenge is how can we manage this ‘big data’ and analyse it to exploit useful information and insights that can guide decision making.

This paper will equip postgraduate students with interests in infrastructure engineering, such as construction, transportation, traffic, water engineering and urban analytics with data analytics skills to handle real-world data challenges. It does not require any in-depth prior knowledge in programming or data analytics but will provide students with the knowledge of the popular tools and the critical thinking skills to apply the core theories in data analytics to solve a range of engineering problems with elements of ambiguity and complexity.

For real-world relevance, the course will utilise real datasets from a range of New Zealand infrastructure owners/operators such as local councils, and government departments. These will further be accompanied by relevant guest lectures from industry and academia.

Upon finishing the course, the students will feel confident in writing small programs to analyse large datasets, identify patterns and insights from the data that will improve decision-making process and choose the right tools, algorithms and methods to solve common data analytics problems in infrastructure engineering.

Course Requirements

No pre-requisites or restrictions

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity
Capability 6: Social and Environmental Responsibilities

Learning Outcomes

By the end of this course, students will be able to:
  1. Write Python programming code using popular tools such as Jupyter Notebook (Capability 1)
  2. Evaluate and apply theories and tools from computer science, data science and statistics to create information, knowledge and innovative solutions in engineering (Capability 1, 2 and 3)
  3. Analyse the suitability and limitations of data analytics tools, algorithms, and platforms for real-world infrastructure engineering problems (Capability 1, 2 and 3)
  4. Apply cutting-edge techniques from large-scale data mining, machine learning and statistical analysis through assignments and a final project (Capability 1, 2, 3, 4 and 5)
  5. Apply statistical and geospatial data visualisation techniques to communicate and visually represent their findings to both technical and non-technical audiences (Capability 4, 5 and 6)

Assessments

Assessment Type Percentage Classification
Assignments 50% Individual Coursework
Project 40% Individual Coursework
Presentation 10% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4 5
Assignments
Project
Presentation
There is no exam for this course. The students will be assessed on their ability to program in Python to understand real-world datasets and present their results to non-technical audience. 

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect an average weekly workload comprising 3 hours of lectures, 1 hour of pre-reading before the class, and 6 hours for working on Jupyter Notebooks, exercises, assignments and final project. 

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities. Lectures will be available as recordings.

The course will include live online events including group discussions and tutorials.

The activities for the course are scheduled as a standard weekly timetable.

This course will be delivered in a unique blended learning model. During lectures, students will be learning and practising in "live coding" sessions with computers in either MDLS Computer Labs at the University of Auckland or using their personal computer, where they can discuss and learn from other students. 



Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Health & Safety

Students are expected to adhere to the guidelines outlined in the Health and Safety section of the Engineering Undergraduate Handbook.

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 06/01/2022 06:47 p.m.