DESC9673: Semester 2, 2023

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Units DESC9673 Semester 2 2023 [Block mode]

Unit outline_

DESC9673: Intelligent Building Control Systems

Semester 2, 2023 [Block mode] - Camperdown/Darlington, Sydney

Overview

The term 'intelligent buildings' was coined some thirty years ago with the advent of Direct Digital Controls (DDC), but only recently can buildings can truly be considered 'intelligent' thanks to advances in sensor technology, control systems theory, information technology, and electronics in general. This unit presents an overview of intelligent buildings from the Building Management and Control System (BMCS) perspective, focusing specifically on Heating Ventilation Air Conditioning (HVAC) processes, plus other building services including security, lighting, and vertical transportation. Fundamentals of control systems theory and technology will be presented. State-of-the-art BMCS capabilities will be demonstrated in relation to optimising the environmental, workplace productivity and economic performance of buildings. Sustainability issues covered by the unit include the role of BMCS in monitoring and managing energy and carbon footprint, water resources and indoor environmental quality (IEQ). The learning outcomes of this unit of study will include sufficient understanding of building controls to enable optimum building performance. It will also provide a platform for critical analysis of control and operational strategies adopted through techniques such as diagnostics and trend logging of parameters such as energy, water, temperature, humidity, to mention a few.

Unit details and rules

Academic unit	Architectural and Design Science
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Chirag Deb, chirag.deb@sydney.edu.au
Lecturer(s)	Simon Mahoney, smah7135@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Discuss the basics of an Intelligent Building Management System (IBMS) and evaluate the potential benefits of using IBMS in buildings. Written assessment	40%	Week 08 Due date: 18 Sep 2023 at 23:59	2000 words
Outcomes assessed:
Assignment	Design and develop an iPython file which encompasses data acquisition, time series analysis, a simple control system and plotting. Programme files	60%	Week 13 Due date: 30 Oct 2023 at 23:59	n/a
Outcomes assessed:

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2021 (Schedule 1).

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	1.Introduction to Module 2. Introduction to Intelligent Building Management Systems (IBMS) 3. Evolution and significance of IBMS 4. Data-driven controls 5. Introduction to Assignment 1	Lecture (4 hr)
Week 01	1. Introduction to Programming (Python) 2. Variables	Tutorial (3 hr)
Week 03	1. Communication protocols 2. Features and functions of IBMS 3. Building Automation and Control Networks (BACnet) 4. Case study	Lecture (4 hr)
Week 03	1. Dataframes in Python 2. Handling data from sensors	Tutorial (3 hr)
Week 07	1.Building systems and controls 2. HVAC systems 3. Control strategies 4. Sensors in the built environment 5. Review of Assignment 1	Lecture (4 hr)
Week 07	1. Time series analysis A 2. Visualisation and Plotting A	Tutorial (3 hr)
Week 09	1.Network security 2. Security and access systems in buildings 3. Energy modelling basics 4. Introduction to Assignment 2	Lecture (4 hr)
Week 09	1. Time series analysis B 2. Plotting B	Tutorial (3 hr)
Week 11	1.Case studies on successful IBMS 2. Research frontiers in building controls 3. AI and future of intelligent buildings 4. Review of Assignment 2	Lecture (4 hr)
Week 11	1. Simple control models in Python	Tutorial (3 hr)

Attendance and class requirements

Please refer to the Resolutions of the University School:

University of Sydney School of Architecture Design and Planning Faculty Resolutions 2022.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Wang, S. (2009) Intelligent Buildings and Building Automation. (Spon Press; New York)

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

LO1. understand the fundamental principles of Intelligent Building Management Systems (IBMS)
LO2. understand the significance of IBMS within the commercial building contexts of performance and sustainability
LO3. understand the basic functionality and capabilities of IBMS: lighting, heating and cooling, ventilation, occupancy, energy efficiency, life safety, security, and facility maintenance
LO4. understand the principles of sensors and their role in IBMS
LO5. understand the logic and algorithms of IBMS
LO6. demonstrate skills in critical thinking and critical analysis of evidence
LO7. demonstrate skills in synthesising and effectively communicating technical information across the multiple disciplines comprising the IBCS/IBMS domain.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

New coordinator for this unit. Teaching activities are slightly revised.

Additional information

Work, health and safety

University COVID-19 safety guidelines will be implemented for on-campus.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

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