Designing a Smart Temperature Control System for Smart Buildings using AoE Principles

Submission Rules

Submission Rules
The assignment should be around 2000 words excluding references and figures. The assignment should be your own work and written in your own words and any information taken from other resources should be referenced appropriately. It will be checked for plagiarism using Turnitin. Any plagiarism or copying from others will be dealt with through the university’s plagiarism procedures.

Your assignment must be submitted electronically via BlackBoard (Assignments tab) by the submission time. The report should be contained in a Word document, or PDF No other means of submission will be accepted. The software code will be submittedindependently.

Any assignment submitted late, but within 5 working days of the deadline, will be given a maximum mark of 50%. Assignments submitted more than 5 working days after the deadline will not be marked, and a mark of 0% will be recorded.

Learning Outcome to be assessed:

1 Research, analyse, integrate, apply and present detailed design proposals.

2 Use appropriate technical terminology to describe basic design concepts.

3 Develop technical competence and skills in generation and adaption of design ideas.

Task:
Lutron is an industry focused IoT application development company that develops smart building for different industries to support a wide range of systems and computing environment. One of the future objectives of Lutron is to be a leading company on smart IoT technologies in cyber-physical domains using the principles of Automation of Everything (AoE) within Industry 4.0.

You have been asked as an engineer in the ‘Lutron company, to design the temperature control system and show the viability of such a system in order to make Lutron a leading company in design and implement smart building,

Provide a detailed, professional report for your company that contains the following:
1- A review/insight of various systems that can be utilized in smart building like temperature, lighting, IT, etc. Human body can be a source of heat. List all the elements that could contribute to the temperature in a close environment and their related sensors.

2- Based on your review, a temperature control system within the concept of AoE need to be designed. Use flowchart to support your design.

3- Build an application using K-Mean for this smart temperature system to establish anomaly detection of the sensors output. You can use any programming language you are comfortable with. You will:

(i) Use input data from local sensors. (You will be going to use data available from the internet or generate your own data)
(ii) Describe in detail the K-mean clustering concept and how you will be going to use it in the task in hand.
(iii) Discuss the use of the InaaS and WaaS in your design such that you can accommodate any sensing technology that you could use in your task.

4- Develop an interface test platform in order to show that your system is working as desired and ready to be incorporated into any smart building. This platform:
i) sample multiple readings from each sensor and
ii) Suggest the necessary action (in software) when the sensor is identified as faulty based on the K-Mean implementation that you developed in previous step.
iii) Suggest a scenario to combine different sensors output reported in Q1 to control the temperature. 

5- Explain how you will be going to convince your line manager that your development is a reliable solution and can be integrated in the smart building.

The Department’s Principles of Assessment will be used to determine grading levels.

1. A review/insight of various systems that can be utilized in smart building like temperature, lighting, IT, etc. Human body can be a source of heating. List all the elements that contribute to the temperature in a close environment and their related sensors.

2. Based on your review, a temperature control system within the concept of AoE need to be designed. Use flowchart to support your design. 

3. Build an application using K-Mean for this smart temperature system to establish anomaly detection of the sensors output. You can use any
programming language you are comfortable with. You will: 

i.  Use input data from local sensors. (You will be going to use available data from the Internet or generate your own data)

ii. Describe in detail the K-mean clustering concept and how you will be going to use it in the task in hand.

iii. Discuss the use of the InaaS and WaaS in your design such that you can accommodate any sensing technology that you could use in your task.

4. Develop an interface test platform in order to show that your system is working as desired and ready to be incorporated into any smart building. This platform:

i. sample multiple readings from each sensor and
ii. Suggest the necessary action (in software) when the sensor is identified as faulty based on the K-Mean implementation that you developed in previous step.
iii Suggest a scenario to combine different sensors output reported in Q1 to control the temperature. 

5.Explain how you will be going to convince your line manager that your development is a reliable solution and can be integrated in the smart building