CET255 Developing A Smart Greenhouse Monitoring System Prototype Assessment Brief

Assessment Format:	Report
Submit:	Files submitted via Canvas

1. CET255 Specification

This assignment is weighted at 100% of the overall module and will be marked out of 100.

The aim of this assessment is to provide you with an opportunity to demonstrate your understanding and practical skills in IoT and Robotics.

The assessment is designed to assess your ability to develop a small prototype, evaluate its performance, and write a technical report.

Additionally, you are required to submit a portfolio of evidence from practical exercises undertaken during the course.

1.1. Learning Outcomes

LO1.Develop and describe contextualised solutions to defined problems by choosing appropriate tools and components.
LO2.Employ a range of basic data science tools and techniques to analyse, process, visualise, store and exploit sensor-acquired data.
LO3.Apply appropriate networking concepts (such as protocols, transports and services) to support the remote operation and connectivity between edge computing devices.

1.2. Deadlines

Files submitted via Canvas. Deadline
Thursday, 29 May 2025 14:00

2. CET255 Important Information

All work is to be completed individually, except where explicitly stated, and you will only be able to receive Marks for your own work. You are responsible for the security and integrity of your own files, and you must not permit others access to your assignment work. Plagiarism or paraphrasing without due accreditation will be dealt with severely as set out in the University Infringement of Assessment Regulations and detailed in the Programme Handbook. You can also refer to the library guidebook on plagiarism, such as Avoiding plagiarism – University Library Services (sunderland.ac.uk)

Students are permitted to use AI tools in an assistive role within the assessment. However, the student must declare in the submission the used tool(s) and how they used it.

Examples of where AI might be used in an assistive category include:

• Drafting and structuring content.
• Supporting the writing process in a limited manner.
• As a support tutor.
• Supporting a particular process, such as translating content.
• Giving feedback on content or proofreading content

However, students cannot use AI tools to complete the project as the work must be completed by the students. All AI-generated content must be validated by the student.

You are expected to upload your work; submitting links to files saved elsewhere in the cloud will not be considered and will result in a zero mark. The actual files must be loaded to Canvas and readily available to the assessor. After uploading and submitting your files, you must check that you can also retrieve and open them. It is your responsibility to ensure files are not corrupted at the time of submission and to report any issues immediately to the help desk, copying in your lecturer and seeking alternative arrangements when required.

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3. Tasks and Deliverables

You are required to complete three main tasks; the task details can be found below:

1. Development of Prototype (30%):

The prototype is a micro-python script with documentation. If you are using any external libraries, you need to show the method you used to install the libraries.

2. Evaluative Report (40%):

Write an evaluative report that documents your development process, explaining all the steps of your development. The performance and functionality of the prototype and the extent to which it meets the project objectives. Your report should critically assess the strengths and weaknesses of your prototype, propose potential improvements, and discuss the implications of your project. The report structure is shown in section 5.

3. Portfolio of Evidence (30%):

Compile a portfolio of evidence showing the practical exercises from Weeks 2, 3, 5, and 6, completed with expected functionality. A single file containing all four chosen weeks’ workshops with evidence of implanting the code. This should include code samples, screenshots, images taken in the workshop, project notes, or any relevant material that demonstrates your practical engagement with the course material.

4. Prototype Specification

Students must select the correct prototype SET number based on the table below. Changing the set number will result in zero marks for Task 1.

SET-1: You will design, implement, and test a data acquisition and visualisation system using the LDR light sensor (light intensity) and BME680 (temperature, humidity, pressure, gas resistance) environmental sensor. The microcontroller will monitor the data and function as an indicator to display the observed values. The system will use NeoPixel LEDs to indicate the status of these values. The LED matrix will display a red light if the sensor is not exposed to sufficient light. Conversely, if adequate light is detected, it will show a green light.

SET-2: You will design, implement, and test a data acquisition and visualisation system using the VEML6070 sensor (UV) and DHT11 sensor (temperature, humidity) environmental sensor. The microcontroller will monitor the data and function as an indicator to display the observed values. The system will use NeoPixel LEDs to indicate the status of these values. The LED matrix will display a red light if the sensor is not exposed to sufficient UV light. Conversely, if adequate light is detected, it will show a green light.

The system will:

1. Continuously collect the data from the sensors at regular intervals (e.g., every second).
2. Transmit the collected data wirelessly via Wi-Fi using the MQTT protocol to a designated broker.
3. Create a CSV file on the microcontroller’s local storage device to store the received data, ensuring proper time stamps and labelling for each data point.
4. Develop a visually appealing and interactive dashboard using Python’s Streamlet library that displays the recorded data.

The dashboard should:

1. Offer multiple visualisation options (e.g., line charts, histograms) to cater to different types of data and user preferences.
2. Allow dynamic interaction (e.g., zooming, filtering, drill-down) to facilitate in-depth exploration of the data.
3. Provide clear labelling and titles for axes, legends, and other visual elements to enhance readability and understanding.

5. CET255 Report Structure

The evaluative report must include the following sections:

• Introduction (1 pages): This section should provide an overview of the work, with a clear outline of the main objectives of developing the prototype.
• Methodology (page count depending on image/diagram usage): This section should show the step-by-step demonstration of the developed prototype. The demonstration must include evidence of the implantation, using screenshots and images of your implantation.
• Results and Discussion (2-3 pages): This section should present the findings of the project in a clear and concise manner. The results should be interpreted, and their implications should be discussed.
• Appendix: This section should demonstrate the code you used in the prototype for both the IoT device and the data analytics. The code should be attached as text, not screeAnshots