Module Learning Outcome (MLO)

MLO 3: Analyze and design programs using appropriate programming concepts in real- world problems.

Assessment Criteria

C1  =  Knowledge  &  Understanding;   C2  =  Cognitive  Skills;  C3A  =  Practical  Skills;  C3B  = Interpersonal Skills; C3C = Communication Skills; C3D = Digital Skills; C3E = Numeracy Skills; C3F = Leadership, Autonomy & Responsibility; C4A = Personal Skills; C4B = Entrepreneurial Skills; C5 = Ethics & Professionalism.

Scenario

You are tasked with developing a predictive system to assess the Air Quality Index (AQI) in a specific region. The dataset, named "Env_Data," includes various parameters that contribute to environmental conditions. This system aims to predict the Air Quality Index based on the provided dataset.

The dataset for Env_Data contains one table structured as follows:

. year (Integer): The year of the environmental impact measurement.

. month (Integer): The month of the environmental impact measurement.

. day (Integer): The day of the environmental impact measurement.

. hour (Integer): The hour of the environmental impact measurement.

. temperature (Float): The temperature in degrees Celsius at the time of measurement.

. humidity (Float): The humidity level at the time of measurement.

. wind_speed (Float): The speed of the wind at the time of measurement.

. air_quality_index (Float): The air quality index recorded at the given timestamp.

. noise_level (Float): The noise level in decibels at the time of measurement.

. precipitation (Float): The amount of precipitation (e.g., rainfall) in millimeters.

. solar_radiation (Float): The amount of solar radiation received at the given timestamp.

Based on the dataset provided, develop a predictive system that provides the prediction of air_quality_index using relevant input. You will explore this dataset, perform data analysis, and design a predictive model to generate air_quality_index forecasts. Additionally, you will evaluate  the  model's  accuracy  and  provide  suggestions  for  improvement  to  enhance  the quality of air_quality_index predictions.

Task 1 (10%) ANALYSIS and DESIGN

Conduct an in-depth analysis of solution to the problem above documenting the followings:

1.   Data cleaning to ensure high quality of data input.                                         (2 marks)

2.   Data exploration to understand and extract critical information. Create at least

THREE data visualizations with justification and result discussion.             (3 marks)

3.   Based on data exploration, provide strategy to build the predication model with proper justification to achieve high accuracy rate.                                                    (3 marks)

4.   Develop at least ONE UML diagram for the above system.                           (2 marks)

Task 2 (15%) IMPLEMENTATION

Based on your design in Task 1, create a full object-oriented Python program that contains multiple  classes  and  object  transactions  in  the  main  program.  Specifically,  you  need  to demonstrate the followings:

Task 3 (5%) PRESENTATION

Present your system identifying all items conforming to the system requirements. In addition, present the live demonstration of your running system. Each person is limited to a 10-minute presentation.

Voice 2 mark

Content 2 mark

Aesthetic 1 mark