DEGREE: BSc Laptop Science and Digitisation
Module: Enormous Knowledge Analytics the utilize of AI
Assignment Title: SmartCity Metropolis Mobility Analysis the utilize of Hadoop and
Predictive AI
Assignment Form: Document
Word Restrict: 3000 phrases (+/- 300)
Weighting: 100%
Project Date: 4/9/2025
Submission Date: 30/9/2025
Feedback Date: 21/10/2025
Plagiarism:
When submitting work for overview, students needs to be responsive to the
InterActive/Canvas guidance and regulations in referring to plagiarism. All submissions needs to be your individual, normal work. Please enlighten that it’s top to no longer put up the identical project for two various modules within your route.
It be important to put up an electronic copy of your work. Your submission shall be electronically checked.
Harvard Referencing:
The Harvard Referencing Machine also can neutral quiet be historical. The Wikipedia, UKEssays.com or identical net sites must no longer be historical or referenced to your work.
Introduction
The aim of this project is to offer you with arms-on skills in designing and enforcing a Enormous Knowledge analytics solution that contains a predictive AI component. You might maybe cope with a hypothetical trim metropolis order by the utilize of the Hadoop ecosystem to route of mountainous-scale recordsdata and gain actionable insights for urban planning. This project requires you to invent an answer the utilize of Hadoop, HDFS, YARN, and MapReduce to analyse transportation recordsdata. The final step entails the utilize of the processed recordsdata to prepare a easy predictive model, thereby connecting Enormous Knowledge processing with AI functions. This enable you to know the finish-to-finish pipeline from raw recordsdata to industry intelligence in a up-to-the-minute context.
Scenario: The metropolis council needs to analyse urban mobility patterns the utilize of recordsdata from twin carriageway sensors, taxi journeys, or public transit data. The neutral is to title congestion hotspots, perceive their causes, and predict future web page visitors patterns to enable proactive web page visitors administration and better infrastructure planning.
Phase 1: Conceptual Assemble & Architecture (LO 1, LO 2) – 20% of Total Grade
1. Exchange Context and Order Assertion (5%)
• Picture the trim metropolis subject, focusing on the challenges of urban mobility.
• Clarify a transparent subject assertion. As an instance: “To analyse historical web page visitors recordsdata to predict the probability of web page visitors congestion at key intersections in retaining with time of day and day of the week”.
• Show how solving this subject presents tangible cost to the metropolis (e.g., reduced commute instances, lower air pollution, improved public security).
2. Hadoop Ecosystem and Architecture (15%)
• Show why a Enormous Knowledge manner is excessive for this subject.
• Name the roles of HDFS, YARN, and MapReduce to your proposed solution.
• Define your need of those substances for the defined subject.
• Build a transparent architectural scheme illustrating how recordsdata flows from offer to HDFS, is processed by MapReduce managed by YARN, and is then historical for prognosis.
Phase 2: Implementation & Analysis (LO 3) – 50% of Total Grade
1. Knowledge Acquisition & Preparation (5%)
• Pick out a appropriate public dataset representing urban mobility (e.g., taxi day out data, web page visitors sensor recordsdata). Platforms love Kaggle or metropolis-philosophize open recordsdata portals are correct sources.
• Picture the dataset’s constructing, size, and key attributes connected to your subject assertion.
2. Hadoop Atmosphere and Knowledge Ingestion (10%)
• Region up an arena single-node Hadoop cluster (e.g., the utilize of the official Apache Hadoop binaries or a Docker image).
• Doc the important steps of your setup route of.
• Load your chosen dataset into HDFS. Provide the instructions and screenshots showing the options successfully saved in HDFS.
3. Knowledge Processing with MapReduce (20%)
• Write a MapReduce program in Java or Python to route of the options. Your programmust form recordsdata cleansing and feature engineering to situation up it for the predictive model.
Instance tasks: calculate common day out length per route, count automobile waft per• hour, or title various connected beneficial properties from the raw recordsdata.
•Show the common sense of your Mapper and Reducer classes and consist of the well- commented offer code to your document’s appendix.
4. Predictive Analysis and Visualization (15%)
• Export the processed recordsdata from HDFS.
• Utilize the processed recordsdata to prepare a easy predictive model. You might maybe almost definitely almost definitely also utilize a library love Scikit-learn in Python to produce a classification or regression model that addresses your subject assertion.
• Analyze and interpret the output of your MapReduce job and your predictive model.
• Build meaningful visualizations (e.g., graphs showing congestion by time of day, a confusion matrix for your model) to original your findings.
Phase 3: Reflection and Documentation (LO 1, LO 2, LO 3) – 30% of Total Grade
1. Serious Reflection (10%)
• Reflect on the important challenges you encountered all the intention thru implementation (e.g., recordsdata cleansing, debugging MapReduce, model accuracy) and how you addressed them.
• Seriously discuss the performance and scalability of your MapReduce solution.
Could well well it be optimized (e.g., by the utilize of a Combiner)?
2. Closing Document Documentation (20%)
• Assemble an intensive, reliable document of no bigger than 3000 phrases documenting the total challenge.
• The document also can neutral quiet be well-structured with certain headings, honest grammar, and academic language.
•
Be sure that all phases (Conceptual Assemble, Implementation, Reflection) are thoroughly coated, including diagrams, code snippets, instructions, and visualizations to beef up your work.
• Encompass a bibliography the utilize of the Harvard referencing model.
Submission Pointers:
• Doc Format: Put up your project as a single doc following theBSBI project template equipped in Canvas.
• Writing Quality: Be sure that certain and concise writing with honest grammar and spelling. Utilize headings and subheadings to prepare your work logically in accordance with the tasks outlined above.
• Visuals: Encompass visuals love diagrams (route of waft, conceptual model sketches), tables (recordsdata assumptions, outcomes), and graphs (simulation output) where acceptable to enhance determining.
• Job Protection: Take care of every segment thoroughly, demonstrating your determining of Enormous Knowledge ideas and their utility to the industry subject.
• Implementation Famous beneficial properties: Provide connected examples and annoying beneficial properties of your model implementation, including code snippets, instructions, and calculations.
• Referencing Fashion: Utilize Harvard referencing model for your bibliography.
• Discussion: Speak about your findings, insights, and the implications of your options. Reflect on the challenges confronted and how you overcame them.
• Submission: Put up your project electronically (Canvas) by the specified deadline.
GUIDANCE ON ASSESSMENT
All supplies also can neutral quiet be successfully referenced under Harvard conventions. The length required is 3000 phrases with tasks equally weighted. The writing model needs to be formal academic / document writing model with in-text referencing to beef up your feedback and observations. Originality, quality of argument and proper constructing are required. The document also can neutral quiet demonstrate sound determining and skill to prepare knowledge and belief of Simulation Systems. Extra marks being awarded for juxtaposition and perception of components.
Grading Criteria
Generic Criteria 90 – 100
Knowledge of contexts, ideas, applied sciences and Distinctive breadth and
processes depth of recordsdata of
The extent to which: contextual and theoretical
components, some of that are connected contextual or theoretical on the forefront of the components are identified, defined and discipline, and their described
relationship to heaps of
historical or up-to-the-minute historical and practices are identified, defined up-to-the-minute practices and described
acceptable applied sciences,
methods and processes are Distinctive knowledge of identified defined and described heaps of connected specialist ways and processes
Figuring out thru Distinctive utility of utility of recordsdata heaps of research The level to which research methodologies to tasks methods are demonstrated: and problems and hypotheses, with evidence connected knowledge and of highly targeted recordsdata is in comparison, neutral conception and contrasted, manipulated, some original insights into translated and interpreted the subject knowledge and data is
chosen, analysed, synthesized and evaluated in teach to Distinctive capacity to
generate inventive options, practices, place heaps of
alternatives, arguments or inventive practices and to hypotheses critically evaluate them in
a wider context, generating sustainable arguments and highly efficient and individual outcomes
80 – 89
Excellent breadth and depth of recordsdata of contextual and theoretical components, some of that are on the forefront of the discipline, and their relationship to heaps of historical and up-to-the-minute practices
Intensive knowledge of heaps of connected specialist ways and processes
Systematic and thorough utility of heaps of research methodologies
to tasks and problems and hypotheses, with evidence of highly targeted neutral conception and a few original insights into the subject
Excellent capacity to place heaps of inventive practices and to critically evaluate them in a wider context , generating sustainable arguments and highly efficient and normal outcomes
70 – seventy nine
A breadth and depth of recordsdata of contextual and theoretical components, some of that are on the forefront of the discipline, and their relationship to heaps of historical and up-to-the-minute practices
Famous knowledge of heaps of connected specialist ways and processes
Rigorous utility of heaps of research methodologies to tasks , problems and hypotheses with evidence of highly targeted neutral conception and
excessive prognosis
Sturdy capacity to place heaps of inventive practices and to critically evaluate them in a wider context, generating sustainable arguments and highly
efficient outcomes
60 – 69
Confident knowledge of heaps of contextual and theoretical components, some of that are on the forefront of the discipline, and their relationship to heaps of historical and up-to-the-minute practices
Confident knowledge of heaps of connected specialist ways and processes
Confident capacity to prepare heaps of research methodologies to tasks, problems and hypotheses with certain evidence of neutral conception and excessive prognosis
Sturdy capacity to place heaps of inventive practices and to judge them in a wider context , generating efficient outcomes
50 – 59
Conversant in heaps of contextual and theoretical components, on the very least some of that are on the forefront of the discipline, and their relationship to heaps of historical and up-to-the-minute practices
Sound knowledge of heaps of connected specialist ways and processes
Sound capacity to prepare a range of research methodologies to tasks, problems and hypotheses and to demonstrate neutral conception
and excessive prognosis
Sound capacity to place arange of inventive practices and to judge them in a wider context, generating efficient outcomes
40 – 49
Conversant in heaps of contextual and theoretical components and their relationship to a
vary of historical and
up-to-the-minute practices
Adequate knowledge of heaps of connected specialist ways and processes
Competent capacity to prepare heaps of research methodologies to tasks, problems and hypotheses with some component of neutral conception and excessive prognosis
Competent capacity to place heaps of inventive practices and evaluate them in a wider context to generate efficient outcomes
30 – 39
Some knowledge of heaps of contextual and theoretical components and their relationship to arange of historical and up-to-the-minute practices
Tiny knowledge of a range ofrelevant specialist ways and processes
Ability to prepare a restricted vary of research methodologies to tasks, problems and hypotheses with minute evidence of neutral conception or excessive prognosis
Tiny capacity to place heaps of inventive practices and to judge them in a wider context to generate efficient outcomes
0-29
Tiny knowledge of contextual and theoretical components and their relationship to heaps of historical and up-to-the-minute practices
No vital knowledge of heaps of connected specialist ways or processes No vital capacity to prepare research methodologies to tasks, problems and hypotheses, and no evidence of
neutral
conception or excessive prognosis
No vital capacity to place heaps of inventive practices or to judge them in a wider context to generate efficient outcomes
5
Application of technical and reliable skills The level to which:
acceptable supplies and media are chosen, examined and utilised to clutch and original options and alternatives acceptable applied sciences, methods and processes are demonstrated
transferable, reliable skills are successfully demonstrated self administration and neutral studying are demonstrated Distinctive,individual andfluentapplication ofa vary of specialist
life like and technical skills
Excellent accomplishment of heaps of improved transferable and reliable skills applied to advanced eventualities and problems
Distinctive capacity to administer non-public studying in a sustained manner and to critically evaluate non-public growth, making utilize of a huge series of options sources Executed,normal andfluentapplication ofa vary of specialist
life like and technical skills
Excellent accomplishment of heaps of improved transferable and reliable skills applied to advanced eventualities and problems
Excellent capacity to administer non-public studying in a sustained manner and to critically evaluate non-public growth, making utilize of a huge series of options sources
Executed and normal applicationof heaps of specialist life like and technical skills
Executed utility of improved transferable and reliable skills to advanced eventualities and problems
Very excessive capacity to administer non-public studying in a sustained manner and critically evaluate non-public growth making efficient utilize of options
Confident and imaginative utility of heaps of specialist life like and technical skills
Confident utility of improved transferable and reliable skills to hard eventualities and problems
Sturdy capacity to administer non-public studying in a sustained manner and to critically evaluate non-public growth making efficient utilize of options
Sound utility ofa vary of specialist life like and technical skills
Sound utility of improved transferable and reliable skills
Sound capacity to administer non-public studying in a sustained manner and critically evaluate non-public growth making efficient utilize of options Competent utility ofa vary of specialist life like and technical skills
Competent utility of improved transferable reliable skills
Competent capacity to administer non-public studying in a sustained manner and place efficient utilize of options
Classic utility of heaps of specialist life like and technical skills
Tiny utility of improved transferable and reliable skills
Classic capacity to administer non-public studying in a sustained manner and place utilize of options Rudimentary utility of heaps of specialist life like and technical skills
Ineffective utility of improved transferable and reliable skills
Proof of a total capacity to administer non-public studying
6
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