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Homework answers / question archive / The assignment requires to analyse the dataset using various information engineering techniques + written report 3000 words

The assignment requires to analyse the dataset using various information engineering techniques + written report 3000 words

Mechanical Engineering

The assignment requires to analyse the dataset using various information engineering techniques + written report 3000 words. The dataset will be provided separately (for SCC Weather). Full details of the assignment can be found in the provided word document

Module: Information Engineering

 

 What is required?        

         A 3,000 word report detailing the concepts and techniques employed to design and   implement an information engineering solution to the assignment scenario, and drawing

 rational conclusions qualified with an understanding of the uncertainties and limitations  from applying the solution. Appendices should include source code, data extracts,  spreadsheets, calculations, screenshots etc. to support the report.

 

 Learning outcomes to be assessed:

 1analytical concepts and methods which form the core of data science and information engineering. Demonstrate a systematic understanding and knowledge of the statistical, algorithmic and 

  1. Identify the most appropriate techniques and tools for a particular data or information problem,  and be critically aware of the limitations on these methods
  2. Design an information engineering solution to a particular data or information problem from a  toolbox of appropriate techniques
  3. Implement an information engineering solution, including such aspects as data modelling at  scale, statistical modelling, programming and visualisation of results
  4. Draw relevant and rational conclusions from the application of an information engineering  solution to a particular data or information problem, and critically appreciate the uncertainties and  limitations to the accuracy and/or applicability of these results

             

 Assessment & Grading Criteria:      

  1. An understanding and knowledge of the statistical, algorithmic and analytical concepts and  methods used in information engineering
  2. The ability to choose information engineering techniques and tools, and articulate any major  limitations 
  3. The ability to design an information engineering solution 
  4. The ability to implement their designed information engineering solution 
  5. The ability to draw some relevant major conclusions and reflect on any major limitations on their results.

 

Assessment Brief.

See the attached brief.

 

Assessment Criteria

 

 

Level 6

In accordance with the FHEQ, at the end of Level 6 students should have coherent and detailed knowledge and understanding of their subject area, at least some of which is informed by the latest research and/or advanced scholarship within the discipline. They will be able to accurately deploy established techniques of analysis and enquiry within a discipline, using their conceptual understanding to devise and sustain arguments and/or to solve problems. They should be aware of the uncertainty, ambiguity and limits of knowledge. They should be able to critically evaluate evidence, arguments, assumptions, abstract concepts and data (that may be incomplete), to make judgements, and to frame appropriate questions to achieve a solution - or identify a range of solutions - to a problem. They should be able to communicate information, ideas, problems and solutions effectively to both specialist and non-specialist audiences.

 

Assessment category

Pass mark, demonstrating achievement of all associated learning outcomes

Marginal fail

Fail

 

 

 

 

 

 

 

 

 

1st: 70% – 100%

2:1: 60% – 69%

2:2: 50% – 59%

3rd: 40% – 49%

35% – 39%

20% – 34%

< 20%

Coherent and detailed knowledge and understanding of the subject area, at least some of which is informed by the latest research and/or advanced scholarship within the discipline

High quality work showing coherent, deep and highly detailed knowledge and understanding of subject matter, explicitly wellinformed by the latest research and/or advanced scholarship within the discipline.

Work of solid quality showing competent and consistent knowledge and understanding of subject matter, informed by the latest research and/or advanced scholarship within the discipline.

Adequate work showing knowledge and understanding of subject matter, but lacking depth and breadth. Awareness of the latest research and/or advanced scholarship within the discipline.

Simple factual approach showing limited knowledge and understanding of subject matter. Narrow or misguided selection of material, with elements missing or inaccurate. Limited awareness of the latest research and/or advanced scholarship within the discipline.

Weak work showing

limited but fragmentary knowledge and understanding of the

subject matter, for example through inaccuracies, inclusion of irrelevant material and/or absence of appropriate information. No awareness of the latest research and/or advanced scholarship within the discipline evident.

Unsatisfactory work showing weak knowledge and understanding of subject matter. Work contains serious

inaccuracies and/or

a significant amount of irrelevant material. No awareness of the latest research and/or advanced scholarship within the discipline evident.

Highly unsatisfactory work showing major gaps in knowledge and understanding of subject matter. Inclusion of largely irrelevant material, absence of appropriate information and significant inaccuracies. No awareness of the latest research and/or advanced scholarship within the discipline evident.

 

 

Cognitive and intellectual

skills 

 

Excellent use of critical evaluation skills to make wellinformed and highly coherent judgements and arguments and/or creatively solve problems. Clearly articulates the significance of relationships between a range of ideas and concepts, enabling a new perspective to be applied. Use of a wide range of relevant supporting evidence. Work shows excellent originality and creativity of thought and approach.

Sound use of critical evaluation skills to make well-informed judgements and arguments and/or solve problems. Usually articulates the significance of relationships between a range of ideas and concepts. Use of a good range of relevant supporting evidence. Work shows significant evidence of originality and creativity which contributes to the overall assignment.

Use of critical evaluation skills to make largely logical and coherent judgements and arguments and/or solve problems, but with gaps and/or inconsistencies. Use of an adequate range of relevant supporting evidence. Work provides examples of

originality and creativity, which enhances aspects of the assignment.

A limited use of critical evaluation

skills to support emerging judgements and arguments and/or solve problems, although not always logical or coherent and with inaccuracies. Arguments not always developed, and gaps in supporting evidence. Little evidence of originality or creativity.

Largely descriptive work, with weak and superficial use of critical evaluation skills to develop judgements and arguments and/or solve problems. Information accepted uncritically, with weak use of evidence resulting in unsubstantiated opinions. No evidence of originality or creativity.

 

Descriptive work with no effort made to use critical evaluation skills to develop judgements and arguments and/or solve problems. Views

expressed are often illogical, invalid or irrelevant. Minimal or no use of evidence to back up views. Completely lacking in originality and creativity.

 

Work is largely irrelevant or inaccurate, characterised by

descriptive text and unsubstantiated generalisations. Minimal or no use of evidence to back up views.

 

Application of theory to practice (for courses with a professional practice element)

Excellent understanding and evaluation of application of theory to practice, with the student making highly appropriate,

developed and

articulated links between the two, drawing skilfully on the latest research within the discipline.

Sound understanding and evaluation of application of theory to practice, with the student making clearly articulated and reasoned links between the two, informed by the latest research within the discipline. 

Mainly consistent, accurate and logical application of theory to practice, with the student making appropriate links between the two and evidence of evaluation. 

Relevant theoretical knowledge and understanding applied in practice, but with students not always making logical links between the two and limited evidence of evaluation.

Limited understanding of the application of theory to practice, with the student often not making appropriate links between the two and no evidence of evaluation.

Weak

understanding of the application of theory to practice, with only occasional evidence of the student making appropriate links between the two.

Very weak theoretical knowledge and understanding, with no evidence of appropriate application in practice.

Reading and referencing

Critical engagement with an extensive range of relevant reading, including literature informed by the latest research. Consistently accurate

application of referencing.

Critical engagement with a good range of relevant reading, including literature informed by the latest research Sound application of referencing, with no inaccuracies or inconsistencies. 

Engagement with an appropriate range of reading beyond essential texts, including literature informed by the latest research. Referencing may show minor inaccuracies or inconsistencies. 

Evidence of reading, largely confined to essential texts, but mainly reliant on taught elements. Referencing may show inaccuracies and/or inconsistencies.

Poor engagement

with essential texts and no evidence of wider reading. Heavily reliant on taught elements. Inconsistent and weak use of referencing.

Limited evidence of reading and/or reliance on inappropriate sources. Limited engagement with taught elements. Very poor use of referencing. 

No evidence of reading or engagement with taught elements. Absent or incoherent referencing. 

Presentation, style and structure *

Highly effective presentation of work that is coherently structured and clearly expressed throughout. 

Competent

presentation of work in terms of structure and clarity of expression. 

Work is structured in a largely coherent manner and is for the most part clearly expressed. 

Ordered presentation in which relevant ideas / concepts are

reasonably expressed.

Work is loosely, and at times incoherently, structured, with information and ideas often poorly expressed. 

 

Work is poorly presented in a disjointed and incoherent manner. Information and ideas are very poorly expressed, with weak English and/or inappropriate style.

Work is extremely disorganised, with much of the content confusingly expressed. Very poor English and/or very inappropriate style.

* Work that significantly exceeds the specified word limit may be penalised.

 

 

 

 

Assignment Brief:

 

  1. THE DATASETS FOR THIS ASSIGNMENT ARE MADE AVAILABLE TO YOU FOR

THE SOLE PURPOSE OF UNDERTAKING THIS ASSIGNMENT. YOU ARE NOT TO REPURPOSE THIS DATA OR SHARE THIS DATA WITHOUT THE EXPRESS WRITTEN PERMISSION OF SUFFOLK COUNTY COUNCIL.  

 

  1. Suffolk County Council have been the recipient of a major funding award to support various trials of IoT sensors and related technologies across the county of Suffolk as part of a consortium, including the University of Suffolk. As a consequence of this and other initiatives, rich and varied datasets are being generated, which have the potential to inform decision-making across the county and improve the county economy and well-being of individual citizens.

 

  1. Suffolk County Council wish to discern useful information and knowledge from these datasets. 

 

  1. To this end, they have provided various datasets (some indicated below), and sets of potential questions which they would like to be able to answer from one or more of the datasets:

 

No. of sensors

What?

Measuring?

Where

Format

Size

31

Traffic Radar

5 minute counts  traffic, speed

Sept 2019 onwards Not all cover the whole time period

Across Ipswich

Excel

per sensor per week

88KB

1460 rows

10 columns

some

Traffic Radar

Subset of above also have vehicle classification

Across Ipswich

 

 

12

SCC Weather

Stations

[Primarily used for winter gritting decisions]

Road surface temp, air

temp, wind speed, dew point, 

Several years of data at

10 minute intervals

Across Suffolk

Excel

Per sensor per month

581KB

4450 rows

14 columns

6

Road

Temperature

Six different road temperature sensors installed in two locations

Data in various formats

Adastral Park

 

 

11 (+ more)

Road temperature

Set of road temperature sensors around Ipswich and along gritting routes

Ipswich and environs

CSV

All sensors per month = 45.5MB c. 540,000 rows

11 columns

 

 

 

 

 

 

 

11

Air quality

PM2.5, PM10, O3, NO2 Installed June 2020

Across Ipswich

CSV

All sensors per

month = 45MB

 

2

Gully condition

Two gully monitors, different data

Adastral Park

 

 

2

Wind sensors

Two wind sensors

Ipswich

CSV

All sensors per month = 6.5MB

 

 

 

 

 

    1. Traffic flow in Ipswich
      • How does it vary by day of the week / time of day? 
      • Is it seasonal?
      • Do some areas correlate with other areas?
      • Does traffic flow correlate with air quality?

 

    1. Dynamic dimming
      • How can lighting dimming correlate with traffic volumes? 
      • How much money can be saved?

 

    1. Targeted winter gritting
      • How often is one area of the county gritted but not the others? 
      • How many nights a year is there a variation in gritting need across the county?
      • (Depending on when the assignment is scheduled): how does information from the temperature sensors correlate with gritting decisions? 

 

More challenging questions may be answerable dependent on availability of data:

      • INRIX traffic data (data file size tens of GB) of routes of lorries around Suffolk. Questions of interest around “where does the traffic go when the Orwell Bridge is shut?” (spreadsheet of Orwell Bridge closure times available)
      • Air quality changes during / subsequent to lockdown, correlation with vehicle class and traffic volume. Use INRIX and CA-Traffic data.
      • Correlate air quality with times of day, vehicle movements.
      • Data from gritting and road surface temperatures. Is reduced gritting possible?
      • A newly available data set is STRAVA records for Suffolk, with cycling and walking records from Strava users – what can we learn from this behaviour?
      • Traffic Master data logs GPS tracking on routes and can be used for journey times.

What can we learn about variation in journey times per various routes?

      • Adaptive lighting doesn’t take weather into account. Can it?

 

  1. Use the full scope of information engineering techniques to represent, manipulate, visualise and analyse this data. You may wish to reimport the data into an NoSQL or even SQL database; you may wish to process the data in Excel, R, Python, MapReduce or other appropriate language / package; you should choose appropriate algorithmic and statistical techniques to use upon the data in order to substantiate any claims that you can derive from the data

 

  1. Write up a 3,000 word report which captures the design and implementation of your information engineering solution and presents the analysis and visualisations that you have been able to perform on the data. Support the report with appropriate appendices including source code, screenshots, graphs, data files, calculations, spreadsheets, etc.

 

  1. Ensure that your work (submitted electronically via the online submission portal) is bundled into a suitable file (Word, pdf, or zipped collection of documents) with the filename matching the pattern  sXXXXXX-InfoEngineering where sXXXXXX is your UoS userid. Ensure that all documents are marked with your UoS userid. Your name should not appear in any of the files.

 

  1. Reports providing substantial insights will be shared with Suffolk County Council as a quid pro quo for access to their datasets.

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