abhinavcreed13 / project-space-optimisation-group-3 Goto Github PK

Ticket to track basic data analysis

Charts + Visualizations

• Collecting Results

• Documenting Results

Write Report Sections

Basic Model

Create Visualizations + Interactive charts

Data cleaning

Project Supervisor: Prashan Madumal ([email protected])

• Section 4.2: Hyper-parameter Tuning & Clustering Algorithms

• Section-2: Problem Description

• Section-3: Data Analysis

• Section-4.1: Non-Randomized Anytime Orienteering Algorithm

Understanding data properties

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Features understanding

• What reading have you been requested to do prior to your initial meeting with your industry partner?
• What further research can your group undertake about the host organisation and the people you will be meeting?
  (Google, LinkedIn, company databases such as Company360 etc)
• What questions can your team ask and who will ask them? (Note: share the questions so each team member has an opportunity to speak)

• Who will be your main communicator with your industry partner?
• What background (if any) reading/research is required about your industry partner before you approach them?

• Fix Tables
• Enable COVID
• British vs American English
• Reduce Space

Create correlations chart + Visualizations

Show some basic analysis of the data, from the size and scale, to ranges of values for response variables and input features.

Basic functionality includes:

• Predicting building based on supply/demand weights
• Running algorithm for both meeting rooms and toilet facilities objectives
• Highlighting or returning predicted building
• Including radius factor + adjusting weights accordingly

Implementation:

• Tested for meeting rooms.

• Test it for toilet facilities.

• Finding optimum building

• Finding optimum beta

Github process review

• Collecting Results

• Documenting Results

Datasets to be provided early next week:

• Space dataset (spatial)
• De-identified employee data
• Timetabling and class registration data
• Meeting bookings data

• Familiarise yourself with Australian Business Culture (review workshop resources), your Industry Partner organisation
  and the people you will be meeting
• Discuss with your Project Supervisor their availability and those of your team members. Find some mutually convenient
  times (aim for three time slots if possible)
• Using your University student account, send an email introduction to your industry partner (see Sample Email
  Template below) and cc into the email:
  • Your Project Supervisor (see Project Brief)
  • Your Subject Coordinator (see Project Brief)
  • Marika Benetti-Hille ([email protected])
  • All of your team
• Suggest possible times for the initial meeting as identified above, keeping in mind that your industry partner may be
  very busy

• Finding optimal floor

• Grid search beta parameter for finding optimal floor

• Automating Meeting Rooms Objective
• Automating Toilet Facilities Objective

Project structure + tex files

Data summary + correlations

Project part 1 timeline with deliverables.

Filling group contract with actions and deadlines

Meeting rooms:

• WITH_EQUIPMENTS: True/False
• ROOM_CONDITION: Excellent/Very Good/Good
• EASY_AVAILABILITY: True/False ~ Meetings held data
• HIGH_CAPACITY: True/False ~ Room Size
• REQUIRED_CAPACITY: ~ MR_CAP
• COVID_LOCKDOWN: True/False

Toilet Facilities:

• ROOM_CONDITION: Excellent/Very Good/Good
• HIGH_CAPACITY: True/False ~ Room Size
• EASY_AVAILABILITY: True/False ~ Class duration
• COVID_LOCKDOWN: True/False

What is the problem?
Why is it important?
How is the problem difficult from a Data Science perspective?

1. https://www.arcgis.com/apps/MapJournal/index.html?appid=59800d93fd194d2084c1555d1f6492b1
2. https://www.esri.com/library/books/the-language-of-spatial-analysis.pdf
3. https://www.esri.com/news/arcuser/0402/files/optimize.pdf
4. https://pages.uncc.edu/eric-delmelle/wp-content/uploads/sites/150/2012/12/Spatial_Optimization_Methods-2.pdf
5. https://www.esri.com/arcgis-blog/products/analytics/analytics/learn-spatial-analysis-techniques-with-scenario-based-case-studies/

• Collecting Results

• Documenting Results

QGIS integration & Plotting

Creating an automation script to load and dynamic values from user

• Enhancing script with toilet facilities weights
• Remove attribute from copied layer

• Set up a google calendar: https://www.google.com/calendar
• Once you have a meeting time set, invite all key people to the meeting:
  • Your Industry Partner
  • Your Project Supervisor
  • Your Subject Coordinator (will attend if possible)
  • Marika Benetti-Hille (will attend if possible) and
  • All of your team
• Establish where you will hold the meeting – generally this will now be a Zoom Meeting so you will need to set this up.
  https://www.unimelb.edu.au/zoom/home

Find preliminary results

• Collecting Results

• Documenting Results

Data preprocessing

Data merging + Approximate joins

• Technology – Where will you “attend” the Zoom meeting? Make sure the space you sit is appropriate for a business meeting
• What will you wear? What is the dress code?
• How will you greet your industry partner? The body language
• Prepare your ‘elevator pitch’ – who are you and why are you there? What do you bring to the project? Why are you interested in the project?
• Ask questions prepared earlier. Add new questions if the need arises.
• Listen carefully to the answers
• Agree next steps with Industry Partner. (Don’t forget to check in with your industry partner at least once per month for the duration of the project).

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