Creating a crime-themed game — dare to play?
Going to put up the first machine learning project, a code in Python today.
I am developing a toy project, that is about crime.
import random The game has a investigator (pictured) as protagonist.
Haven’t yet decided how the play mechanics happens. This stage is so much fun! I love it. All the options are open :)
Media relations and your team
See above.
Street view CCTV cameras
You can see, sometimes with a latency, some of CCTVs (cameras) in the city. City has plenty of cameras.
Stats
In stats view, you can also see potential densities of CCTV deployments. This figure is the CPDa (CCTV cameras deployed, per Area).
- choose a density plot, or
- choose a area, and read the CPDa number attached to it
With a Permission, you can get also historical film archives.
Costs of your Team´s activities
Profiling is actually very interesting business.
Below are the costs you can expect. There are ways to Negotiate with vendors, but these are the list prices.
Paying the bill happens by your Boss. You can talk with the issues, but usually it is not necessary. Only when your Boss gets some rap from or ideas, then you can negotiate.
You may allocate budget, or use the Payment as you go.
List prices for Activities
HF
Clicking on a camera shows what you can do with its reel:
- look in real time (only your teams’ Deployed online Cameras) — DOC
- look
- start (power ON) a camera — DC, that has a “Remote” feature
Order reels from public CCTVs
Buy cameras
- place Orders in the Depot
deploying Gear into various POIs in the City
- order a team member do the Task
- plan a Task in the Planning view
- the team member makes the task
- there is Success metric
- task may Fail due to many reasons, also
- task programming happens in a UI screen
Task proficiencies — and the consequences
Your team members will be doing stuff for you. You rarely go on the field. Rather: order the Actions from your team members.
As a forensic Team Lead, you have a lot of motivating tools at your disposal. Here are a few in the game:
- talk
- preparations = spends time, slows down progress
- force = reminding of consequences of a failure in the Task
You can motivate a team member by using a pep talk.
Profiling
Machine learning could be used here in many ways.
This is sort of a exploratory project, in finding out how:
a) to do Machine Learning algorithms in the first place — with Python
b) strategy / tactics games’ use of AI — what kind of new fun, or alternative features can be borne out of this
Btw — you wanted it. The first antagonist, beefman is right here:
