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Supercomputing Challenge

Modeling Future Crime

Team: 103


Area of Science: Computer Science

Interim: Problem Definition:
Artificial Intelligence (computers) has been used to solve a myriad of our society’s problems. Recent jumps in crime level all over the U.S. have recently caught the eyes of many people, especially the media. Cities now face the dilemma of lowering crime rate in order to attract prospective citizens. Current citizens also demand more security. This demand led us to the idea to attempt a program whose ideological basis was thought to lie in a quixotic future. In our endeavor to transform this fantasy into reality, our group will attempt to simulate the future within an acceptable margin of error.
Problem Solution:
The milieu in which our simulation would be conducted in is based on the layout of cities’ block formations. Buildings would be represented as sites on the block. The computer would be in charge of calculating how sites affect each other in crime rate by determining the end result of the combining their “gravities” for crime attraction. Using a set of random seeded "factoids", the AI would determine the alteration of a gravity based on random events (such as if today was Sunday or there was a car accident on a highway) enhancing the effectiveness of the model. Eventually, cities crime areas could be compared.
Progress to Date:
Presently, we have a simulator constructed in which a grid representing a city is displayed with 80 possible sites for buildings and etc. Menus along the side allow the user to input the structure at each site (or if there is no structure) and the location of highways. The AI will then determine the site most likely to be hit by crime and point at it with a spiffy arrow.
Expected Results:
After testing and refining our “model-ator”, it could be implemented into city infrastructural planning; ergo reducing crime, attracting future citizens, raising the economy, lowering un-employment, cutting back on greenhouse gas emissions, saving the ozone layer, protecting wildlife and humanity, and ultimately bring peace to the world.

Team Members:

  Omar Soliman
  Alan Benalil
  Joseph Romero
  Bryan Haworth
  Alex Takacs

Sponsoring Teacher: Bala Settu

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