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🍁 Canadian Special Forces Command Incidence Response Automated Analysis by Artificial Intelligence at Hack the North 2017
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README.md

AINOMALY

Canadian Special Forces Command Incidence Response Automated Analysis by Artificial Intelligence at Hack the North 2017

Image of Yaktocat

Ainomaly introduces automation of surveillance footage analysis by harnessing the power of computer vision and machine learning. Ainomaly is NOT a replacement for human controllers, but functions as a powerful tool to assist and augment this important task.

Really cool demo video: https://youtu.be/RNBxzSINypo

BACKGROUND

CANSOFCOM personnel are tasked and trained to conduct a wide range of dangerous missions on behalf of the Government of Canada. One of these high risk missions is Hostage Rescue.

One of the most important aspects of mission success in a Hostage Rescue operation is accurate and reliable intelligence; principally gathered from observation. To ensure mission success, while reducing collateral damage, CANSOFCOM personnel continuously observe locations to determine patterns – an extremely time consuming and monotonous process.

SCENARIO

A senior Canadian Government Official has been kidnapped and is being held hostage in a [House/Office/Warehouse/Farm]. An incident response team has been dispatched comprised of both local and federal police authorities. They have each deployed drones with various camera technologies (high resolution, electro-optics, infra-red, etc.) that provide a live/near-real time feed to the analysts on the ground.

Due to certain complexities on the ground, law enforcement agencies have requested the support of the Canadian Armed Forces, and CANSOFCOM is called upon to conduct a hostage rescue operation.

The CANSOFCOM analysts have an important job of determining historical information of the hostage situation from previous footage from local security forces, in addition to live on-going footage of various drones. The analysts need to identify important key indicators (as described in the Challenge, below) that will help ensure a successful rescue operation by CANSOFCOM operators.

CHALLENGE

CANSOFCOM seeks to automate the persistent monitoring process to discern patterns of personnel (both threat actors and innocent civilians), vehicles, distinguishing features (physical, pattern, movement, etc.), and to develop normalcy in patterns, which can be used to isolate deviations in support of a hostage rescue operation.

The principle objective of automating the process is to reduce the person power required for the analysis of surveillance footage; thus allowing CANSOFCOM personnel more time and space to perform more pertinent tasks related to the operation.

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