Many of the parameters used in AquilaVision’s software package POMM™ are based on spatial network model research used to predict human movement patterns when subjects have a goal and wander directed behavior.

network modelFor example, take a security guard trying to catch an intruder. Assumptions must be made that the direction and speed of the intruder will predict the intercept point but not the path traveled. Positioned at a stationary interception point, the security guard will probably not catch the intruder. It is the predictions of the most likely paths that the intruder will take to allow him to penetrate the facility boundaries, which will allow the security guard to detain the trespasser.

Spatial network models of POMM™ were designed to predict the location based on the rate of movement and barriers that slow movement, similar models have been used by city and county officials to route emergency vehicles across road systems efficiently.

Expected Benefits:

AquilaVision specializes in the use of prior knowledge about the behavior of a species to predict the path of movement and where to seek an object of interest. The movement model uses spatial network modeling together with statistical equations to estimate a path using the starting parameters of where, when, direction and speed. Knowing where to look once a facility intrusion is detected is vital information for enhanced security.

AquilaVision provides digital intrusion base maps for each installation site using remote sensing surveillance technology of our clients. The POMM™ layer and model will be unique to each site and use information provided by the surveillance technology to estimate a path traveled and a destination path based on the features on the ground and time of day and seasonal adjustment. Data will incorporate historic records of intrusion at the site to strengthen the POMM™ model.

The addition of AquilaVision’s POMM™ digital map layer will extend the life of already in place surveillance technology. Eventually intruders will learn unsuspected perimeter crossings, thus the surveillance will be rendered useless. The POMM™ map layer will show where secondary sensors may need to be placed or where increased monitoring may be necessary.