“Additionally, the geographical features themselves should be helpful because even if an offender doesn’t stop at a liquor store, the parole officer will know if they are near a liquor store and if they are near that location frequently. We hope the system provides officers with information, so they can decide if certain offender activity is worthy of concern,” Yuan said.
Another tool, a social network of potential interaction, will show parole officers the proximate space and time parolees under their watch are likely to have an interaction that would be a violation of their parole.
Hot spots of crime will use crime incident reports from the past two to three years to map out areas with a high density of crime in jurisdictions. Yuan said the team had created such hot spot maps for Tulsa and Norman and are currently working on Oklahoma City.
“Beyond knowing if an offender is in a hot spot, parole officers have to make home visits, and this tool can give them an idea of whether they’re going into a high crime area, so they can prepare,” Yuan said.
Crime scene correlation will provide parole officers data showing their parolees’ GPS points in relation to recent crimes.
Daily alert reports, which Yuan said the team was in the process of creating, should provide parole officers with a compilation of their parolees’ daily parole offenses. For example, a parolee could go to a liquor store and not make curfew; the daily alert report would notify the parole officer of both offenses.
Moreover, Yuan said the team hoped a historical report could be developed to show long-term patterns, not just daily behavior, so parolee behavior might be changed and recidivism decreased.
Currently, in their second user test, Yuan said the team had received helpful feedback from parole officers.