Administrator

By: John Kirtland, Track Group U.K.

We have all seen the rapid increase in data creation – much of which has location information as an integral part. Developments in toolsets and algorithms for the analysis of large volumes of location based data now enables greater context to be derived in Pattern of Life (PoL) analysis… answering more questions in less time and with the benefits of collaborative work processing.

The tools to view the data have typically been delivered through map-oriented or data-oriented visualisation efforts. The reality of these tools is that they represent a visualisation into the raw data – leaving all of the interpretative analysis of what the data actually represents up to the user. Users are now looking for automated answers that reveal key patterns that are represented in the data but that are not evident through pure visualisation.

The development of advanced generation toolkits in response to increased data provision and in-depth questioning are now available and producing good results. Agencies are reporting improved intelligence results with reduced Analyst processing time.

Location Analytics

To obtain intelligence from all of these analytical stages, one must be able to effectively apply four treatments to location-based surveillance data:

1. Deep Analyzing several months of data, from a number of sources, for a suspect revealed his location to match a number of other crimes that he had not been seen as connected with.
2. Broad The analysis of data relating to 8 targets gathered over 3 months was completed in 11 minutes. Comparing each target against all the others identified previously unrecognized common meeting and visit locations connecting two separate groups and resulted in a modified approach to their surveillance.
3. Predictive Location data for a target with complex life patterns identified their home, work and other regular locations in 90 seconds, an activity that had previously taken weeks of physical surveillance of this unpredictable pattern.
4. Layered Following apprehension of a gang leader other suspect tracks were analyzed with influential gang members being identified by their response behaviors captured through phone records and social media activity. The same analysis also eliminated other traces from the subsequent round of pick up activity.

Deep – rapidly analyse 100,000’s data points

The analysis of large data sets has been made easier and can be processed faster to automatically provide a Deep Life pattern.

There has been a large increase in the amount and variety of data presented to intelligence and surveillance teams. First and second generation toolsets were unable to make best use of this data quickly resulting in analysis commonly being applied to recent activity only.

Toolsets provide answers to commonly asked questions:

• Expand awareness of the location of interest with certainty of the previous and subsequent locations, along with the routes used. This allows plans to be developed that can reduce the cost of surveillance activities and enhance the deployment of personnel and technology.
• Bring in a greater volume of data to identify other locations of interest previously not identified through regular use or abnormal use. Such locations do not normally reveal themselves with superficial analysis.
• Identify cycles of behavior previously not identified nor planned around. Longer term cycles of activity can only be identified when analyzing greater periods of collected data. Third generation tools can analyze this volume and also conduct greater contextual analysis in doing so.

Broad – compare across multiple targets

Processing multiple parallel sets of data for multiple targets is providing a Broad Life pattern within a matter of seconds.

The comparison of a single target against a small number of others (1:N) was a useful feature of the better second generation toolsets. Third generation tools have advanced to enable N:N analysis at the push of a button and without the need for a supercomputer.

With the added advantage that the analysis can be performed across large data sets a Broad Life pattern covering these three key features can be easily delivered in a single review of the data.

• Review common locations across many targets, and whether their attendance at these locations is also common in time, to determine meeting places.
• Perform a similar review where the location attendance is not common in time to identify drop locations or safe houses.
• Review tracks for multiple targets to identify previously unknown connections between individuals or groups.

Predictive – where next? and when?

With an enhanced analysis of more data we can introduce predictive tools that can answer the question “Where will they be?” for a date and time in the future.

Previous toolsets have been restricted in the volume of data analyzed causing analyzed timeframes to be restricted to a number of days. This restriction has limited the forward planning capability of surveillance teams.

Applying a level of confidence selected by the analyst, planning, enhancing deployment of personnel and their surveillance technology. Field operatives have a higher degree of confidence for the future location of the target and as such can modify their tactical procedures for surveillance, equipment deployment/refresh and target interception.

• Where will the target be?
• Where will they have come from and go to after?
• Which route will they have used?

Layered – social media, ANPR, phone, any geolocation data

With an array of data sets providing location attributes (lat:long) the creation of intelligence has become a more complex job.

Rapid import tools allow the analyst to import data sets from any source of location data. With the ability to create a standard import list and to import on the fly the addition of a new data set is no longer a time consuming headache.

Layering and de-layering the data sets allows for swift comparisons.

• Mobile phone data records – cell tower data can be extracted and analysed to provide routes taken.
• Smart travel card (eg Oyster) use – will enable a pattern of life to be created for public transport use.
• Financial records – ATM cash withdrawals and payments
• ANPR data – will place the target’s vehicle at a particular location and time.
• Blue force data – can also place and locate known friendlies to determine compromise.
• Others – any data set with time and location information.

Enhanced Pattern of Life context

Bringing these four new capabilities together enhances Pattern
of Life information and is delivered in a fraction of the time of traditional methods. The most immediate outcomes for this are:

• Less time spent ‘crunching’ the data.
• Data from a wide variety of sources can be easily tied together.
• Answers to your most typical questions are generated automatically.
• New answers are provided that would not have previously been possible

Acquisition Adds Cutting-Edge Analytics Capabilities to Inform and Improve outcomes in National Security, Law Enforcement, Corrections and Adjacent Markets.

SALT LAKE CITY, UT– Track Group, a premier provider of global tracking and monitoring services, today announced that it has acquired G2 Research, a global provider of analytical software with solutions ranging from data analysis and reporting to advanced predictive analytics. The transaction was finalized on Wednesday, 26 November 2014 for a total of up to CAD 4.6 million in a combination of cash and stock.

With this acquisition, Track Group will integrate G2 Research’s executive leadership and employees who will remain in Halifax, Nova Scotia Canada where G2 Research is currently headquartered. This will enable Track Group to deliver sophisticated analysis and detailed interpretation of data to improve performance across its current customer base including National Security, Law Enforcement, Community Corrections, and Health Research and will enable the company to rapidly enter adjacent markets.

“We are proud to announce our acquisition of G2 Research, an industry leader in analytics,” said Guy Dubois, Chairman, Track Group. “Today, our customers are faced with substantial challenges as it relates to extracting meaningful information from the mass of data accumulated. With G2 Research onboard, Track Group will address these challenges holistically by offering advanced capabilities in managing big data to improve decision-making and efficiency.”

“Track Group was the best company for us to partner with,” stated Tom Gilgan, co-founder and CEO, G2 Research. “Joining a global, market leader will enhance our ability to create and develop leading-edge technology that helps our customers fight crime and reduce recidivism.” said Gilgan.

About Track Group:
Track Group is a premier, global provider of customizable tracking solutions that leverage real-time tracking data, best-practice monitoring, and analytics capabilities to create complete, end-to-end solutions.

Visit website https://trackgrp.com/.

Safe Harbor Statement
This press release from Track Group (Company) contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934, including future growth and earnings pportunities of the Company. Actual results could differ materially from those projected in these forward-looking statements, which involve a number of risks and uncertainties, including the Company’s ability to promptly satisfy orders and other economic, competitive, governmental, technological, regulatory, manufacturing and marketing risks associated with the Company’s business and financial plans. The contents of this release should be considered in conjunction with the risk factors, warnings, and cautionary statements that are contained in the Company’s most recent filings with the Securities and Exchange Commission.

Contact:
Steve Hamilton
Chief Marketing Officer
877-260-2010 ext. 4004
steve.hamilton@trackgrp.com

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A home-invasion-burglary crime spree in Colorado ended abruptly when police arrested a 27-year-old male at one of the crime scenes. The burglaries, in which over $120,000 worth of cash, electronics and jewelry were stolen, soon become international news as the offender was wearing a SecureAlert GPS monitoring device, but committed the crimes anyway.

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SecureAlert has been awarded a 41 month government contract with Chile’s Gendarmerie, the nation’s uniformed prison service, to provide offender tracking, monitoring and public safety services.

The award follows a thorough competitive review by Chile’s Ministry of Justice, which considered all available technologies for an electronic monitoring program designed to alleviate prison overcrowding while ensuring compliance among domestic violence, pre-trial and early release offenders. SecureAlert was chosen in large part because of the company’s proven ability to monitor high-risk offenders through its innovative tracking solutions and real-time monitoring programs.

Under the agreement, SecureAlert will deliver and put into service up to 9,400 electronic monitoring devices over a three-year period. In addition, the company will also initiate real-time monitoring and data centers, to be staffed by Chilean government employees, and will provide ongoing training and support to maintain the program’s full effectiveness.

Edna Erez, LL.B., Ph.D., University of Illinois at Chicago
Peter R. Ibarra, Ph.D., University of Illinois at Chicago
William D. Bales, Ph.D., Florida State University
Oren M. Gur, M.S., University of Illinois at Chicago

June 2012

This project was supported by Grant No. 2007-IJ-CX-0016 awarded by the National Institute of Justice, Office of Justice Programs and U.S. Department of Justice.

This study examines the implementation of Global Positioning System (GPS) monitoring technology in enforcing court mandated “no contact” orders in domestic violence (DV) cases, particularly those involving intimate partner violence (IPV).

The research also addresses the effectiveness of GPS as a form of pretrial supervision, as compared to other conditions in which defendants are placed.

The results indicate an increase in agencies’ use of GPS technology for DV cases since 1996, primarily to enhance victim safety and defendant supervision.

The study also examined the impact of GPS technology on DV defendants’ program violations and re-arrests during the pretrial period and on re-arrests during a one-year follow-up period after case disposition.

• The results indicate that GPS has an impact on the behavior of program enrollees over both short and long terms.
• Examination of the short-term impact of GPS enrollment shows it is associated with practically no contact attempts.
• Furthermore, defendants enrolled in GPS monitoring have fewer program violations compared to those placed in traditional electronic monitoring (EM) that utilizes radio frequency (RF) technology (i.e. remotely monitored and under house arrest, but without tracking).
• GPS tracking increases defendants’ compliance with program rules compared to those who are monitored but not tracked.
• Defendants enrolled in the program had a lower probability of being rearrested for a DV offense during the one-year follow-up period, as compared to defendants who had been in a non-GPS condition (e.g., in jail, in an RF program, or released on bond without supervision).
• Those placed on GPS had a lower likelihood of arrest for any criminal violation within the one-year follow-up period.
• An examination of the relationship between GPS and legal outcomes revealed similar conviction rates for defendants on GPS and those who remained in jail during the pretrial period.
• Further, a comparison of conviction rates for GPS and RF defendants found a significant difference – with GPS defendants being likelier to be convicted as compared to RF defendants; also higher for GPS defendants compared to defendants released on bond without supervision, suggesting that defendants’ participation in GPS increases the likelihood of conviction.

The final component of the study is a qualitative investigation with stakeholders in domestic violence cases – victims, defendants and criminal justice personnel.

• Victims largely felt that having defendants on GPS during the pretrial period provided relief from the kind of abuse suffered prior to GPS, although they noted problems and concerns with how agencies and courts apply GPS technology.
• Benefits of GPS enrollment for defendants included protecting them from false accusations, providing added structure to their lives, and enabling them to envision futures for themselves without the victim.