What Big Data Means to Public Safety, Part 2

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The buzz word “big data” has been around in information technology for a while, but only recently has it been correlated with Public Safety. While big data is defined as data sets whose size or type are beyond the ability of traditional relational databases to capture, manage, process and analyze; it also incorporates components of artificial intelligence (AI), mobile data, social media and the Internet of Things (IoT), including data from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media.
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The buzz word “big data” has been around in information technology for a while, but only recently has it been correlated with Public Safety. While big data is defined as data sets whose size or type are beyond the ability of traditional relational databases to capture, manage, process and analyze; it also incorporates components of artificial intelligence (AI), mobile data, social media and the Internet of Things (IoT), including data from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media.

A key question is, what does big data bring to Public Safety, especially to dispatch centers, law enforcement agencies, fire departments and EMS teams. Let’s examine what pieces of big data could be used in Public Safety applications:

  • Local and regional agency data and information
  • State and federal data and information
  • Government and private GIS mapping and GPS data
  • Electric and water grid information
  • Video feeds from government and privately owned cameras located at major thoroughfares, city streets, intersections, buildings, schools, high rises, individual businesses and homes
  • Video feeds from Body Worn Cameras
  • Social media feeds
  • Smartphone information
  • IoT in vehicles and body sensors
  • Smart city data and information such as traffic signals, traffic flow, bridges, etc.
  • Incident information captured electronically by either public safety officers or citizens
  • Facial and symbol recognition (i.e. gang tracking, tattoo association)
    There are a number of national public safety organizations that are working on developing and defining standards as they could apply to Big Data.  For example, APCO is working on several NG911 standards including the National Information Exchange Model (NIEM) standard to define how external information can flow to Public Safety agencies. While the NIEM standard doesn’t specifically address big data, it could be a conduit to transport big data within Public Safety agencies. In addition, the National 911 Program office within the U.S. Department of Transportation National Highway Traffic Safety Administration recently released volume 1.0 of the 911 Data and Information Sharing Strategic plan, outlining the 911 community’s need for a data and information sharing environment to enable NG911 transition efforts. 

The larger issue of big data is how can it be consumed and made actionable by Public Safety software applications, such as Computer Aided Dispatch (CAD), Mobile, Records Management Systems, (RMS), Fire Management Systems (FMS) and Emergency Medical Systems (EMS). There are currently two ways that big data could be consumed by these software solutions. Each CAD, Mobile, RMS, FMS and EMS vendor develops a separate interface to each of the different big data types, or a middleware software product is utilized to manage all of the different big data types and disseminates the information to the various software solutions in an actionable format. But no matter if a standard data exchange mechanism, such as the NIEM standard, is utilized; for big data to be useful, it needs to be analyzed and disseminated based on relevance, need to know and if an action is required.

For example, large corporations have been using big data for location tracking, fraud detection and predictive purchases of consumable goods such as food, medication, clothing, etc. as well as large purchase items such as vehicles, appliances, homes, etc., for years. They target consumers, businesses and services to better serve their own clients. This same predictive big data analysis can be applied to Public Safety agency operations.  Similar analyses of big data can help agencies act faster and smarter in dealing with emergency responses, and allocation of resources, particularly in time sensitive situations. Big data analysis could also be used to more effectively deal with situations such as demonstrations, hostage situations, shootings, terror attacks, etc., and manage overall operations more effectively.  The key is integrating big data analytics into everyday processes and workflow of police, fire and EMS operations.

Big Data is not only here to stay, but will continue to play an increasingly important role in public safety. As artificial intelligence (AI) evolves; big data will become critical in developing operational strategies for Public Safety agencies to serve citizens more effectively and efficiently. Agencies need to start analyzing and defining what role big data can play in their agency, and in cooperation with other agencies to improve emergency response and internal process flows.

There are immediate steps agencies can take to incorporate big data analytics technology into their current public safety databases. Big data analytics are designed to mine data from a variety of databases and provide a view into the data that is both a visual view; including maps, graphs and dashboards, and a data view including statistics, trends, patterns and relationships.

All of this information is useful to schedule resources, predict crime trends and provide situational awareness. Agencies can work with other city and county departments including transportation, permits, traffic, inspections, etc. to include their specific information in the big data analysis and predictive modeling process. Utilizing big data analytics on internal databases provides immediate results, and is a great stepping stone toward importing data from outside sources that are both relevant and actionable. Agencies and IT departments can first utilize this technology on internally available data prior to venturing to outside governmental and business sources for additional data. This provides the agency and IT a way to learn and implement big data analytics technology on internal systems, and start the planning process to add external data sources as they become available.           

Since utilization of big data relies on cooperation, we suggest:

  • Working with internal departments to define roles and responsibilities on how data will be accessed and processed by big data analytics technology
  • Establishing intra- and inter-governmental agreements with guidelines on how big data analytics will be implemented
  • Developing plans and implementation strategies to securely connect big data analytics technology to relevant internal databases
  • Developing plans to import data from outside agencies, governmental units and businesses to be included in the big data analytics technology
  • Developing a definition of roles and responsibilities on how big data will be incorporated into your agency’s operations and emergency response


Develop an IT strategy for big data analytics technology including the following steps:

1)   Assess current databases for inclusion of big data analytics technology; include connectivity, physical and cyber security and data access

2)   Assess current Public Safety software applications’ ability to consume and integrate big data analytics into processes and workflows 

3)   Develop a big data analytic technology acquisition strategy and implementation plan

4)   Develop a pilot project plan to utilize big data analytics with dispatch, law enforcement, fire and/or EMS. The plan needs to contain:

  • a needs assessment
  • benefits analysis
  • cost and time estimate
  • an implementation plan and timeline of 6 to 12 months to prove the legitimacy of the big data analytics technology

5)  Develop a long-term plan to implement other internal and external big data sources

6)   Work with public safety software application vendors to utilize big data within their CAD, Mobile, RMS, FMS and EMS applications

7)   Work with big data contributors to ensure information is secured and reliable

8)   Work with vendors that manage big data to ensure that only relevant and actionable data is passed to the public safety software applications

9)   Explore regional Public Safety and business big data opportunities

 

In conclusion, big data is coming and agencies that take a proactive approach in planning the implementation of a big data strategy will be better prepared to improve operations, emergency response, public relations and situational awareness. Winbourne Consulting has extensive experience in all areas of Information Management – from establishing a “Big Data” master plan to implementing a Business Intelligence/Data Warehouse solution.  For additional information, contact Winbourne Consulting at info@w-llc.com.

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