Lieutenant Brian Ellis; Sacramento Police Department

It’s a Saturday night on the outskirts of the city limits when police receive a call from a distraught convenience store clerk reporting a violent robbery occurred and he’s been shot.  As police units respond to the emergency call, they are aided by connected vehicle technologies to control traffic lights to safely help officers get to the scene as quickly as possible, minimizing the possibility of a traffic accident en route.  Concurrently, data is relayed to the responding officer’s mobile computer without the need to search for it. This data pertains to the call the officers are being dispatched to, the persons involved, and the information about the environment. Information from nearby police observation devices also capture a license plate fitting the description of the getaway vehicle and broadcast it to responding patrol units.

Just prior to arrival at the original scene, another unit engages in a short vehicle pursuit with the getaway vehicle, ending in a nearby residential area. The suspect barricades himself inside a residence; the police are now in a standoff with an armed barricaded suspect and are searching for his nexus to the house he is now inside. As the incident commander responds, he is monitoring the event through real-time information monitoring, a program that encapsulates everything from bodycam video of the officer, pulse rate of the officer, and any other sensor-able connectivity into which the platform is connected.  Before tactical assets are even on-scene, computer information has the suspect’s identity via facial recognition taken from surveillance video uploaded into the police cloud; it links him to five other similar robberies in the last two months.

After the incident, all the data (everything from demographics, modus operandi, operational information, etc.) is analyzed. This establishes links to an opioid epidemic and eight other offenders who fit the general description of eleven additional property crimes in a small residential neighborhood across town.  All the while, the police department analyzes all parts of the report (including text); linking people and vehicles to other cases for follow-up.  Meanwhile, all crimes involving the event are reported to the federal government, giving light to the “darkness” of the mystery of the statistical world.  This information capture and analysis lets the public know just what the police are up against in the war on crime and delinquency. It also ensures any incident, including those involving a police use of force, is documented, analyzed and cataloged. In a larger context, it can illuminate the infrequency of police shootings to dispel rumors and provide truth to the reality of those incidents.  This is just one example of the power of connectivity and the Internet of Things (IoT) holds for the future of policing.

The Possibilities of the Internet of Things Are Endless

Throughout the last decade, the shift to digital dependence has fiercely snowballed, disrupting traditional policing.  In today’s world, as our digital footprint increases, so does the ability to collect and interpret information.  While uncommon in policing, the race of the Internet of Things (IoT) is at a fevered pace in the public sector (Elkheir, Hayajneh, & Ali, 2013).  Ongoing developments in computing and communication technologies have taken the world by storm, and it’s called IoT. The idea behind IoT is the connection of any electric device to the Internet and/or to each other; making everything from cellular phones to machines interconnected. The result is the IoT connects people to people, people to things, and things to things (Morgan, 2014).  IoT has the potential for 200 billion connected devices by 2020, and a trillion by 2025 (Peppet, 2014).  Because of the overwhelming opportunities and pitfalls IoT technology creates, it is imperative that public safety understands the opportunities and implications the IoT has to offer.

The Police Must Embrace and Use Innovative Technology

Although society’s expectations of public safety’s role in safeguarding our citizenry are rather similar from jurisdiction to jurisdiction, one of the greatest needs for change in American policing is the lack of standardization (Johnson, 2015).  With more than 18,000 local, state, and federal police agencies in the US, America is one of the most decentralized policing systems in the world (Roufa, 2017). One issue that contributes to the lack of uniformity across the US is the disparity in the various levels of funding for new technologies. Police departments that can afford new technology and equipment will make it happen; those who can’t will fall behind. It begs the question: can technology assist in the transformation of policing in America?

In just the last ten years, policing has rapidly integrated technology to aid in the development of operational readiness. For instance, the Sacramento Police Department utilizes police observation devices (POD) throughout the city. PODs have cameras that video record intersections as well as read license plates of vehicles travelling through (Heise, 2017).  The information is captured in real time, alerting officers to things such as stolen cars driving through. It’s also linked to a database used for criminal investigations, linking general descriptions from witnesses on the scene into cross referenced database with video and license plate technology to come up with leads to crimes police would otherwise not have. This global rise of technology has brought on an information age, bringing other benefits such as security and safety. For example, we have entered into a surveillance society, where safety and civil rights are in a tug of war (Lemieux, 2014). This is evident by the extensive amount of closed-circuit television (CCTV) monitors surveilling public and private spaces. There are more than 17,000 cameras in Chicago alone (www.vinetechnology.com).  CCTV’s alone have played a crucial role in several high profile criminal cases and has Americans reevaluating the role of surveillance platforms in public places (Dailey, 2013). Coupled with inexpensive sensors, cloud infrastructure, and advanced analytics, organizations and governments will take advantage of connected devices to drive efficiency and conservation (Seitz, 2016).  Unfortunately, American policing has not yet harnessed the data rich world to aid its problem-solving abilities to the greatest degree possible. Today is the time to interpret the vast data mines into something significant for policing in America.

Current advances in technology have accelerated the ability to collect, interpret, and analyze data; all of which can impact police organizations from efficiency to effectiveness (Luchetti, Mancini, Sturari, Frontoni, & Zingaretti, 2017).  The growing costs of labor, shrinking governmental budgets, and the public’s increased demand for transparency and performance should cause police agencies to look to new and innovative ways to utilize technology in the efforts to make better use of metadata. This increased efficiency could potentially reduce crime rates, save organizations time and money, and increase confidence in police by the public. IoT is on the verge of taking data to new heights and can help police organizations build greater abilities for operations, investigations, and transparency with the public; but is doesn’t come without a price.

Implications of IoT Technology for Law Enforcement Use

One implication of IoT technology will be new crime vectors that increase avenues of victimization through hacking of an individual’s digital footprint. In 2016 alone, more than 178 million records on Americans were exposed in cyberattacks (Wagstaff, 2016). And in the last three years there have been over 300 million hacks into secure databases, compromising everything from credit card information to personal information (Pagliery, 2014). Because of the unlimited possibilities to interconnect one’s life to the Internet, an increased amount of personal data will be available for all to see.  To compound the information struggle, most millennials are not as concerned with privacy, seeing their personal information as digital currency to be used to capitalize on goods and services (Fleming & Adkins, 2016). Privacy concerns will take a turn when victimization is present. Law enforcement’s challenge will be to safeguard the public’s digital footprint. This will not only increase the caseload of high tech crimes, but complicate the jurisdictional issues that already face policing.

A second implication in using IoT technology is the efficiency for law enforcement agencies – both operationally and managerially. IoT gives law enforcement the ability to synthesize metadata more efficiently, enabling faster collection and analytical responses to data (Williams, Burnap, & Sloan, 2017); thereby creating value in several ways.  The largest being the ability to better connect people to information.  Sensor development will continue to increase (Elkheir, Hayajneh, & Ali, 2013), and one can see a day where police are tracked with sensors on anything from their skin to clothing and equipment to allow agencies to collect vital information where it can be used from everything from operational management, criminal prosecution and training environments.  An example would be the ability of investigators to use data points to validate a person’s alibi, to the collection of data at crime scenes; everything from surveillance to Alexa-like devices.  This will increase value to public safety by allowing officers to make faster and better decisions.  It can also help in the illumination of the police story.

A third implication of IoT is that it will provide law enforcement an opportunity to remedy what skeptics call a lack of data collection on policing in America. Ex-FBI Director James Comey described the lack of government data regarding policing “embarrassing” and “ridiculous” (Berenson, 2015), leading to a national credibility issue on the topic of statistics surrounding police shootings in the US. More data promises us the ability, albeit using computing, to become contextually aware of organizational, operational, and communal problems.  While current IoT technology is in the phase of collecting data, fast approaching is the shift to understanding and utilizing the data for better outcomes (Oswald, 2016).  Data for police organizations will not only be limited to part one crimes and/or demographics about suspects and victims, but can search for elements of crime and social patterns in everything from people, places, things and environments.  This information will be sent back to computers for further evaluation and synthesis, and finally to the operator to make more informed decisions.

Faster analytical responses will affect the process development and management capabilities of police organizations (Cisco, 2014).  Managers and executives will have more intelligence at their fingertips on issues related to people, events, and line level approaches to problems.  The content can deliver better situational awareness in the field for the incident commander or supervisor; and also to the manager or executive providing justifications for new police initiatives.  IoT can have local and national implications on the collection, use, and interpretation of data being used for public safety needs, so long as law enforcement leaders are thinking about ways to exploit the opportunities of this technology.

The IoT Integrated Into Law Enforcement’s Future Operations

Despite significant advances in technology, data collection and interpretation has remained mostly a manual process in police organizations. The evolution of algorithms and data has tremendous benefit- most importantly increasing the ability to identify suspects and problems faster while finding ways to work smarter and harder. The integration of IoT technology into law enforcement will not only aid police organization’s ability to solve crime, but will also uncover issues before they rise to epidemic proportions.  This has significant impacts to the effectiveness of the role of the police while boosting the public’s confidence in the work police do.

Police leadership is responsible to forecast the future and provide adaptive challenges for their organization’s health and vitality in serving their public. Living in an era where technology is increasing its prowess, the police must engage the technological superhighway to advance our profession and better the safety of our citizenry as a whole. IoT technology will bring efficiencies and effectiveness to the workplace, but not without a price.  The new crime vector that IoT brings will increase public safety’s workloads although the technology does have more upside than down.  The transparency piece of IoT will help connect the unconnected, illuminating the issues that do contribute to crime, delinquency, and the public safety experience in America.  While budgets restrict organizations, data expands our reach, and no public safety organization will be as effective as they can be without it.


Berenson, T. (2015). FBI head calls lack of data on police shootings ‘embarrassing.’ Time magazine.  Available [Online] at http://time.com/4066558/police-shootings-data-fbi/

Cisco Corporation (2014).  The connected public safety agency: How the age of mobility is transforming public safety agencies.  Available [Online] at http://www.cisco.com/c/dam/en_us/solutions/industries/docs/public_safety_mobility_whitepaper_us.pdf

Dailey, K. (2013). The rise of CCTV surveillance in the US. Available [Online] at http://www.bbc.com/news/magazine-22274770

Elkheir, M., Hayajneh, M., & Ali, N. (2013). Data management for the Internet of Things: design primitives and solution.  Sensors Journal.  Available [Online] at  http://www.mdpi.com/1424-8220/13/11/15582

Fleming, J., & Adkins, A. (2016). Data security: Not a big concern for millennials. Gallup Poll. Available [Online]: http://news.gallup.com/businessjournal/192401/data-security-not-big-concern-millennials.aspx

Heise, S. (2017). So what exactly do those Sacramento police PODs do? Available [Online] at http://www.kcra.com/article/so-what-exactly-do-those-sacramento-police-pods-do/10217039

Johnson, K. (2015). Lack of training, standards mean big problems for small police departments. Available [Online] at https://www.usatoday.com/story/news/nation/2015/06/23/small-police-departments-standards-training/28823849/

Lemieux, F. (2014). Democratic policing: What it says about America today. Available [Online] at https://theconversation.com/democratic-policing-what-it-says-about-america-today-35066

Luchetti, G., Mancini, A., Sturari, M., Frontoni, E., & Zingaretti, P. (2017). Whistland: An augmented reality crowd-mapping system for civil protection and emergency management. ISPRS International Journal of Geo-Information. Available [Online] at https://doaj.org/article/25893e137c14445e9ecceb9f092ba7c8

Morgan, J. (2014). A simple explanation of ‘the Internet of Things.’ Forbes. Available [Online] at http://www.forbes.com/sites/jacobmorgan/2014/05/13/simple-explanation-internet-things-that-anyone-can-understand/#6ef9e9a36828

Oswald, M. (2016). Algorithmic policing and freedom of information – how far should transparency extend? BSC Policing Network. Available [Online] at

Pagliery, J. (2014). Half of American adults hacked this year. CNN News. Available [Online] at http://money.cnn.com/2014/05/28/technology/security/hack-data-breach/

Roufa, T. (2017). How police are different around the world. Available [Online] at https://www.thebalance.com/how-police-are-different-around-the-world-974595

Seitz, B. (2016). The importance of IoT data collection. Available [Online] at https://buddy.com/blog/importance-iot-data-collection/

Williams, M., Burnap, P., Sloan, L. (2017). Crime sensing with big data: The affordances and limitations of using open-source communications to estimate crime patterns. The British Journal of Criminology.  Available [Online] at https://academic.oup.com/bjc/article-lookup/doi/10.1093/bjc/azw031




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