“Be careful what you wish for” is an appropriate adage for the flourishing use and advancement of body worn camera (BWC) technologies. As police forces around the world adapt to increased demands for accountability – where every decision, reaction, and word can be analyzed in post-event forensic fashion – the need and desire to equip each police or federal agent with a continuously recording camera has grown.
There are pros and cons to every technology – both from technical capability and societal changes. The impartial and continuous recording of an event or confrontation places new stresses on those whose job is to enforce the thousands of laws society must operate within on a daily basis, in the knowledge that each interpretation and action could be dissected in a court of law at some point in the future. Meanwhile, “offenders” must assume that each action – hostile or otherwise – could fall afoul of some hitherto unknown law in fully recorded technicolor.
Recently the National Institute of Justice released a market survey on Body Worn Camera Technologies. There are over 60 different BWCs specifically created for law enforcement use and the document provides information on the marketed capabilities of this relatively new class of technology.
The technological features of the current generation of BWCs are, overall, quite rudimentary – given limitations of battery power, processing capabilities, and network bandwidth. There is however a desire by the vendors to advance the technology substantially; not just in recording capability, but in areas such as facial recognition and cloud integration.
Today’s generation of BWCs truly are the 1.0 version of a policing platform that will evolve rapidly over the coming decade.
I’ve had a chance to look a little closer at the specifications and capabilities of today’s BWC solutions and have formulated some thoughts to how these BWC platforms will likely advance over the coming years (note that some capabilities already exist within specialized military units around the world – and will be easy additions to the BWC platform once the costs to produce reduce):
- Overcome the bandwidth problem to allow real-time streaming and remote analysis of the video date. As cellular capabilities increase and 4G/5G becomes cheaper and more reliable in metro centers, “live action” can be passed to law enforcement SOC (just like existing CCTV capabilities). In cases where such cellular technology isn’t reliable, or where having multiple law enforcement officers working in the same close geographic proximity, the likely use of mobile cellular towers (e.g. as a component of the police vehicle) to serve as the local node – offering higher definition and longer recording possibilities, and remote SOC “dial-in” to oversee operations with minimal bandwidth demands.
- Cloud integration of collected facial recognition data. As the video processing capabilities of the BWC improves, it will be possible to create the unique codification of faces that are being recorded. This facial recognition data could then be relayed to the cloud for matching against known offender databases, or for geographic tracking of individuals (without previously knowing their name – but could be matched with government-issued photo ID’s, such as driver license or passport images). While the law enforcement officer may not have immediately recognized the face or it may have been only a second’s passing glimpse, a centralized system could alert the officer to the persons presence. In addition, while an officer is questioning or detaining a suspect, facial recognition can be used to confirm their identity in real-time.
- BWC, visor, and SOC communication integration. As BWCs transition from a “passive recording” system in to a real-time integrated policing technology, it is reasonable to assume that advancements in visual alerting will be made – for example a tactical visor that presents information in real time to the law enforcement officer – overlaying virtual representations and meta-data on their live view of the situation. Such a technology advance would allow for rapid crowd scanning (e.g. identifying and alerting of wanted criminals passing through a crowd or mall), vehicles (e.g. license plate look-up), or notable item classification (e.g. the presence of a firearm vs replica toy).
- Broad spectrum cameras and processing. The cameras used with today’s BWC technology are typically limited to standard visible frequencies, with some offering low-light recording capabilities. It is reasonable to assume that a broader spectrum of frequency coverage will expand upon what can be recorded and determined using local or cloud based processing. Infrared frequency recording (e.g. enabling heat mapping) could help identify sick or ailing detainees (e.g. bird flu outbreak victim, hypothermic state of rescued person), as well as provide additional facial recognition capabilities independent of facial coverings (e.g. beard, balaclava, glasses) – along with improved capabilities in night-time recording or (when used with a visor or ocular accessory) for tracking a runaway.
- Health and anxiety measurement. Using existing machine learning and signal processing techniques it is possible to measure the heart rate variability (HRV) from a recorded video stream. As the per-unit compute power of BWC devices increase, it will be possible to accurately measure the heart rate of an individual merely by focusing on their face and relaying that to the law enforcement officer. Such a capability can be used to identify possible health issues with the individual, recent exertions, or anxiety-related stresses. Real-time HRV measurements could aid in determining whether a detainee is lying or needs medical attention. Using these machine learning techniques, HRV can be determined even if the subject is wearing a mask, or if only the back of the head is visible.
- Hidden weapon detection. Advanced signal processing and AI can be used to determine whether an object is hidden on a moving subject based of fabric movements. As a clothed person moves, the fabrics used in their clothing fold, slide, oscillate, and move in many different ways. AI systems can be harnessed to analyze frame-by-frame movements, identify hard points and layered stress points, and outline the shape and density of objects or garments hidden or obscured by the outer most visible layer of clothing. Pattern matching systems could (in real-time) determine the size, shape, and relative density of the weapon or other hidden element on the person. In its most basic form, the system could verbally alert the BWC user that the subject has a holstered gun under the left breast of their jacket, or a bowie knife taped to their right leg. With a more advanced BWC platform (as described in #3 above), a future visor may overl
ay the accumulated weapon and hard-point detection on the law enforcement officer’s view of the subject – providing a pseudo x-ray vision (but not requiring any active probing signals).
Given the state of current and anticipated advances in camera performance, Edge Computing capability, broadband increases, and smart-device inter-connectivity over the coming decade, it is reasonable to assume that BWC technology platform will incorporate most if not all of the above listed capabilities.
As video evidence from BWC becomes more important to successful policing, it is vital that a parallel path for data security, integrity, and validation of that video content be advanced.
The anti-tampering capabilities of BWC systems today are severely limited. Given the capabilities of current generation off-the-shelf video editing suites, manipulation of video can be very difficult if not impossible to detect. These video editing capabilities will continue to advance. Therefore, for trust in BWC footage to remain (and ideally grow), new classes of anti-tamper and frame-by-frame signing will be required – along with advanced digital chain of custody tracking.
Advances and commercialization block-chain technology would appear at first glance to be ideally suited to digital chain of custody tracking.