The Future of First Response & Emergency Management: New Technology Considerations

The mission critical communication industry is moving towards enhancing the effectiveness of first responders by making multiple streams of information in various modalities, or multimedia, converge; a.k.a,, unified communications. This includes bringing together voice (Land Mobile Radio; Cellular; PSTN (telephony); VoIP; Video / Data).

This is underway as we are moving away from legacy circuit-switched technologies to interoperable and secure IP-based network-centric services that deliver video, file transfer, and unified messaging. And it is being operationalized on a transport layer: a mobile networking infrastructure (e.g., 4G LTE; FirstNet; IP-based interoperable platform) to deliver this [converged] rich information at the tactical edge to the first responder in the field.  This connectivity works both ways (inbound / outbound). The first responder(s) and commanders at the incident site should not only be able to communicate, capture information, query databases and stream multimedia information but also share what they have onsite with cohorts and/or reach back into the chain of command.

This degree of connectivity, communicability and flexibility made possible by the evolution of technology is both a boon and if not designed well from a human factors standpoint a bane.  

In this article, I briefly discuss the "boons." That is, how technology when designed well, by taking into consideration human factors (cognitive/physical capabilities & limitations) and organizational structure and cultures in which they perform, can amplify first responder capability. In other words, become a force multiplier.

Consider firefighting (structure and wildland fires), where both voice and data integration is being explored by equipment manufacturers and first responder organizations. This includes, but is not limited to, transporting data -- e.g., database interrogation, remote sensing, and telemetry, or computing data in situ, as part of a cognitive computing or intelligent network.  This may include a variety of data sets that range from alarm type, incidence location, geo-location, building layouts, hazmat info, etc., for structure fires; and meteorology, topology, fuel source,, etc., for wildland firefighting.  Last, but not least, some of the industry players are also moving towards tracking individual fire fighter's physiological measures, location / presence, etc., to monitor health, safety and performance, on the fire ground.

Next, let us look at law enforcement, which I will use to explain the elements of what is known as a "socio-technical system" or STS. If a police officer has to succeed at the tactical edge, s/he needs to be networked and connected with the rest of the players and technologies that make it happen. This amalgamation of personnel and technology(s) in an organization, with its own culture, structure, goals, and how it utilizes technology to get work done, is a "socio-technical system."  

Law Enforcement Socio-Technical System (People + Technology)

Brief HVHF note on how technology may either hinder or amplify first responder performance at the tactical edge. Available here.

Thus the design of a network or a handheld device can't be seen in isolation. If they have to be effective, their design should take into consideration both human interaction with it and how well it is integrated to accomplish organizational goals.  For example, wireless communication dead-spots, frequent outages, slow network speeds, sub-optimal preempting/prioritizing & squelching protocols or difficulty in maintaining the system or troubleshooting equipment can result in inefficiencies, low throughput and loss (human lives to property) in a first responder context.  Furthermore, it needs to take into account cultural and structural factors such as chain of command dynamics, centralization vs. decentralization, conformity vs. customizablity, operational doctrine, cultural power distance, short term thinking vs. long term orientation, policies, politics, intra/inter-organizational issues, budgets (equipment to training), etc.

So what is the ideal architecture for the human-machine interface for first responder technology?  How does one filter raw Data, to identify mission critical & essential Information that are relevant to the incident.  Next, put that information into context -- so that it is transmuted into actionable Knowledge for all stakeholders at the incident-site (e.g., enriching situation awareness and mental models of the progress & containment of the fire, search & rescue, safety, etc., for fire fighters & commanders). See Figure below. 

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RAW DATA (when filtered for relevancy) → (and put into context, inline with current goals) turns into mission critical & eseential INFORMATION → (when this information is presented in a format, mode or medium where it could be accurately understood) then it turns into useful and actionable KNOWLEDGE 

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To accomplish the above goal, a data rich ecosystem should, of course, first be data-driven, but then should be information-based and knowledge-led to be successful. This could be accomplished by abstracting the human-technology interface into three layers:

1. physical / graphical user-interface (provides the perceptual gist from a semiotic and affordances standpoint); 
2. cognitive interface (couples the physical / graphical user-interface's affordances, semiotic & information architecture with the work-related goals and mental models of the technology that the user brings to the task -- which produces a conceptual gist in his/her mind); 
3. epistemological interface (aiding via predictive/prescriptive analytics and enabling the comprehension of relevant, goal supporting information -- nudging the human agent to take a certain course of action (CoA) among a set of choices, resulting in a CoA gist). 

The means to this end could range from exploiting commercial off-the-shelf technologies that might range from hardware or software / apps; or it might involve developing new products (if none exist off-the-shelf) to close the gap. 

But how does one determine what is the appropriate technological solution? Applying technology for technology's sake, or because it is there, is a dangerous proposition in a first responders' world. It could occlude his senses (e.g., poorly designed heads-up display), diminish situation awareness, not constructively aid decision making on the fly, which might eventually lead to the misuse or disuse of expensive technology; or worse yet, may result in wrong decisions and lead to catastrophic outcomes. 

Thus, first and foremost, we need to understand what is that we are trying solve. It begins by asking the right questions. The place to begin is cognitive ethnography (field research) to actually observe first responders performing their work in the field. It could be real events in real time and/or simulated ones like drills. (Asking questions to first responders in a closed room, out of context, via a focus group may provide partial answers. They are unlikely to be accurate; people say things that they thought they did in a time stressed situation, but in reality they may never have done it. Memory is fragile. It is distorted due to stress, lapses and  decay due to passage of time). 

The data collected from cognitive ethnography should be followed by a rigorous human factors design analysis to ideate, innovate and conceptualize usable and utilitarian solutions. 

The last step is to identify technology that can be either adapted off-the-shelf or developed from scratch. They are the portable / wearable / mobile / fixed devices, network infrastructure, and platforms (data centers, transport, service architectures) -- their form factors and user-interfaces -- that will accomplish the above stated goal of developing usable and utilitarian solution for first responders.

Thus when a technology is designed with a user-centered focus and driven by human and socio-technical factors, it can turn it into a great boon -- a "force multiplier" by delivering the following benefits:

• Context sensitive information that yields knowledge (situation awareness, sensemaking, accurate analytics-driven decision-aiding).
• Hyper-intuitive user-experience, even under stress (when first responders' cognitive resources are depleted), that makes technology second nature and delivering utility to the first responder at the tactical edge or for personnel in the back-end of the system.
• Effective C2 (command & control): Locus of control for commander and emergency managers; and resilient delivery of first response and emergency services.

So before we conclude how cool that Google Glass will be on a first responder or Siri voice interface for light and siren controls inside a police car; or as a technologist get on the drawing board to design something from scratch; or as a purchaser in a first responder department making a purchase decision about a particular vendor's technology; let us pause and ask ourselves what is that we are trying to solve?: both from the back-end and at the tactical edge.

About the author:

Moin Rahman is a Principal Scientist at HVHF Sciences, LLC. He specializes in:

"Designing systems and solutions for human interactions when stakes are high, moments are fleeting and actions are critical."

For more information, please visit:

http://hvhfsciences.com/

http://www.linkedin.com/in/moinrahman

HVHF Article Archive: http://hvhfsciences.blogspot.com/

E-mail: hvhf33322@gmail.com

FirstNet Public Safety Wireless Broadband Network: User-Centered Design and Human Factors Driven Engineering of NextGen Public Safety Network

Data, Data, Everywhere...

The New York City Police Commissioner Raymond Kelly testified to Congress last year that 
“a 16-year-old with a smart phone has a more advanced communications capability than a police officer or deputy carrying a radio.” 

10-4 ... Roger that! 

And, if I may add, the 16-year old revels in the data deluge delivered by this "advanced communications capability": Facebook, Twitter feeds, IM, SMS, YouTube, Spotify, and you name it! The young man or lady is socially connected, entertained and is up to speed with the goings-on in his/her social network. But how well does this apply to a mission critical, first responder such as a police officer, fire fighter or paramedic? 

There is no doubt about the need for an advanced communications capability for first responders. However, the first responder doesn't wish to be drowning in a data deluge that is devoid of immediately useful and actionable information or intelligence. His refrain would be "data, data everywhere, but where is my byte that matters most???"

Simply put, our mission critical professional has no time to google, mapquest, tweet or watch a video. In other words, a first responder on call doesn't have the time to:

• google to figure out the nature of the domestic violence incidents at a particular house
• mapquest a street in response to a fallen colleague's mayday call broadcast to get there within the "platinum 10" [minutes] and provide basic life support.
• tweet during a hot pursuit to warn citizens that a fugitive is driving at high speed on the wrong side of a highway
• watch a video-tutorial to compare the situation on hand and receive guidance on delivering advanced life support / antidote to a grievously poisoned citizen.

Drowning in Data, But Where is the Information?

Obviously, the public safety communication infrastructure and the subscriber units (the handheld 2-way portable radios and vehicle-based mobile radios, data devices, computing technologies, etc.) used today do not have the bells and whistles of an iPhone. Or to go back to Police Commissioner Kelly's analogy, they are unlike the 16-year old's smart phone with processors and chipsets generating bewitching animations -- and more importantly pumping unlimited data from a fat pipe (a 4G LTE wireless broadband network). 

But in the process, what we also forget is the fact that the 16-year old is enjoying his streaming music and emitting his tweets when his commercial-grade wireless network is standing like the Rock of Gibraltar. For example, it has not been physically attacked, virtually hacked or brought down by peak demand due to a natural disaster or terrorist attack.  Furthermore, the 16-year is doing all this in a threat-free situation, where his heart rate is not surging or the adrenalin and cortisol (stress hormones) are not coursing in his veins, prepping him for a fight or flight response. The good young man is neither in the situation of a hotshot surrounded by a raging forest fire nor is he a paramedic trying to figure out the best way to stop an arterial bleeding of an accident victim with a punctured lung and fractured vertebrae. 

Enough said!

A first responder is unlike you and me, the consumer. More often than not he is functioning in a system that is in non-equilibrium, where High Velocity Human Factors or "HVHF" comes into play.

On to Mission Critical / Public Safety Communication

The evolution of public safety communication networks (APCO P25 in North America, Figure 1; TETRA in Europe) have been slow from the days of the analog conventional radios that were so large they could only fit in the trunk of a car. But over the years they acquired the traits of the Rock of Gibraltar: hardened and solid in terms of survivability; reliability; security; velocity of voice comms.  For example, they have redundancies built into the base station and site controllers so that a single point failure doesn't take all communications down. And they are catching-up with their cousins in the defense space (JTRS: Joint Tactical Radio System): where the network is not only resilient but intelligent (self-healing and self-connecting networks; cognitive radios with programmable wave forms, which might change attributes on the fly depending on the communication link: rifleman to manpack radio in an Abrams Tank, or from from a Humvee to recon aircraft hundreds of miles away.)

Figure 1: The APCO P25 communication network was a major step towards standardizing disparate communication systems via a CAI (Common Air Interface), which was also backward compatible (worked with legacy analog, conventional systems), with the goal of promoting interoperability
(Source: Electronic Design)

Public Safety comms. have their weaknesses as well, the biggest one being lack of interoperability as they are fragmented, unconnected and constrained due to technology, jurisdiction and inter-organizational cultural impediments. Say, the Fire Department in County X may not be able to communicate with the one in County Y. Put in consumer-communication speak, if you are a Verizon subscriber from New York visiting Miami, you can't call the local restaurant because they subscribe to AT&T Wireless and land line telephony.

FirstNet: Sociotechnical-based, User-Centered, Human-Engineered NextGen Public Safety Networks

A brave new initiative called FirstNet -- a rugged, public safety-grade broadband wireless network -- seeks to retain the strengths of existing public safety communication networks but overcome its weaknesses (from lack of interoperability to the narrowness of its data pipes) is in the works.  

The design and deployment of FirstNet, including the subscriber units (portable radios to mobile computing technologies), have to considered with great care so that it delivers both utility and usability. This is no casual communication; life and limb are often on the line.

Thus the goal here is not to drown the first responder with data because one has gotten hold of a fat pipe (broadband wireless network). In fact, for some mission critical use cases, (a data deluge) more data maybe worse than no data! Simply because, the constant data pings and voice chatter may distract the first responder from his primary task of saving someone. Remember HVHF! Under stress he has limited cognitive resources and they are precious. He needs to put all his attention and cognitive effort in either focusing on the threat or putting out a raging fire. He has no mental bandwidth left to idly monitor the goings-on in his network or surf the data that his streaming through his device.

To get mission critical communication design right, let's first, well, get to first principles.

What is Communication?

In its simplest form, communication results in the transmission of information, from a transmitter, with the goal of making the Receiver aware of something that he would otherwise be ignorant of (Figure 2).  Ideally speaking, the integrity of this communication should not be compromised either while being encoded (transmitter-end) / decoded (receiver-end), or due to "noise" (garbled) by a weak signal or cross-talk.  Here are three examples of mission critical communication: 

• First responder at the accident scene communicating to dispatch; "Life threatening injury; need paramedics and transport to Level 1 Trauma Center."
• Police officer after pulling over a vehicle [accessing data]: Interrogating a remote database for driver's license and registration information.
• Accident Investigator: [video] Recording and transmitting video (evidentiary information for forensic analysis and/or to be used in court).

Figure 2: Mathematical Theory of Communication (cf. Claude Shannon)

Communication -- be it one-way, two-way, multi-way (conference call style, a.k.a., "TalkGroup" in public safety comms.) -- is all about context: e.g., seeking immediate rescue; enhancing situation awareness to prevent friendly fire; or enable sensemaking in a complex wildland firefighting scenario.

Thus communication, particularly one that is technologically enabled, to be successful needs to consider the social & organizational context; users' information and communication needs; and human cognitive & physical capabilities and limitations. These are discussed next.

Socio-technical System (STS) Based

Consider a major natural disaster such as Hurricane Sandy. Several entities from FEMA, federal to local government agencies coordinate emergency management, search and rescue. When designing a comm. network, one has to take into consideration the intra- and inter-organizational factors among the various government agencies, in deciding, planning, collaborating and managing their work. This may encompass written procedures, trained responses, tactics, techniques and procedures, politically and legally mandated protocols -- and last but not least cultural factors (good and bad).  

As an example, FEMA's incident command system (ICS) is a scalable and manageable command and control system with the goal of integrating local, county, state, and federal assets to provide the most effective first response from a category IV Hurricane to a terrorist attack.

Figure 3: Incident Command System

As seen above, a fat pipe (broadband) may be a necessary but not a sufficient solution for effective communication. It needs to be agile so that it either self-configures (or is easily configured by a technician) on the run in real time (by recognizing the infrastructure [base station, site controllers, repeaters, etc.] and, last but not least, the plethora of subscriber units, which could range from portable radios, mobile computers, including consumer tablets and smart phones (BYODs); It must be intelligent and know what and which type of voice or data traffic to prioritize; It must be adaptive to the situation on hand so that it morphs (e.g., cognitive radio) to exploit the available RF spectrum to deliver connectivity on the ground to into the cloud. 

PLUS, the network should be hardened and have all the required attributes for public safety grade communications: survivability, reliabiity, security, interoperability, etc.

User-Centered Design

Consider a sampling of mission critical professionals: A hotshot battling a wildfire in a gulch, an EMT providing basic life support to a gunshot victim, or an officer with a search warrant have different goals, situational context in which decisions have to be made and informational needs. 

• The hotshot serving as a lookout may require live meteorological and topological information and needs to be networked with the central command and his cohort, hotshots on the fireground; 
• An EMT may have to look-up electronic health records of the victim for any pre-existing health conditions and contraindications and be in touch with the receiving ER physician; 
• An officer with the search warrant who has descended to the basement might find himself cornered with no network signal and, thus, has to use Direct Talkaround to his partner in the floor above to summon help. 

Thus the information ecosystem and the communication networks shoud be user-centered in terms of delivering useful, usable and actionable intelligence in realtime to the mission critical professional. They could either be delivered on demand or with predictive analytics that carefully sifts through data to deliver useful and situationally relevant information.

Human Factors + Ergonomics + Cognitive Engineering

This final piece concerns the mission critical professionals themselves: the human operators, their physicial / cognitive capabilities and limitations; and how they have to be integrated into the public safety communication socio-technical system.  There are several layers to this integration, and one of them is the human-machine interface (HMI), also known as UI (user-interface). This covers both the physical (knobs, buttons, keys) and graphical user-interfaces (information architecture and human-computer interaction design) on the devices with which they interact: handheld / vehicle-mounted radios, tablet-computers, command & control computers, etc.

Whether it be a normal operational situation or an emergency, and, thus, an abnormal situation, the user-interface for any and all technology should be intuitive and usable. Furthermore, depending on who the mission critical user is -- e.g., front line first responder, commander or network administrator -- it should as an useful cognitive interface as well: augment their senses and deepen their comprehension of what is going right or wrong in the mission-space. This is critical, because they are the first and last line of defense with regards to protecting precious assets, from human lives to property.

The Fat Pipe Filtered: Data to Information to Knowledge

A communication network (Core to Nodes to Subscriber Units) when designed by applying an STS-based, user-centric, and human engineered approach gets its closer to the ideal solution -- where technology is used to amplify human capability. Simply put both the technology and human agents in the STS should work as peers and partners -- a joint cognitive system -- to produce best results. In other words, when an algorithm fails to provide the answer when confronted with a novel situation a first responder may solve it with his sudden flash of insight. On the flip side, the technology maybe the best handyman when a sensor, search and analytical engine does what it does best:  connecting an automatically scanned license plate to a stolen car, or using facial recognition technology to recognize the face of a man who is wanted for hacking ATM machines in a different state.

It is good to be gung-ho about new, better and faster technology. But technology should not be celebrated for technology's sake. So let me summarize what I have discussed so far in this article in the context of FirstNet, the public safety broadband network being designed in the United States: 

The purpose of FirstNet is to deliver actionable information at a high velocity -- which is comprehensible via an intuitive user-interface -- and not terabytes of useless data.  It must equip and enhance the capability of our public safety professionals.  It is a fallacy to entertain the mistaken notion that a Public Safety Broadband Wireless Network will do the first responding and the first responders will be transformed into IT workers who are busy manning the equipment.

About the author:

Moin Rahman is a Principal Scientist at HVHF Sciences, LLC. He specializes in:

"Designing systems and solutions for human interactions when stakes are high, moments are fleeting and actions are critical."

http://hvhfsciences.com/

http://www.linkedin.com/in/moinrahman 

E-mail: hvhf33322@gmail.com

Funnel Cognition: How Macrocognition can inform Successful Adaptations in Competitive Tennis

Megginson (1963) citing Charles Darwin’s theory of evolution in the context of business management observed “…it is not the most intellectual of the species that survives; it is not the strongest that survives; but the species that survives is the one that is best able to adapt and adjust to the changing environment in which it finds itself.” This applies equally well when the ecology is no longer the natural habitat of a species but a tennis court on which the competitive tennis player (singles) finds himself at the appointed hour for a duel with his opponent. The tennis player on this occasion encounters a few invariants (personal racket, balls, court dimensions, rules, etc.) but also is confronted with a large number of variables. They range from exogenous variables (e.g., wind speed, crowd support, opponent’s physical & mental states, including his tactics and strategic intent, etc.) to endogenous variables (e.g., one’s own physical and mental states, fluency in execution on that particular day of practiced perceptual-motor skills, among others). Needless to say, the player has to rapidly make sense of these variables and develop strategies to overcome them through adaptations, without any external assistance, as no coaching is permitted in professional tennis. The ultimate goal obviously is to use these adaptations to his advantage to increase his likelihood of winning the match.

The 2013 Wimbledon Finalists Andy Murray and Novak Djokovic who are known to be Deep Thinkers and the most Adaptive Pro's to the Circumstances on the ATP Tour

I will discuss how a player can make such dynamic adaptations, not at the tactical level (e.g., whether to hit a drop shot vis-à-vis a top-spin ground stroke in a particular situation), but at a strategic level – i.e., by utilizing the information contained in the aforesaid variables to make advantageous adjustments. It will be shown that this could be accomplished by building a set of macrocognitive skills, specific to tennis, which are referred to as “funnel cognition” (as opposed to “tunnel cognition.”) This is tantamount to integrating information from a wide range of input variables (akin to the inflow-mouth of a funnel) to develop a hypothesis on current system state, which is a form of pre-kinetic, situation assessment (even before a ball is hit); this would be used to develop a specific strategy that is apropos to the situation on hand (the outflow from the funnel’s stem). Next, during the post-kinetic periods – brief breaks between points, games or sets – the player may reassess the situation again at a macro cognitive level by making suitable assimilations and accommodations (Klein, Moon & Hoffman, 2006) to redefine or refine the strategy. At least two well known approaches from Human Factors sciences – Sensemaking (Weick, 1995) and situated cognition (Suchman, 2007) – used in the context of human-systems design are applicable to sports such as tennis, where the embodied athlete has to solve high level problems without the assistance of an external agent (coach or technology). These formalized approaches and applicability to tennis have received little attention. Most of the analyses, that can be considered cognitive, has been done do develop and hone tactical skills for the kinetic phase in tennis (Teltscher, 2006; Elderton, 2010). It should also be noted that these macrocognitive skills discussed in this talk differ from the microcognitive, perceptual-cognitive skills – centered around direct perception of a projectile (Iacoboni, 2001), its effective anticipation (e.g., Singer, Cauraugh, Chen, Steinberg, Frehlich, 1996) and decision making (Elderton, 2010) – which usually fall under the rubric of “game intelligence” (Stratton, Reilly, Richardson, Williams, 2004) in sports research and literature. The latter have been widely studied by sports psychologists (for a review see Casanova, Oliveira, Williams, Garganta, 2009). Finally, how macrocognitive skills can be formally inculcated to competitive tennis players through methods such as Instance-based Learning Technique (Gonzalez, Lerch, Lebiere, 2003) will be discussed in a future article.

The science of human performance under high stakes and stressful situations discussed in this article shares many characteristics in domains such as first response, warfighting, piloting, emergency medicine, process control in abnormal situations, among others. 

Although, sports does not have life and death implications it can serve as a live laboratory to study cognition and decision making under high stakes and time stress. Knowledge gleaned from this may even contribute to the field of "comparative cognitive engineering."  Ultimately, the this will not only inform sports training and technology, but can also facilitate "antifragile" (cf. Nassim Taleb) approaches to design human-technology interaction in mission critical systems (first response to healthcare). So that the human agents such as first responders, pilots, emergency physicians -- and systems, particularly smart technologies that "learn" in real time -- adapt to stress and even gain from it. Much like an athlete getting stronger from the stressors (real and simulated) imposed on him / her during training and match play. 

REFRENCES

Casanova, F., Oliveira, José, Williams, M., Garganta, J. (2009). Expertise and perceptual-cognitive performance in soccer: a review. Revista Portugesa de Ciências do Desporto, 9(1), 115-122.

Elderton, W. (2010). 21st Century tennis coaching: Learner-centered principles for the game-based approach: manual by Wayne Elderton, available from ACE coach http://www.acecoach.com/main/manuals/

Gonzalez, C., Lerch, J.F., Lebiere, C. (2003). Instance-based learning in dynamic decision making. Cognitive Science, 27(4), 591-635.

Iacoboni, M. (2001). Playing tennis with the cerebellum. Nature Neuroscience, 4(6), 555-556.

Klein, G., Moon, B., & Hoffman, R.R. (2006). Making sense of Sensemaking 2: A macrocognitive model. IEEE Intelligent Systems, 21(5), 88-92.

Megginson, L. (1963). Lessons from Europe for American Business, Southwestern Social Science Quarterly, 44(1), 3-13.

Singer, R.N., Cauragh, J.H., Chen, D., Steinberg, G.M., Frelich, S.G. (1996). Visual search, anticipation, and reactive comparisons between highly-skilled and beginning tennis players. Journal of Applied Sports Psychology, 8(1), 9-26.

Stratton, G., Reilly, T., Richardson, D., Williams, A.M. (2004). Youth soccer: From science to performance. London: Routledge.

Suchman, L. (2007). Human-machine reconfigurations: Plans and situated actions (2nd Ed.). New York: Cambridge University Press.

Teltscher, E. (2006). Keep your strokes, change your game. Tennis Magazine.

Weick, K. (1995). Sensemaking in Organizations. Thousand Oaks, CA: Sage.

About the author:

Moin Rahman is a Principal Scientist at HVHF Sciences, LLC. 

He specializes in:

"Designing systems and solutions for human interactions when stakes are high, moments are fleeting and actions are critical."

http://hvhfsciences.com/

http://www.linkedin.com/in/moinrahman 

E-mail: moin.rahman@hvhfsciences.com

Preventing Tragedies in Wildland Fire Fighting

We mourn the loss of 19 of the very best and brave wildland fire fighters, the Granite Mountain Hotshots*, at Yarnell Hill (Prescott), Arizona. As painful as this loss was, it behooves us, the scientific research community, to advance our understanding of fire science and fire fighter human factors to prevent such future tragedies. 

*Hotshots are an elite group of wildland firefighters, with a demanding regimen of physical and fire science training. They carry around 40 - 50 lbs. of gear, food, water, fire shelters, etc., and are dropped-off as a small group, where they fight the fire on their own. For example, they create a fire line, by starving the fire of its fuel (getting rid of brush, dry chaparral, brittle oak brush etc.) to keep the fire from spreading. They have a lookout who observes the wind patterns, weather, progression of fire, etc., on the fireground in real time, to help the firefighters develop their strategy and tactics -- and keep them safe. (A video of the Granite Mountain Hotshots that was filmed in April 2012 is available below this article.)

Started by a lightning strike on Friday, the fire spread to 8,000 acres. (Via NY Times)

Given the nature of the events at Yarnell Hill -- a burnover where the wind radically shifted suddenly and the flames changed direction without warning engulfing the Granite Mountain Hotshots -- posing the following research questions and finding answers may close the gap in our current knowledge on wildland firefighting. Thus enhancing risk assessment, situation awareness and decision making of firefighters and their commanders, supplemented with advances in communication, sensing and computing technologies that truly deliver utility, usability and safety to the crew on the fireground.

• Computational modeling of fire fighting by treating it as a physical & socio-technical complex systems. This complex system will consist of various heterogeneous agents (physical and human) -- fuel source (for the fire), heat intensity, oxygen levels, wind patterns and fire fighters' characteristics (knowledge, skills, abilities, training, physical fitness, cognitive readiness, experience -- i.e., capabilities & limitations). Furthermore, the human / organizational (socio-technical) element will encompass operational strategies and tactics (protocols), equipment and machines.  Thus these various agents produce their own signals and interact with other agents at the boundaries (a.k.a., signal-boundaries of a "dynamic generated systems" in complexity and chaos theory). This modeling may enable the commander and his/her crew to predict in near real time the behavior of the fire and effort/resources needed to starve it off fuel and oxygen to bring it under control; advise received, as needed from a central command center, who develop a macro level situation awareness with computational model providing proactive decision support;

The above picture from AZCentral.com

• Advance research in fire fighter (human) sensemaking, situation awareness and naturalistic decision making of complex scenarios in volatile, high stakes and complex settings to understand the fidelity and validity of situation assessment. Understand how firefighters / commander makes a decision on how to engage or disengage from a fire and how do they perceive risks (loss / gain) and probabilities to inform their decision making in real time.

Note the communication gear, the 2-way radio in front -- and inside the radio pocket -- of the harness on the Fire Jacket. 

(Communication and Computing technology is discussed in the next bullet point)

"Rick Cowell, the 55-year-old superintendent of the Tahoe Hotshots, addressing his crew during the Stafford blaze." *Photographer:* Kyle Dickman  via Outside Magazine

• Signal and imaging technologies (aerial and geospatial sensing and analysis), including command and control (radio communications and computing), that best integrate human and systems to enhance safety. The design of radio communications between the "lookout" and the "hotshots" on the fire ground -- as well as group communications between centralized command & control, lookout and hotshots (shared situation awareness) -- are vital to enhance situation awareness. In other words, comprehend the current conditions, particularly risks and hazards arising due to the fuel source and wind/weather patterns; and, more importantly, project the future trajectory and progression of the fire. Furthermore, the utility and use of large screen, data / computing devices on the fireground for use by the lookout or the hotshot squad leader, where data is fed from ground / aerial sensors (e.g., dropsondes) and video/images from central servers, should be investigated. Even though, this technology may provide valuable thermal and weather intelligence, it also poses the danger of cognitive / attentional tunneling and information overload causing the firefighters to loose situation awareness of dangers in the immediate physical  vicinity.

Thus it is vital to formulate the right research questions, find answers in terms of training and technologies, to prevent future tragedies resulting from volatile, uncertain, complex and ambiguous factors, time stress -- that are inherent to wild land fire fighting.

Video: Granite Mountain Hotshots

 

This video of the Granite Mountain Hotshots was filmed in April 2012. Chillingly, it shows the crew practicing the deployment of their fire shelters (aluminum foil and silica sacks that reflect radiant heat). Prior to this tragic and wicked conflagration the Prescott Fire Department -Granite Mountain Interagency Hotshot Crew had never before been forced to deploy shelters in a fire. The LAST RESORT... Fire shelters have saved the lives of nearly 300 firefighters since 1977. Story credit: Stand with Arizona standwitharizona.com 

Thanks to -- and via -- Brotherhood of Fire 

News Articles

NPR: "19 Firefighters Killed In Ariz. Wildfire Called Deadliest In Decade"

PBS Newshour Video Report:  
Part 1: Ariz. Inferno Kills Elite Firefighters

Part 2: Firefighters Who Perished in Arizona Faced High Heat, 'One of the Hardest' Tasks

AZ Central: Wildfire experts: More than 1 factor spawned Yarnell tragedy

Further Reading:
Outside Magazine, on being a Hotshot: IN THE LINE OF WILDFIRE 

About the author:

Moin Rahman is a Principal Scientist at HVHF Sciences, LLC. He specializes in:

"Designing systems and solutions for human interactions when stakes are high, moments are fleeting and actions are critical."

http://hvhfsciences.com/

http://www.linkedin.com/in/moinrahman 

E-mail: moin.rahman@hvhfsciences.com

Designing In-Car, Driver-Vehicle Voice Activated Technologies

A recent study (1a,b) has rekindled an old debate regarding the true utility and safety of driver interaction with on-board, hands-free -- but voice-based interactive -- technology in a car (e.g., technologies such as a hands-free cellphone or other voice activated apps pertaining to in-vehicle Internet browsing/texting/e-mail, infotainement, GPS, etc.). Remember multitasking is not necessarily natural for a human (driver) due to competing demands, two or more concurrent tasks place on one's perceptual, cognitive and motor resources. Not all concurrent tasks are similar to walking and chewing gum. In some cases, a single task, all by itself -- for example, driving in heavy traffic and simultaneously trying to locate a street intersection in a new town -- is not easy. (The concurrent demands affects many multitasking 'tasks,' but not all. There are exceptions, where it may not have significant affects; cf. Wickens' multiple resource theory.)

When it comes to driving, the old saw "eyes-on-the-road, hands-on-the-wheel" will suffice to promote safe driving has been questioned over the last decade by both driving simulator and naturalistic driving (real time, on real roads) studies.  

The most recent study from the AAA Foundation for Traffic Safety (1), argues (supported with empirical results) that "Mind-on-the-Road" (having NO other external or in-vehicle 'cognitive distraction'; e.g., rubber necking caused by an emotionally arousing stimuli on the road such as a gruesome accident or talking on a hands-free cellphone, respectively) is equally important for safe driving. However, human factors studies have produced conflicting results as to the extent and amount of risk caused by such cognitive distraction (e.g., see 2).

 "A study released by AAA compared the impact on drivers of different activities, including listening to a book on tape or the radio, and talking on a phone."  Via New York Times (1)

Nevertheless, the true design question that needs to be asked his, how does one design voice based interaction technologies in a car to mitigate cognitive distractions? It has been known for some time, that on-board human-human communication (e.g., driver talking with co-passenger on the front seat) doesn't cause as much cognitive distraction. Because the passenger is cognizant of the traffic conditions (shared situation awareness; a.k.a., "mutual knowledge"* in the field of linguistic-pragmatics) -- and, thus, the driver's workload -- and may choose to pause or stop talking all together in heavy traffic conditions; likewise, the driver too may modulate his behavior by becoming silent because he knows that the passenger knows his mind is busy -- and, thus, may tolerate the period of driver going incommunicado.

*Mutual Knowledge: I (the driver) know that you (my co-passenger) knows that my mind is totally occupied due to the navigation demands placed by heavy traffic on the road; and you know that I know that you have stopped talking to me so as to not bother me; and I know that you know I won't anyway listen to you because my mind (and attention) are completely consumed due to the heavy cognitive load imposed by driving through heavy traffic. 

Thus, in an era of AI and Machine Learning  would it not be possible to design on-board technology that perceives, acts and behaves like a fellow passenger who is cognizant of the driver's workload? In other words, a machine that practices a form of analytics and AI, where it predicts and intuits human / driver capabilities and limitations, based on his workload on the primary task (driving) moment by moment in real time -- and adapts its behavior (via the voice or graphical/physical human interface) accordingly.Thus making itself (pseudo) hyper-intuitive to the driver, resulting in an illusion as though it is reading his mind! We may even refer to this intelligent machine behavior as being facilitated via an Inverted Hyper-Intuitive User Interface. 

A voice-activated technology (machine) endowed with "mutual knowledge" and shared situation awareness -- adapting itself and, thus, enhancing its usability via its Inverted Hyper-Intuitive User-Interface -- can go a long way in promoting safe driving outcomes.  Finally, the utilization and design of voice-activated technology should be carefully considered for police, emergency response and military vehicles, given the HighVelocityHumanFactors "HVHF" issues (high stakes, volatile, danger, stress-induced cognitive depletion) they encounter during their mission.

REFERENCES 

(from the press):

1(a) NPR: Hands-Free Gadgets Don't Mean Risk-Free Driving

1(b) New York Time: Voice-Activated Technology Is Called Safety Risk for Drivers

(2) VTTI has produced several studies showing that talking on a cell phone while driving does not increase risk." 

Moin Rahman

Founder/Principal Scientist

HVHF Sciences, LLC

"Designing systems and solutions for human interactions when stakes are high, moments are fleeting and actions are critical."

http://hvhfsciences.com/

http://www.linkedin.com/in/moinrahman 

Incisive Cognitive Analysis: Solving the Crime at Mile 26 of the Boston Marathon

It will be a long arduous recovery for victims, the kith and kin of those lost and injured in the heinous attack on civilians at Mile 26 of the Boston Marathon. Although, the people directly affected by this dastardly act will be scarred forever, human resilience is such they will recover in the fullness of time. Needless to say, the perpetrators will be found and justice will be served. It is just a matter of time.

Police officers reacted to a second explosion near the finish line (via New York Times)

Incisive Cognitive Analysis

The rest of this post is to look at how this crime is being -- and will be -- solved by professionals in the FBI, law enforcement, and intelligence analysts. And how this effort will be aided by cognitive machine agents supplemented by the following:
SIGINT (Signal Intelligence; telecommunication chatter)
GEOINT (Geospatial Intelligence; satellite, photography, video, etc.)
MASINT (Measurement & Signal Intelligence; spectral analysis of bomb materials)
CYBINT (Cyber Intelligence; web chatter), and, of course,
HUMINT (Human Intelligence)

The (human and machine) "cognitive agents," in the intel domain, are chartered with the goal of transforming raw data into information into knowledge. The challenge here is not the paucity of data, but in fact too much data. Some data would be relevant providing diagnostic cues (e.g., bomb materials), and most of other types of data ranging from imagery (video footage) to social data (cyber, tips, leads, innuendos and conspiracies) maybe irrelevant. The lesser mortal would be overwhelmed, but it is unlikely to faze the professional criminologist and intel analyst who would expertly sift through the data until he homes-in on his quarry.

But how does s/he do it?

Inference Engines: Human & Machine

Intelligence analysis involves analytical activity with a deep reserve of critical thinking.  It involves defining goals, formulating hypotheses, gathering information, sense-making, harnessing human imagination, reading the adversary's mind, leveraging expertise -- and yet being dispassionate and unbiased throughout the process.

The intelligence analyst, just like a physician or an automotive mechanic, is a diagnostician.  But there are subtle differences. The latter (physician or a mechanic) diagnose problems that fall under the rubric of "deterministic causation"; because the cause and effect chain are enmeshed in physical systems such as, "hydraulic circuits," for example; which either carry blood or oil and could be contaminated by pathogens or detritus, respectively.  Whereas the intelligence analyst wrestles most often with problems in the "indeterministic causation" genre because it is a smart, thinking and reasoning human agent like himself is the root cause.  The problem space does not have a set piece architecture or consistently obeys laws of societal rules or reveals explicit causal chains.  Furthermore, the indeterminate nature is undergirded by the perpetrator's need to utilize guile, deceit, bluff and bluster as a means to his end of inflicting harm. Thus the problem is harder for the intelligence analyst as he has to "read" the (intelligent) mind of the perpetrator.

The problem of intelligence analysis is made both easier and difficult at once by machine agents and technological decision aids. It is compounded in our era of Big Data, given the volume, velocity and variability with which data flows causing an acute mismatch between the cognitive capacities of machine and human agents.

A machine agent is far-superior in trying to sift through these massive data sets consisting of phone calls, video feeds (facial analysis), web chatter, social media and the like. It might even be programmed to suggest plausible hypotheses, with an inference engine or Bayesian network model, by connecting the dots between people, events and objects.

A machine agent's cognitive abilities may be constrained. For instance, it may not be savvy about the importance of certain days (e.g., Patriot Day, Tax Day, Anniversaries, etc.), seasonal patterns, local moods, linguistic colloquialisms, etc. It maybe oblivious to novel patterns that fall outside the ambit of its algorithms.  A human agent is aware of such things but falls short in terms of the machine's appetite for almost limitless, brute computing.  Thus a well designed joint cognitive system, which brings these agents together in a symbiotic and synergistic partnership enhances analytical ability (machine) and intuitive acuity (human).

Implicit vs. Explicit Information

Naive observers, meaning us the public, are attracted to information that is explicit to the incident. The pain, the blood, the color of the smoke, the pandemonium -- and the information that gets played over and over again on TV. We anchor to that information, and, furthermore, they are made worse by our prejudices, fears, (in)group think, etc. An intel analyst must be indifferent to those elements (innate traits and externalities) to succeed. He may have to infer information that is NOT explicit, perhaps information that is unavailable, seek it with the aid of the machine agent, by exercising inductive logic; for example, query the machine to sift through massive linguistic data sets, which connects certain signal words such as "Boston" or "Marathon."  Or employ deductive logic by making inexplicit information, explicit, by forensic analysis, of say, the bomb material.

A human agent, with his expertise, intuition and social knowledge may provide the kind of insights the machine may lack. But the machine agent will more than make-up by sifting, analyzing and deducing to discover nuggets of knowledge from Terabytes of data that is beyond human abilities.

Solving a problem, whether it be in a criminal or clinical context requires a cold calculus (aka, cold cognition, rational thinking and analysis). But at the same time it should leverage "hot cognition" (emotionally charge cognition) vicariously to think like the adversary and glean his or her motivation and modus operandi to attack a target. And reverse engineer the chain, from effect-to-cause-to- (locating the) perpetrator.

The tools from criminology, forensic science and cognitive engineering are in place to apprehend the perpetrators who placed their bombs at Mile 26 of the Boston Marathon. We have a cadre of seasoned professionals at work on the problem.

Regardless of who the perpetrators are, be they domestic or foreign agents, local or transnational terrorists, a lone wolf or an intolerant hate group they will be brought to justice. It is just a matter of time.

Moin Rahman

Founder/Principal Scientist

HVHF Sciences, LLC

"Designing systems and solutions for human interactions when stakes are high, moments are fleeting and actions are critical."

http://hvhfsciences.com/

http://www.linkedin.com/in/moinrahman