Situation Awareness Requirements Research Articles

To ensure the safety of storage: Enhancing accuracy of fire detection in warehouses with deep learning models

Warehouses are important places with storage functions in process units, containing many flammable and explosive materials. Nevertheless, fire protection systems often fail to provide adequate information when fires break out, hindering firefighting and leading to catastrophic outcomes. This research aims to develop a deep learning (DL) model capable of precisely locating the fire source and estimating its intensity, providing graphical representations of fire information. We propose a novel Multi-head Attention-based Long Short Term Memory (MHA-LSTM) model and apply Computational Fluid Dynamics (CFD) to generate datasets for model training on warehouse environments. The results demonstrate losses on the validation set and test set are less than 0.003, and all errors are below 0.15, indicating that MHA-LSTM has good generalization ability for fires in various locations. Compared to 3 common DL models, such as LSTM, the loss of MHA-LSTM on the test set is reduced by at least 51.6 %, greatly improves the accuracy of fire detection in complex scenarios. Finally, based on firefighters' situational awareness (SA) requirements, graphical examples of estimated fire information are generated to provide accurate and visualized fire data. This study utilizes artificial intelligence (AI) to overcome the limitations of complex internal structures in warehouses, offering a feasible approach to improve process safety and the accuracy of fire protection systems.

Supporting human supervision in autonomous collision avoidance through agent transparency

Ongoing trends in society point towards the adoption of intelligent agents across safety critical industries. In the maritime domain, artificially intelligent agents may soon be capable of autonomously performing collision and grounding avoidance (CAGA); a task traditionally performed by humans. Consequently, the role of humans is anticipated to change from those performing collision avoidance to those supervising an agent performing collision avoidance. One of the key concerns with regards to human factors is avoiding the out-of-the-loop performance problem where humans lose situation awareness (SA) and become susceptible to misinterpreting the agent’s decisions and planned actions. Despite previous research addressing human factors in autonomous shipping and remote control, few studies have focused on how to support the humans’ mental processes in this new role. Therefore, this study performed a goal-directed task analysis addressing goals, decisions, and SA requirements for human-supervised collision avoidance. Data was obtained from in situ observations and interviews with nine navigators onboard passenger ferries, an appraisal of the collision regulations, and of relevant company documentation. The task analysis identified specific SA requirements to make agents, capable of collision and grounding avoidance, transparent to their users. The results further indicate a change towards increased cognitive activities required to verify agent performance. Therefore, providing insight into the agents’ internal reasoning and actions becomes a key consideration in supporting future supervisors. Given the trends towards the application of artificially intelligent agents capable of autonomous behaviour, this study anticipates that transparency becomes an essential prerequisite for safe and effective human-autonomy system oversight.

Identifying firefighters' situation awareness requirements for fire and non-fire emergencies using a goal-directed task analysis

A firefighter's situation awareness (SA) is considered crucial to making effective tactical decisions and actions at the scene. Despite the importance of the firefighter's SA, there have been limited research efforts to understand what cues and information firefighters use to assess ongoing situations and predict future conditions. In addition to fire events, contemporary firefighters respond to an increasing volume of non-fire incidents. Thus, this study aims to identify firefighters' SA during three fire incidents (single house fire, vehicle fire, and passenger aircraft fire) and three non-fire incidents (medical emergency, hazardous materials, and urban search and rescue). A goal-directed task analysis was conducted via focus group discussions with eight career firefighters. Findings indicate that firefighters build their SA by processing various cues from hazards (e.g., fire, ignition source), humans (e.g., occupants, bystanders, drivers, passengers), spatial elements (e.g., building structure, location of hazards), and surrounding conditions (e.g., traffic, weather). Our findings provide insights into SA measurement, SA-oriented work processes, training for SA, and designing technologies to support firefighters' SA during all-hazard responses.

Modern Firefighters’ Three-Level Situation Awareness in Fire and Non-Fire Incidents

This study aimed to identify professional firefighters’ situation awareness (SA) requirements for six high-risk emergencies: i) a single-house fire, ii) an unconscious person as a medical emergency scenario, iii) a vehicle fire, iv) a gas leak incident as a hazardous material (HazMat) case, v) a passenger aircraft fire, vi) and a search and rescue operation for a collapsed building. A Goal-Directed Task Analysis (GDTA) was employed to elicit major goals, sub-goals, decisions, and three-level SA information requirements for firefighters in six different types of an incident. Findings indicate that firefighters have common goals of ensuring life safety and incident stabilization. Sub-goals were concerned with the safety of residents as well as responders’ safety. Incident stabilization meant extinguishing fire for fire events and providing medical treatment in case of a medical emergency. To build SA for different situations, firefighters indicated that they use characteristics of fire and smoke, the location and condition of residents, a person’s appearance and behavior, and building structure. These findings can inform the design of work processes and emergency response technologies for fire and non-fire operations.

Distribution Network Security Situation Awareness Method Based on the Distribution Network Topology Layered Model

Distribution network security situation awareness refers to the process of perception, understanding, and state projection of systems, elements, and environmental factors within a certain space-time volume. Security situation awareness is an important part of the security assessment of the distribution network. In response to the rapid and accurate distribution network security situation awareness requirements, this paper proposes a distribution network security situation awareness method based the distribution network topology layered model. First, a hierarchical model of the distribution network topology under the premise of optimizing the location of the synchronous phasor measuring device is constructed. This model can quickly capture the system security situation elements. Then, a support vector data description algorithm fused with information entropy is used to realize the identification and understanding of abnormal information in the security situation elements of the distribution network. The long- and short-term memory network is then used to predict the operation trend of the distribution network under normal operation and fault disturbance. Finally, a simulation is established, and the IEEE-33 distribution network model is used to verify the effectiveness of the method proposed in this paper. The results show that the method of this paper improves the speed and accuracy of obtaining the security situation elements of the distribution network, shortens the identification time of the security situation elements, and realizes the security situation awareness of the nodes of the distribution network.

Situation Awareness-Oriented Dashboard in ICUs in Support of Resource Management in Time of Pandemics.

In a pediatric intensive care unit (PICU) of 32 beds, clinicians manage resources 24 hours a day, 7 days a week, from a large-screen dashboard implemented in 2017. This resource management dashboard efficiently replaces the handwriting information displayed on a whiteboard, offering a synthetic view of the bed's layout and specific information on staff and equipment at bedside. However, in 2020 when COVID-19 hit, the resource management dashboard showed several limitations. Mainly, its visualization offered to the clinicians limited situation awareness (SA) to perceive, understand and predict the impacts on resource management and decision-making of an unusual flow of patients affected by the most severe form of coronavirus. To identify the SA requirements during a pandemic, we conducted goal-oriented interviews with 11 clinicians working in ICUs. The result is the design of an SA-oriented dashboard with 22 key indicators (KIs): 1 on the admission capacity, 15 at bedside and 6 displayed as statistics in the central area. We conducted a usability evaluation of the SA-oriented dashboard compared to the resource management dashboard with 6 clinicians. The results showed five usability improvements of the SA-oriented dashboard and five limitations. Our work contributes to new knowledge on the clinicians' SA requirements to support resource management and decision-making in ICUs in times of pandemics.

Supporting Human-AI Teams:Transparency, explainability, and situation awareness

System autonomy and AI are being developed for a wide variety of applications where they will likely work in tandem with people, forming human-AI teams (HAT). Situation awareness (SA) of autonomous systems and AI has been established as critical for effective interaction and oversight of these systems. As AI capabilities grow, and more effective teaming behaviors are expected of AI systems, there will also be an increased need for shared SA between the human and AI teammates. Methods for supporting team SA within HAT are discussed in terms of team SA requirements, team SA mechanisms, team SA displays and team SA processes. A framework for understanding the types of information that needs to be shared within HAT is provided, including a focus on taskwork SA, agent SA, and teamwork SA. AI based on learning systems creates new challenges for the development of good SA and mental models. AI transparency and explainability are discussed in terms of their separate roles for supporting SA and mental models in HAT. The SA Oriented Design (SAOD) process is described as a systematic methodology for developing transparent AI displays for HAT and an example of its application to automated driving in a Tesla is provided.

PrioDeX

Real-time event detection and targeted decision making for emerging mission-critical applications require systems that extract and process relevant data from IoT sources in smart spaces. Oftentimes, this data is heterogeneous in size, relevance, and urgency, which creates a challenge when considering that different groups of stakeholders (e.g., first responders, medical staff, government officials, etc.) require such data to be delivered in a reliable and timely manner. Furthermore, in mission-critical settings, networks can become constrained due to lossy channels and failed components, which ultimately add to the complexity of the problem. In this article, we propose PrioDeX, a cross-layer middleware system that enables timely and reliable delivery of mission-critical data from IoT sources to relevant consumers through the prioritization of messages. It integrates parameters at the application, network, and middleware layers into a data exchange service that accurately estimates end-to-end performance metrics through a queueing analytical model. PrioDeX proposes novel algorithms that utilize the results of this analysis to tune data exchange configurations (event priorities and dropping policies), which is necessary for satisfying situational awareness requirements and resource constraints. PrioDeX leverages Software-Defined Networking (SDN) methodologies to enforce these configurations in the IoT network infrastructure. We evaluate our approach using both simulated and prototype-based experiments in a smart building fire response scenario. Our application-aware prioritization algorithm improves the value of exchanged information by 36% when compared with no prioritization; the addition of our network-aware drop rate policies improves this performance by 42% over priorities only and by 94% over no prioritization.

Context enabled decision aids to support the situation awareness and performance of risk engineers carrying out loss prevention surveys

Routine inspection by insurance companies at their clients’ facility, also known as loss prevention survey, help identify the best strategies to minimize damages when there is a high-speed wind event. More specifically, wind vulnerabilities associated with a building are evaluated using a process known as windstorm risk inspection. This routine inspection helps clients reduce the extent of damages caused by high-speed wind events including hurricane and tornado. Risk engineers make use of their subjective and analytical deduction skills to successfully carry out the inspection tasks. In this research the researchers investigated the effect of context-based visualization strategies on situation awareness and their understanding of the situation. The study examined how different types of information contribute towards the three levels of situation awareness. Following a between-subjects study design, 65 participants completed the study. Each session lasted 90–120 min. A checklist based and predictive display-based decision aids were tested and found to be effective in supporting the situation awareness requirements as well as performance of risk engineers. However, the predictive display only helped with certain tasks such as understanding the interaction among different components on the rooftop. For remaining tasks such as perceiving obvious issues like membrane tear, clogged drains and vegetation growth, checklist alone was sufficient. This study helped the understanding of the advantages and disadvantages of the decision aids tested. More specifically, these decision aids can improve the mental model of novice risk engineers. Additionally, this study provided insights that could help design training materials for infrastructure inspectors.

Social Media Data in an Augmented Reality System for Situation Awareness Support in Emergency Control Rooms

During crisis situations, emergency operators require fast information access to achieve situation awareness and make the best possible decisions. Augmented reality could be used to visualize the wealth of user-generated content available on social media and enable context-adaptive functions for emergency operators. Although emergency operators agree that social media analytics will be important for their future work, it poses a challenge to filter and visualize large amounts of social media data. We conducted a goal-directed task analysis to identify the situation awareness requirements of emergency operators. By collecting tweets during two storms in Germany we evaluated the usefulness of Twitter data for achieving situation awareness and conducted interviews with emergency operators to derive filter strategies for social media data. We synthesized the results by discussing how the unique interface of augmented reality can be used to integrate social media data into emergency control rooms for situation awareness support.

Adaptation and Validation of the Situation Awareness Global Assessment Technique for Nurse Anesthesia Graduate Students

BackgroundEndsley's Situation Awareness Global Assessment Technique (SAGAT) is accepted as a valid and reliable situation awareness (SA) measurement tool in event-driven domains, including health care specialties. This study validated an adapted SAGAT to quantify anesthesia providers' SA in a simulation. MethodUsing exploratory sequential mixed methods, SAGAT items were adapted and validated using qualitative techniques and further validated by quantitative approaches. The study used 2 samples of CRNA, nurse anesthesia educators. ResultsContent analysis of identified and validated SA requirements elicited SAGAT items, with the final item list demonstrating I-CVIs of 0.83 to 1.0 and S-CVI/Ave of 0.92. Conclusion(s)An anesthesia providers' competence is directly related to clinical decision making and thus SA, necessitating the importance of its measurement.

Attention allocation in pilots based on climbing and circling mission behavior.

Exploration of changes in eye movement at different flight conditions can enrich scholarly understanding of situation awareness (SA) and inform new scanning behavior training techniques for efficient and effective pilot education. The SA requirements for pilots vary from mission to mission. Eye tracking is often used to analyze various attention allocation and SA acquisition processes at work in different missions. Pilot eye movements were measured during a climbing task and circling task using a cockpit-based simulator. Results of situation awareness rating technique (SART) tests show that there are significant differences between attention processes during climbing versus circling flight tasks. Fixation frequency during climbing is lower than in the circling task. Additionally, saccade frequency and average fixation time in the climbing task are markedly higher than those in the circling task. Wilcoxon test results show that the pilot has a higher fixation count and fixation time during the circling phase in out-view (OV) areas of interest (AOI) than during the climbing phase. Notably, the attention probability is higher in climbing task than in circling task when the current area of fixation (AOF) is in the head-up display (HUD) AOI and the next fixation area is in the instrumentation panel left (IPL); when the current AOF is in the out-view right (OVR) and the next AOF is HUD, the attention probability is higher in climbing task than in circling task; when the current fixation is in the IPL and the next fixation probability is to the out-view left (OVL), the attention probability is higher in task climbing task than in circling task. In terms of the Markov stationary distribution, the Wilcoxon test shows that, when IPL AOI is the area of the maximum probability of fixation in both tasks, the attention probability of HUD AOI and instrumentation panel right (IPR) is higher in climbing task than in circling task. Circling tasks require efficient eye movement patterns accompanied by strict attention distribution, which yields high SA level and flight performance when performed properly. This paper summarizes the attention characteristics at different flight phases and various requirements of different tasks according to pilot eye movement tracking results. Similar activities, as routine training, can enhance the efficiency of a novice pilot's attention distribution.

Context-Based Visual Aids to Support the Situation Awareness of Field Engineers Conducting Windstorm Risk Surveys

Insurance loss prevention survey, specifically windstorm risk inspection survey is the process of investigating potential damages associated with a building or structure in the event of an extreme weather condition such as a hurricane or tornado. This process is performed by a trained windstorm risk engineer who physically goes to a facility to assess the wind vulnerabilities associated with it. This process is highly subjective, and the accuracy of findings depends on the experience and skillsets of the engineer. Although using sensors and automation enabled systems help engineers gather data, their ability to make sense of this information is vital. Further, their Situation Awareness (SA) can be affected by the use of such systems. Using a between-subjects experimental design, this study explored the use of various context-based visualization strategies to support the SA requirements and performance of windstorm risk engineers. The independent variable included in this study is the type of context-based visualizations used (with 3 levels: no visual aids, checklist based and predictive display based visual aids). We measured SA using SAGAT and performance using a questionnaire. SA and performance were found to be higher for the predictive display and checklist based conditions. The findings from this study will inform the design of context-based decision aids to support the SA of risk engineers.

Thinking Ahead of the Tractor: Driver Safety and Situation Awareness

ABSTRACTObjective: Situation awareness has been identified as a key skill in maintaining safety in high-risk, dynamic industries. However, there is a lack of research evaluating situation awareness requirements and error types in agricultural operators. The aim of this study was to explore situation awareness among farmers in the United Kingdom (UK) when operating heavy agricultural machinery.Method: The study used an online qualitative survey to collect data in three main areas: situation awareness requirements, factors impacting situation awareness, and the safety context for UK farmers. A total of 57 farmers completed the survey, responding to seven open-ended questions. Data were analyzed using directed content analysis.Results: The results indicate the importance of situation awareness for safe and efficient work practice in farming. Situation awareness requirements span the machinery system, including awareness of internal cab systems and the status of implements attached to the external machine. Farmers needed to map and monitor the surrounding conditions in addition to considering personal requirements. Data also indicated the impact of a range of factors, including system-based elements such as blind spots, individual factors such as level of fatigue, and issues related to a lack of knowledge and failure to think ahead on the maintenance of situation awareness.Conclusion: This research highlights the situation awareness requirements for operating agricultural machinery in complex and dynamic environments. By taking a human factors approach, utilizing design and practical interventions, it may be possible to both support and enhance farmer situation awareness and, therefore, reduce errors and adverse incidents.

Design of Future UAV-Relay Tactical Data Link for Reliable UAV Control and Situational Awareness

Unmanned aerial vehicles (UAVs) have recently been widely used in the military and commercial domains. UAVs, especially in the military domain, were initially used for gathering intelligence, surveillance, and reconnaissance data, and sending them to a command center. Their use was then expanded to the tactical level to perform military operations with manned platforms. Operating a UAV as a relay node in the air has many advantages, including coverage, recovery from disconnection from a relay, clear communication channel, and easy deployment. Thus, the UAV-Relay tactical network can support more effective military operations. However, reliable UAV control and situational awareness must be guaranteed for the use of tactical UAVs. In other words, all tactical nodes must be able to send their location and status periodically under the dynamic and unexpected situation of a battlefield. However, a jamming attack from the enemy can make UAV control and situational awareness impossible. Thus, we need a robust tactical data link (TDL) to guarantee reliable UAV control and situational awareness under a jamming attack. In this article, we first explain the requirements for reliable UAV control and situational awareness. We then design a future UAV-relay TDL, called link-situational awareness and control (Link-SAC), which satisfies the requirements. We also deal with the spectrum allocation and management of Link-SAC because Link-SAC requires large bandwidth under the scarcity of spectrum resource. Thus, we consider spectrum sharing to allocate an X-Band uplink to Link-SAC. Based on the interference analysis in a prior study, we show that spectrum sharing is possible. We also show how Link-SAC can manage the spectrum. Lastly, we present our concluding remarks.

A taxonomy of autonomous vehicle handover situations

This paper provides a taxonomy of different forms of autonomous vehicle handover situations. It covers scheduled, emergency and non-emergency handovers and it differentiates between system and driver initiated handovers. The purpose is to examine how the system and driver are responsible for different stages in the transition timeline, i.e., first alert, handover phase, and return to automated control (handback). This is examined from the perspective of SAE levels in comparison to aspects drawn from situational awareness. The work is complemented by analysis drawn from current practice within the insurance industry and interviews with insurers. The result is a closer examination of system and driver responsibility which is independent of but includes SAE levels with respect to specific handover situations. It also identifies gaps between the current legal liability for accidents when compared to aspects such as the situational awareness requirements placed on driver under different driving conditions.

Nationwide critical infrastructure monitoring using a common operating picture framework

This paper describes the efforts involved in designing a common operating picture system for monitoring large-scale critical infrastructures. The design leverages the Joint Directors of Laboratories (JDL) data fusion model to enable the integration of different critical infrastructure systems with their dependency relations. The resulting Situational Awareness of Critical Infrastructure and Networks (SACIN) framework offers a platform that provides a common operating picture of a critical infrastructure. A generic data collection component customized to each source system generates events and facilitates JDL level 0 integration. An analysis component collects events and data to produce meaningful information about the current state and future impact estimates in accordance with JDL levels 1 to 3. A brokered architecture supports level 4 control by various components and a JDL level 5 user interface is offered via a web application. Interviews of infrastructure subject matter experts were conducted to obtain the situational awareness requirements. By applying key situational awareness oriented design principles to the situational awareness requirements, a user interface was created for organizing information based on operator situational awareness needs and supporting key cognitive mechanisms that transform data into high levels of situational awareness. Situational awareness measures were used to assess operator performance during critical infrastructure tasks – a “freeze-probe” recall approach (Situational Awareness Global Assessment Technique (SAGAT)), a post-trial subjective rating approach (Situational Awareness Rating Technique (SART)) and the System Usability Scale (SUS). The results indicate that the supply of attentional resources (SART supply) and overall SAGAT score best predict the performance levels of operators.

Data Properties Underlying Human Monitoring Performance

The application of phasor measurement unit (PMU) data in the power industry is currently an area of intense interest. The key driver for PMU technology is to use the precise time sources provided by Global Positioning System (GPS) satellites to accurately measure the relative voltage and current phase angles at buses across an interconnect at a very high sampling rate. Presenting PMU data to power system operators in a format that is truly useful for them and that affords improved situation awareness (SA) and fast and accurate decision making is a particular challenge to display design. This paper described development of prototype displays of PMU data where the design criteria were derived from characteristics of the data as well as the situation awareness requirements of power system dispatchers. A prototype display that meets all these design criteria is described.

Roadmap for the Development of at-Home Telemonitoring Systems to Augment Occupational Therapy

While the literature supports the potential to provide occupational therapy through telemedicine, there are several design challenges embedded in creating an at-home telemonitoring system that can visualize the complex biomechanical data required for clinical decision making. The challenge highlighted here is the development of measures that align with current decision making methods, which will support the integration and translation of the technology. A modified cognitive task analysis methodology is presented that is composed of three segments: characterizing the subject matter, defining relevant information, and formalizing requirements. This method was implemented through observations of eight therapists over 21 patient sessions. There were nine unique modes of interaction observed between the clinician and patient. Embedded within these interactions were 14 different features monitored. Relevant performance measures were defined from these interactions to provide perception and comprehension situation awareness (SA) to the clinician about the patients task performance. Using specific activities observed during therapy sessions, sample metrics and a visualization are presented that followed from the SA requirements. Finally, the technological challenges associated with making these measurements were identified.

Enhancing information interaction as a means for situation awareness maintenance in mobile field work

Maintenance of situation awareness is of critical importance for the safe and productive execution of mobile field work. However, there is scarcity of research considering maintenance of situation awareness in mobile field work settings. The case study analyses information interaction as a means to maintain situation awareness. The empirical data for the study were collected from security service personnel participating in a pilot of guarding service based on NFC (near field communication) technology. NFC enables ubiquitous and location- and context-aware computing. Interviews, on-site observation and a questionnaire were conducted to define situation awareness requirements and to assess both current user experiences and future scenarios of NFC-based information support for security service work. Results of the study show that information interaction challenges were related to non-value-adding information activities when trying maintain situation awareness. Challenges were related to disturbances in information flow between clients, security service back office and field. It was found that maintaining situation awareness in circuit guarding was more challenging than in local guarding. Future NFC functionalities providing information support in particular for maintenance of short-term situation awareness were assessed as promising.