Situation Awareness Framework Research Articles

Supervisory Protection and Automated Event Diagnosis Using PMU Data

This paper presents a new framework for supervisory protection and situational awareness to enhance grid operations and protection using modern wide-area monitoring systems. In contrast to earlier approaches dealing with the combined processing of data from multiple phasor measurement units (PMUs), the proposed approach analyzes only the PMU data with the strongest or the most prominent disturbance signature. The specific contributions of this paper are: a) new criteria for identification of PMU with the strongest signature, b) simplified approach for quick detection of faults, c) early classification of eight other disturbances suitable for near real-time response, d) time-frequency transform-based feature extraction techniques for speedy and reliable classifiers, and e) a promising approach to locate disturbances within narrow geographical constraints. The contributions are verified with exhaustive simulation data from the Western Electricity Coordination Council system model and limited real PMU data.

Situation awareness: when nurses decide to admit or not admit a person with mental illness as an involuntary patient.

This paper will explore the application of situation awareness in nursing to determine its suitability as a framework to study how the decision to admit or not admit a person as an involuntary patient is made. The decision by a specially qualified nurse to admit or not admit a person to a mental health facility against their will remains a central component of contemporary mental health legislation. The decision has an impact on a person's autonomy and human rights. Conversely, the decision to admit may facilitate urgent assessment and treatment and ensure the safety of the individual and others. Research highlights that decision-making in this context is challenging due to the multiple information sources and often incomplete information available to the clinician. Situation awareness is a concept used to explain how practitioners identify, use and make meaning of a multitude of factors and elements relevant to their practice. Discussion paper. A search of terms related to situation awareness and mental health nursing was conducted in the period 2000 - present. Exploring nurses decision-making using a situation awareness framework provides for a more nuanced understanding of nurses knowledge and skill when deciding to admit or not a person as an involuntary patient. The concept of situation awareness provides a framework to better understand the decision-making process associated with the involuntary admission decision.

Representation of Network Security Situation Elements Based on Cloud Model

Aiming at efficiently aware the network security situation, we proposed a framework of Network Security Situation Awareness on the base of Cloud Model. With network security situation elements at the core, we modified the Cloud Model to a novel concept, situation cloud, which act as theoretical foundation in the transition between the qualitative and quantitative representation on situation elements. Finally, the experimental results showed that these two kind of representations can directly summarize the security condition of network as well as precisely recognize the changes of situation elements.

Situation Awareness Framework for Multi-Machine Environments: An Application to Operator Assistive Collision Warning System

Mobile multi-machine environments consist of varying types of objects, either static or dynamic with the state known exactly or with some uncertainty. Sensors observe the environment from different positions and views, such as horizontally from the top of a mobile machine or vertically downward from an external observing machine. In this paper, we propose a simple grid-based framework for representing the information of varying types of objects in a 2-D environment and Bayesian methods for updating this information through observations and prediction models. This information about the current and near-future state of the environment is called situation awareness (SA). SA information can be utilized as the basis of the operator assistance system for enhancing the safety and efficiency of manual and semiautonomous multi-machine work environments. SA information can also be utilized in task planning of autonomous machines, via creating a dynamic costmap for path planning or entropy map for planning the optimal use of sensory systems. This paper aims at real-time mobile multi-machine environments; hence, the SA framework is kept simple for computational feasibility, but is also general enough to be applicable in other environments as well. Discussion on discretization errors and computational complexity are also covered.

A Qualitative Analysis of NWS Forecasters’ Use of Phased-Array Radar Data during Severe Hail and Wind Events

Abstract The 2013 Phased Array Radar Innovative Sensing Experiment (PARISE) investigated the impacts of higher-temporal-resolution radar data on National Weather Service forecasters’ warning decision processes during severe hail and wind events. In total, 12 forecasters participated in the 2013 PARISE over a 6-week period during the summer of 2013. Participants were assigned to either a control [5-min phased-array radar (PAR) updates] or experimental (1-min PAR updates) group, and worked two cases in simulated real time. This paper focuses on the qualitative retrospective reports of participants’ warning decision processes that were collected using the recent case walk-through method. Timelines of participants’ warning decision process were created for both cases, which were then thematically coded according to a situational awareness framework. Coded themes included perception, comprehension, and projection. It was found that the experimental group perceived significantly more information during both cases than the control group (case 1 p = 0.045 and case 2 p = 0.041), which may have improved the quality of their comprehensions and projections. Analysis of timelines reveals that 1-min PAR updates were important to the experimental group’s more timely and accurate warning decisions. Not only did the 1-min PAR updates enable experimental participants to perceive precursor signatures earlier than control participants, but through monitoring trends in radar data, the experimental group was able to better detect storm motion, more accurately identify expected weather threats from severe thunderstorms, more easily observe strengthening and diminishing trends in storms, and make more correct tornado-related warning decisions.

Formal Specification of the Framework for NSSA

As the computer network has evolved to provide the user many services, the attacks on these networks to disrupt the services and to gain access to resources has also evolved. New entities in form of services, hardware, network protocols etc. are being added to the network, which is leading to new ways to attack the network. The complexity of the system is increasing so fast that it is becoming increasingly difficult for network administrator to comprehend the situation and react in an appropriate manner. Situation becomes more complex as there is no uniform terminology. Though serious efforts in form of Common Vulnerability Enumeration (CVE), Common Weakness Enumeration (CWE), Common Attack Pattern Enumeration and Classification (CAPEC) etc. has been made, still a long way is to go. In this paper we have proposed a formal specification of the framework for network security situational awareness (NSSA) using ontological engineering approach. We have modeled a computer network by modeling its components i.e. hardware, software, services using ontology. Also vulnerabilities and attacks on these computers are modeled. We populate our ontology with various instances of vulnerabilities, CVSS scores, attacks and possible services in the network. Knowledge representation methods are used in order to provide Description Logic reasoning and inference over network security status concept. Secondly we propose an ontology based system which predicts probable attacks using inference and information provided by the environment.

IoT based situational awareness framework for real-time project management

Factories of the Future roadmap identifies that the major challenges manufacturing companies face today are the growing complexity of their processes, therefore affecting the overall process of decision making. Thus, it is a very important research area to integrate the evolving technologies in the domain of Internet of Things (IoT) into the applications used for project management. At the same time, to capture events on the shop-floor and determine the meaning of information about those perceived events would be an important aspect for making decisions in heterogeneous, highly dynamic environments. This research paper aims to provide a framework for efficient project management by reducing the time for decision-making based on IoT technologies. The goal is pursued by dynamically establishing situational awareness on the top of existing manufacturing processes. The proposed framework is validated in real industrial scenario by implementing a platform for efficient project management within the domain of construction industry.

Measuring the HIV Care Continuum Using Public Health Surveillance Data in the United States.

The HIV care continuum is a critical framework for situational awareness of the HIV epidemic; yet challenges to accurate enumeration of continuum components hamper continuum estimation in practice. We describe local surveillance-based estimation of the HIV continuum in the United States, reviewing common practices as recommended by the Centers for Disease Control and Prevention. Furthermore, we review some challenges and biases likely to threaten existing continuum estimates. Current estimates rely heavily on the use of CD4 cell count and HIV viral load laboratory results reported to surveillance programs as a proxy for receipt of HIV-related outpatient care. As such, continuum estimates are susceptible to bias because of incomplete laboratory reporting and imperfect sensitivity and specificity of laboratory tests as a proxy for routine HIV care. Migration of HIV-infected persons between jurisdictions also threatens the validity of continuum estimates. Data triangulation may improve but not fully alleviate biases.

Situation awareness errors in anesthesia and critical care in 200 cases of a critical incident reporting system.

BackgroundA loss of adequate Situation Awareness (SA) may play a major role in the genesis of critical incidents in anesthesia and critical care. This observational study aimed to determine the frequency of SA errors in cases of a critical incident reporting system (CIRS).MethodsTwo experts independently reviewed 200 cases from the German Anesthesia CIRS. For inclusion, reports had to be related to anesthesia or critical care for an individual patient and take place in an in-hospital setting. Based on the SA framework, the frequency of SA errors was determined. Representative cases were analyzed qualitatively to illustrate the role of SA for decision-making.ResultsSA errors were identified in 81.5 %. Predominantly, errors occurred on the levels of perception (38.0 %) and comprehension (31.5 %). Errors on the level of projection played a minor role (12.0 %). The qualitative analysis of selected cases illustrates the crucial role of SA for decision-making and performance.ConclusionsSA errors are very frequent in critical incidents reported in a CIRS. The SA taxonomy was suitable to provide mechanistic insights into the central role of SA for decision-making and thus, patient safety.

Situation awareness systems, states and processes: a holistic framework

This paper argues that state, system, and process descriptions of situation awareness (SA) are interdependent. Based on SA research from the last 30 years, the paper proposes a holistic SA framework. SA states emerge from processes of exploring situations through SA systems. Reflecting research on safety II (resilience), in describing SA states, the framework distinguishes frames (what situations are considered) from implications (regarding the situations) of objects on and of an event horizon. The paper describes and discusses SA system and process dependencies on SA states. It also describes SA system components as mediators and catalysts for SA, SA system properties (e.g. buffering SA), and dynamic SA system formation. Based on an analysis of four enactments of Air Traffic Control situations, the paper argues that what is domain-characteristic may not characterise all situations in a domain. The SA field could thus benefit from incrementally refining a nuanced cross-domain framework.

A multi-agent fuzzy consensus model in a Situation Awareness framework

In order to define systems enabling the automatic identification of occurring situations, numerous approaches employing intelligent software agents to analyse data coming from deployed sensors have been proposed. Thus, it is possible that more agents are committed to monitor the same phenomenon in the same environment. Redundancy of sensors and agents is needed, for instance, in real world applications in order to mitigate the risk of faults and threats. One of the possible side effects produced by redundancy is that agents, observing the same phenomenon, could provide discordant opinions. Indeed, solid mechanisms for reaching an agreement among these agents and produce a shared consensus on the same observations are needed. This paper proposes an approach to integrate a fuzzy-based consensus model into a Situation Awareness framework. The main idea is to consider intelligent agents as experts claiming their opinions (preferences) on a phenomenon of interest.

Mobile situation-aware framework for developing smart mobile software

Advances in mobile technology and significantly increasing utilization of mobile devices such as smartphones and tablets have resulted in a paradigm shift from PC-centric computing to mobile computing. The results of careful analysis conducted of this mobile landscape indicate that there is a growing demand for smart, user-centric, situation-aware mobile software. Invariably, concomitant with this demand is the need for methodologies that can provide support the development of this type of software. In this paper, we propose a semantic framework, called the mobile situation-aware framework, which supports efficient modeling, construction, processing, management, and inference of mobile situation information. The framework comprises two phases, situation modeling and situation construction, and can serve as a guide and a template in the development of situation-aware applications for the mobile environment. A case study in which mobile situation-aware framework is utilized in the development of a semantic media player verifies the efficacy of the proposed framework. Copyright © 2014 John Wiley & Sons, Ltd.

A tour of BeAware – A situation awareness framework for control centers

Large control centers, as needed in road traffic, typically manage highly dynamic environments. They process vast amounts of information from heterogeneous data sources about a large number of real-world objects, which are anchored in time and space. In such systems, human operators are vulnerable to information overload and, thus, may fail to be aware of the overall meaning of available information and its implications. With BeAware, we propose a software framework that supports the development of situation awareness applications for control centers. The contribution of this paper is twofold: First, we integrate existing ontologies with spatio-temporal reasoning concepts, focusing on extensibility. We introduce meta-modeling concepts that allow us to assess and project situations and actions using semantic web technology. Second, we compare the runtime performance of the situation comprehension capabilities of a generic, ontology-driven implementation and a domain-specific relational-database-backed implementation, and discuss the strengths and shortcomings of each approach.

A Knowledge-Based Analytics System via Online Monitoring of Dissolved Gas in Power Transformer – A Conceptual Framework

The monitoring of dissolved combustible gases in power transformer oil could enable early detection of disastrous fault. The conventional dissolved gases in oil monitoring activities have these characteristic: 1) periodically sampling and 2) manual interpretation of combustible gases. However, periodical sampling increases number of undetected fault due to long sampling interval and manual interpretation of dissolved gas is often too complex for system operator to digest, resulting in reduced reliability of the power system and lack of situational awareness. To enhance the condition based monitoring activities for power transformer; TNB Research is embarking on online monitoring and knowledge-based system research project to address both issues related to periodical sampling method. This paper outlines the conceptual framework of the research project which was recently approved. It includes (1) the system architecture of the online monitoring system, (2) brief explanation of the mechanism of photo-acoustic spectroscopy, (3) the engineering system situational awareness framework which integrates different levels of automation and (4) blocks of knowledge sources theory used in modeling the engineering system.

Cyber Security Situation Awareness Based on Data Mining

Situation awareness is a kind of the third generation of information security technology, which aims to provide the global security views of the cyberspace for administrators. A framework of cyber security situation awareness based on data mining is proposed in this paper. The framework can be viewed from two perspectives, one is data flow, which presents the abstracting of cyber data, and the other one is logic view, which presents the procedure of situation awareness. The frameworks core component is correlation state machine, which is an extension of state machine. The correlation state machine is a data structure of achieving situation awareness, which is created based on the technology of data mining. After being created, it can be used to assess and predict the threat situation to achieve cyber knowledge. We conclude with an example of how the framework can be applied to real world to provide cyber security situation for administrators.

Applying cognitive situation awareness to collision avoidance for harbour last-mile area safety

Maneuvering ships in harbour areas is recognized as one of the most complex activity to be carried out Le (An automatic control system for ship harbour maneuvers using decoupling control. In: IEEE International Conference on Robotics and Automation, 2001. Proceedings 2001 ICRA 2:2108–2113, 2001) as a consequence of all information needs related to safety maintenance during guidance and control activities. By taking advantage of existing results, in this work we argue how situation awareness could be a leading and valuable technology to support decision making activities in this application. In particular, we propose the usage of a decentralized, autonomous, agent-based cognitive situation awareness framework, yet successfully experimented for airport safety monitoring and specifically modified to be applied to the maritime domain. The proposed framework exploits sensor network acquired streamed data management activities, together with semantic technologies and uncertainty management methods. The resulting architecture is aimed at monitoring ongoing situations and forecasting potential collisions, identifying involved entities and relations in order to improve the ability of maneuvering operators in assessing the current situations and their possible evolutions. Results and performances will be verified at the Port of Salerno, in order to show that information supporting inferred situations comply with real needs of decision making activities to prevent collisions during daily operations.

Wireless Network Design for Transmission Line Monitoring in Smart Grid

In this paper, we develop a real-time situational awareness framework for the electrical transmission power grid using Wireless Sensor Network (WSN). While WSNs are capable of cost efficient monitoring over vast geographical areas, several technical challenges exist. The low power, low data rate devices cause bandwidth and latency bottlenecks. In this paper, our objective is to design a wireless network capable of real-time delivery of physical measurements for ideal preventive or corrective control action. For network design, we formulate an optimization problem with the objective of minimizing the installation and operational costs while satisfying the end-to-end latency and bandwidth constraints of the data flows. We study a hybrid hierarchical network architecture composed of a combination of wired, wireless and cellular technologies that can guarantee low cost real-time data monitoring. We formulate a placement problem to find the optimal location of cellular enabled transmission towers. Further, we present evaluation results of the optimization solution for diverse scenarios. Our formulation is generic and addresses real world scenarios with asymmetric sensor data generation, unreliable wireless link behavior, non-uniform cellular coverage, etc. Our analysis shows that a transmission line monitoring framework using WSN is indeed feasible using available technologies. Our results show that wireless link bandwidth can be a limiting factor for cost optimization.

Aware online interdependency modelling via evidence theory

Critical infrastructure interdependency models are typically used in a simulation-based perspective, in order to perform ‘what if?’ analyses and identify structural vulnerabilities in a dynamic perspective. While in the literature some attempts have been made to use interdependency models at real time, such approaches are flawed by the inability to properly determine the ongoing situation. Such models, typically, receive data from SCADA systems, which are mostly able to assess the effects of failures rather than the causes, while knowing the typology of failure would increase dramatically the predictive-ability of online interdependency models. In this paper, a situation awareness framework is provided with the aim to complement online interdependency models by providing more specific information on the causes of the outages highlighted by sensor data. In order to determine such causes, in this paper a transferable belief model representation is adopted to increase the awareness of interdependency models on fault causes. Moreover in this paper some of the limitations of evidence theory methods are highlighted and discussed, with particular reference to a real time context, providing some insights on how to overcome them, especially the closed-world assumption.

A situational awareness framework for securing the smart grid using monitoring sensors and threat models

Security, access control and risk mitigation in the smart grid are matters of great impact for this important sector of the critical infrastructure. Situational awareness requires a means of aggregating information and presenting that information in a manner conducive to assessing risk. While major components of the electric power grid were traditionally deployed in physically isolated networks, they are now utilising IP-based, open, interconnected networks to transmit and manage the supervisory control and data acquisition (SCADA) messages. Unfortunately, SCADA protocols used for communications and the systems that implement those protocols were not originally designed with security in mind. Therefore, in order to enhance security and detect potential malicious behaviour, smart grid operators need detailed and accurate information about the status, integrity, configuration and network topology of SCADA devices as well as information about any threats that may impact the grid. This paper describes a comprehensive framework that provides situational awareness (SA) for SCADA devices and their operations in a smart grid environment. Situational awareness is achieved by processing information collected by monitoring sensors and understanding threats that may affect operations. The proposed framework employs a threat modelling methodology to support this mission.

Exploring situational awareness in diagnostic errors in primary care

ObjectiveDiagnostic errors in primary care are harmful but poorly studied. To facilitate the understanding of diagnostic errors in real-world primary care settings that use electronic health records (EHRs), this study...