Situation awareness

About: Situation awareness is a research topic. Over the lifetime, 7380 publications have been published within this topic receiving 108695 citations. The topic is also known as: SA & situational awareness.

Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review

Abstract: Autonomous ships are expected to improve the level of safety and efficiency in future maritime navigation. Such vessels need perception for two purposes: to perform autonomous situational awareness and to monitor the integrity of the sensor system itself. In order to meet these needs, the perception system must fuse data from novel and traditional perception sensors using Artificial Intelligence (AI) techniques. This article overviews the recognized operational requirements that are imposed on regular and autonomous seafaring vessels, and then proceeds to consider suitable sensors and relevant AI techniques for an operational sensor system. The integration of four sensors families is considered: sensors for precise absolute positioning (Global Navigation Satellite System (GNSS) receivers and Inertial Measurement Unit (IMU)), visual sensors (monocular and stereo cameras), audio sensors (microphones), and sensors for remote-sensing (RADAR and LiDAR). Additionally, sources of auxiliary data, such as Automatic Identification System (AIS) and external data archives are discussed. The perception tasks are related to well-defined problems, such as situational abnormality detection, vessel classification, and localization, that are solvable using AI techniques. Machine learning methods, such as deep learning and Gaussian processes, are identified to be especially relevant for these problems. The different sensors and AI techniques are characterized keeping in view the operational requirements, and some example state-of-the-art options are compared based on accuracy, complexity, required resources, compatibility and adaptability to maritime environment, and especially towards practical realization of autonomous systems.

Emergency Situation Awareness: Twitter Case Studies

Abstract: The Emergency Situation Awareness (ESA) system provides all-hazard situation awareness information for emergency managers using content gathered from the public Twitter API. It collects, filters and analyses Tweets from specific regions of interest in near-real-time, enabling effective alerting for unexpected incidents and monitoring of emergency events with results accessible via an interactive website.

Situation awareness and co-operation within and between hierarchical units in dynamic decision making

Abstract: This paper is a follow-up of a field study of two military command teams and reports an experiment that tests three organizations (serial, parallel and optional) of co-operation and situation awareness within commander teams, as well as the communication between the commander team and the operative level. It was found that most groups in the optional condition performed worse than the groups in the other conditions. It was also found that members of teams in the parallel condition differed from members of teams in the serial condition in their situation awareness. The more successful commander team produced more planning in relation to hypothesis, as well as sending fewer messages in total between the units, than the less successful team.

ENHANCED SITUATIONAL AWARENESS AND TARGETING (eSAT) SYSTEM

Abstract: eSAT pushes 3D scene awareness and targeting to forward positioned mobile operators and their handheld devices in environments such as found in military theaters of operation, border control and enforcement, police operations, search & rescue and large commercial industrial operations. A host computer hosts a 3D model of a scene and dynamically captures and transmits a windowed portion of the visual representation of that 3D model over a wireless network to the mobile operators' handheld devices. The windowed portion of the visual representation is streamed directly to the operators' handheld device displays. The mobile operators may interact with and control the 3D model via the wireless network. The host computer may synthesize the visual representation of the 3D model with live feeds from one or more of the handheld devices or other assets to improve situational awareness. Either the mobile operators or host operator can make point selections on the visual representation to extract geo-coordinates from the 3D model as a set of target coordinates.

Visual Analytics on Mobile Devices for Emergency Response

Abstract: Using mobile devices for visualization provides a ubiquitous environment for accessing information and effective decision making. These visualizations are critical in satisfying the knowledge needs of operators in areas as diverse as education, business, law enforcement, protective services, medical services, scientific discovery, and homeland security. In this paper, we present an efficient and interactive mobile visual analytic system for increased situational awareness and decision making in emergency response and training situations. Our system provides visual analytics with locational scene data within a simple interface tailored to mobile device capabilities. In particular, we focus on processing and displaying sensor network data for first responders. To verify our system, we have used simulated data of The Station nightclub fire evacuation.