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Human factors related context is structured into three categories: information on the user (knowledge of habits, emotional state, biophysiological conditions), the user's social environment (co-location of others, social interaction, group dynamics), and the user's tasks (spontaneous activity, engaged tasks, general goals). Likewise, context related to physical environment is structured into three categories: location (absolute position, relative position, [[wikt:colocation|co-location]]), infrastructure (surrounding resources for computation, communication, task performance), and physical conditions (noise, light, pressure, air quality).<ref>[https://link.springer.com/article/10.1007%2Fs11042-010-0711-z?LI=true A Comprehensive Framework for Context-Aware Communication Systems. B. Chihani, E. Bertin, N. Crespi. 15th International Conference on Intelligence in Next Generation Networks (ICIN'11), Berlin, Germany, October 2011]</ref><ref>[https://ieeexplore.ieee.org/document/5956518 A Self-Organization Mechanism for a Cold Chain Monitoring System. C. Nicolas, M. Marot, M. Becker. 73rd Vehicular Technology Conference 2011 IEEE (VTC Spring), Yokohama, Japan May 2011]</ref>
Human factors related context is structured into three categories: information on the user (knowledge of habits, emotional state, biophysiological conditions), the user's social environment (co-location of others, social interaction, group dynamics), and the user's tasks (spontaneous activity, engaged tasks, general goals). Likewise, context related to physical environment is structured into three categories: location (absolute position, relative position, [[wikt:colocation|co-location]]), infrastructure (surrounding resources for computation, communication, task performance), and physical conditions (noise, light, pressure, air quality).<ref>[https://link.springer.com/article/10.1007%2Fs11042-010-0711-z?LI=true A Comprehensive Framework for Context-Aware Communication Systems. B. Chihani, E. Bertin, N. Crespi. 15th International Conference on Intelligence in Next Generation Networks (ICIN'11), Berlin, Germany, October 2011]</ref><ref>[https://ieeexplore.ieee.org/document/5956518 A Self-Organization Mechanism for a Cold Chain Monitoring System. C. Nicolas, M. Marot, M. Becker. 73rd Vehicular Technology Conference 2011 IEEE (VTC Spring), Yokohama, Japan May 2011]</ref>
情景相关的人类特征可以被分为3类:用户基本信息（习惯、情绪状态、生物心理状况）、用户社交环境（位置网、社交、群体动态）和用户任务（无意识活动、沉浸式任务、一般任务）。物理环境相关的情景也可以分为3类：位置（绝对位置、相对位置和位置网），设施（周围的计算资源、交流、任务表现）和物理条件（噪音、灯光、压力、空气质量）。
情景相关的人类特征可以被分为3类:用户基本信息（习惯、情绪状态、生物心理状况）、用户社交环境（位置网、社交、群体动态）和用户任务（无意识活动、沉浸式任务、一般任务）。物理环境相关的情景也可以分为3类：位置（绝对位置、相对位置和位置网），设施（周围的计算资源、交流、任务表现）和物理条件（噪音、灯光、压力、空气质量）。'''【位置可能有问题】'''
== Relational context : dynamic and non-user-centric definitions==
== Relational context : dynamic and non-user-centric definitions==
Whereas early definitions of context tended to center on users, or devices interfaced directly with users, the oft-cited definition from Dey<ref name="dey2001"/> ("''any information that can be used to characterize the situation of an entity''") could be taken without this restriction. User-centric context, as may be used in the design of [[human-computer interaction|human-computer interfaces]], may also imply an overly clearcut, and partially arbitrary, separation between "content" (anything which is ''explicitly'' typed in by users, or output to them), and context, which is ''implicit'', and used for [[context adaptation|adaptation]] purposes. A more dynamic and de-centered view, advocated by Dourish <ref> Dourish, Paul. "What we talk about when we talk about context." Personal and ubiquitous computing 8.1 (2004): 19-30.</ref> views context as primarily ''relational''. This was originally congruent with the move from desktop computing to [[ubiquitous computing]], but it does also fit with a broader understanding of [[ambient intelligence]] where the distinctions between ''context'' and ''content'' become relative and dynamic.<ref> https://www.researchgate.net/publication/230704197_Ambient_Intelligence Streitz, Norbert A., and Gilles Privat. "Ambient Intelligence" , ''Universal Access Handbook'' (2009)</ref> In this view, whichever sources of information (such as [[Internet of Things|IoT]] sensors) may be ''context'' for some uses and applications, might also be sources of primary ''content'' for others, and vice versa. What matters is the set of ''relationships'' that link them, together and with their environment. Whereas early descriptions of single-user-centric context could fit with classical [[Entity-attribute-value model|entity-attribute-value models]], more versatile graph-based information models, such as proposed with [[NGSI-LD]], are better adapted to capture the more relational view of context which is relevant for the [[Internet of Things]], [[Cyber-Physical Systems]] and [[Digital Twins]]. In this broader acceptation, context is not only represented as a set of attributes attached to an entity, it is also captured by a graph that enmeshes this entity with others. Context awareness is the capability to account for this cross-cutting information from different sources.
Whereas early definitions of context tended to center on users, or devices interfaced directly with users, the oft-cited definition from Dey<ref name="dey2001"/> ("''any information that can be used to characterize the situation of an entity''") could be taken without this restriction. User-centric context, as may be used in the design of [[human-computer interaction|human-computer interfaces]], may also imply an overly clearcut, and partially arbitrary, separation between "content" (anything which is ''explicitly'' typed in by users, or output to them), and context, which is ''implicit'', and used for [[context adaptation|adaptation]] purposes. A more dynamic and de-centered view, advocated by Dourish <ref> Dourish, Paul. "What we talk about when we talk about context." Personal and ubiquitous computing 8.1 (2004): 19-30.</ref> views context as primarily ''relational''. This was originally congruent with the move from desktop computing to [[ubiquitous computing]], but it does also fit with a broader understanding of [[ambient intelligence]] where the distinctions between ''context'' and ''content'' become relative and dynamic.<ref> https://www.researchgate.net/publication/230704197_Ambient_Intelligence Streitz, Norbert A., and Gilles Privat. "Ambient Intelligence" , ''Universal Access Handbook'' (2009)</ref> In this view, whichever sources of information (such as [[Internet of Things|IoT]] sensors) may be ''context'' for some uses and applications, might also be sources of primary ''content'' for others, and vice versa. What matters is the set of ''relationships'' that link them, together and with their environment. Whereas early descriptions of single-user-centric context could fit with classical [[Entity-attribute-value model|entity-attribute-value models]], more versatile graph-based information models, such as proposed with [[NGSI-LD]], are better adapted to capture the more relational view of context which is relevant for the [[Internet of Things]], [[Cyber-Physical Systems]] and [[Digital Twins]]. In this broader acceptation, context is not only represented as a set of attributes attached to an entity, it is also captured by a graph that enmeshes this entity with others. Context awareness is the capability to account for this cross-cutting information from different sources.
尽管情景的早期定义往往以用户或直接与用户交互的设备为中心，但 Dey 经常引用的定义（“可用于表征实体情况的任何信息”）不受此限制。以用户为中心的情景，尽管可以用于人机界面的设计，也可能暗示“内容”（用户明确输入或输出的任何内容）与“情景”（隐式的，用于适应目的）之间的分离之间过于明确且部分任意的分离。 Dourish 提倡一种更加动态和去中心化的观点，认为情景主要是关系性的，这最初与从桌面计算到普适计算的转变是一致的，但它也符合对环境智能的更广泛理解，即情景和内容之间的区别变得相对和动态。在这种观点中，无论信息来源（例如物联网传感器）可能是某些用途和应用的情景，还是其他人的主要内容来源，反之亦然。重要的是将他们联系在一起并与他们的环境联系起来的一组关系。尽管以单用户为中心的情景的早期描述可以适用于经典的实体-属性-值模型，但更通用的基于图的信息模型（例如 NGSI-LD 提出的）更适合捕获更相关的情景视图。与物联网、网络物理系统和数字孪生相关。大家普遍认为，情景不仅表示为附加到实体的一组属性，它还被一个将该实体与其他实体结合在一起的图所捕获。情景感知是解释来自不同来源的跨领域信息的能力。
尽管情景的早期定义往往以用户或直接与用户交互的设备为中心，但 Dey 经常引用的定义（“可用于表征实体情况的任何信息”）不受此限制。以用户为中心的情景，尽管可以用于人机界面的设计，也可能暗示“内容”（用户明确输入或输出的任何内容）与“情景”（隐式的，用于适应目的）之间的分离之间过于明确且部分任意的分离。 Dourish 提倡一种更加动态和去中心化的观点，认为情景主要是关系性的，这最初与从桌面计算到普适计算的转变是一致的，但它也符合对环境智能的更广泛理解，即情景和内容之间的区别变得相对和动态。在这种观点中，无论信息来源（例如物联网传感器）可能是某些用途和应用的情景，还是其他人的主要内容来源，反之亦然。重要的是将他们联系在一起并与他们的环境联系起来的一组关系。尽管以单用户为中心的情景的早期描述可以适用于经典的实体-属性-值模型，但更通用的基于图的信息模型（例如 NGSI-LD 提出的）更适合捕获更相关的情景视图。与物联网、网络物理系统和数字孪生相关。大家普遍认为，情景不仅表示为附加到实体的一组属性，它还被一个将该实体与其他实体结合在一起的图所捕获。情景感知是一种解释来自不同来源的跨领域信息的能力。
== Applications in situational or social awareness ==
== Applications in situational or social awareness ==
Context awareness has been applied to the area of [[computer-supported cooperative work]] (CSCW) to help individuals work and collaborate more efficiently with each other. Since the early 1990s, researchers have developed a large number of software and hardware systems that can collect contextual information (e.g., location, video feeds, away status messages) from users. This information is then openly shared with other users, thereby improving their situational awareness, and allowing them to identify natural opportunities to interact with each other. In the early days of context-aware computing, many of the systems developed for this purpose were specifically designed to assist businesses or geographically separated work teams collaborate on shared documents or work artifacts. More recently, however, there has been a growing body of work that demonstrates how this technique can also be applied to groups of friends or family members to help keep them apprised of each other's activities.
Context awareness has been applied to the area of [[computer-supported cooperative work]] (CSCW) to help individuals work and collaborate more efficiently with each other. Since the early 1990s, researchers have developed a large number of software and hardware systems that can collect contextual information (e.g., location, video feeds, away status messages) from users. This information is then openly shared with other users, thereby improving their situational awareness, and allowing them to identify natural opportunities to interact with each other. In the early days of context-aware computing, many of the systems developed for this purpose were specifically designed to assist businesses or geographically separated work teams collaborate on shared documents or work artifacts. More recently, however, there has been a growing body of work that demonstrates how this technique can also be applied to groups of friends or family members to help keep them apprised of each other's activities.
情景感知已被应用于计算机支持的协同工作 (CSCW) 领域，以帮助个人更有效地工作和协作。 自 1990 年代初以来，研究人员开发了大量软件和硬件系统，可以从用户那里收集情景信息（例如，位置、视频源、离开状态消息）。 然后，将这些信息与其他用户开放共享，从而提高他们的形势感知能力，有能力识别相互交流的自然机会。 在情景感知计算的早期，许多以此为目的开发系统，都是专门为帮助企业或地理上分散的工作团队在共享文档或工作工件上进行协作而设计的。 然而，最近有越来越多的工作展示了这种技术也可以应用于朋友或家庭成员群体，以帮助他们了解彼此的活动。
To date, systems that use context awareness to improve situational awareness can be characterised by:
To date, systems that use context awareness to improve situational awareness can be characterised by:
* the method by which they convey this information to other users
* the method by which they convey this information to other users
到目前为止，使用情景感知来改善情势察觉的系统可以被特征化为:
* 从每个用户那里收集的上下文，以及
* 从每个用户那里收集的情景，以及
* 将这些信息传达给其他用户的方法
* 将这些信息传达给其他用户的方法
The most common context to obtain and share for the purposes of improving situational awareness is the user's location. In an early prototype, the Active Badge system, for example, each user had a uniquely identifying badge that could be tracked via a series of overhead infrared sensors. As users walked throughout a building, their location was constantly monitored by a centralized server. Other users could then view this information (either in text form, or on a map, as was done in later work) to determine if a user is in her office, thereby allowing them to determine the best time to stop by for an unplanned conversation. Location was also shared in the PeopleTones, Serendipity, and the Group Interaction Support Systems to help users determine when they are near friends, users with shared personal interests, and teammates, respectively. In comparison with Active Badge, which only displays location information, these systems are more proactive, and will alert the users when they are in proximity of each other. This lets the user know when a potential interaction opportunity is available, thereby increasing his/her chances of taking advantage of it.
The most common context to obtain and share for the purposes of improving situational awareness is the user's location. In an early prototype, the Active Badge system, for example, each user had a uniquely identifying badge that could be tracked via a series of overhead infrared sensors. As users walked throughout a building, their location was constantly monitored by a centralized server. Other users could then view this information (either in text form, or on a map, as was done in later work) to determine if a user is in her office, thereby allowing them to determine the best time to stop by for an unplanned conversation. Location was also shared in the PeopleTones, Serendipity, and the Group Interaction Support Systems to help users determine when they are near friends, users with shared personal interests, and teammates, respectively. In comparison with Active Badge, which only displays location information, these systems are more proactive, and will alert the users when they are in proximity of each other. This lets the user know when a potential interaction opportunity is available, thereby increasing his/her chances of taking advantage of it.
为了改善情势察觉，最常见的获取和分享情景就是用户的位置信息。例如，在早期的原型机 Active Badge 系统中，每个用户都有一个独特的识别标志，可以通过一系列的间接红外传感器来跟踪。当用户在建筑物中行走时，他们的位置信息会被一个集中的服务器持续监控。然后，其他用户可以查看这些信息(以文本形式或在地图上查看) ，以确定用户是否在办公室，从而允许他们确定非预约访问的最佳时间。位置信息也在PeopleTones、 Serendipity 和 Group Interaction Support 系统中进行了共享，以帮助用户分别确定他们何时与朋友、有共同兴趣的用户和队友关系密切。与只显示位置信息的 Active Badge 相比，这些系统更加积极主动，当用户彼此靠近时会提醒他们。这样可以让用户知道什么时候有潜在的交互机会，从而增加他/她利用这个机会的机会。
Another popular context to share is a user's work activity, often by sharing video. In the Community Bar system,<ref>{{cite conference
Another popular context to share is a user's work activity, often by sharing video. In the Community Bar system,<ref>{{cite conference
Another popular context to share is a user's work activity, often by sharing video. In the Community Bar system, researchers developed a desktop application that periodically took screenshots of the user's display. This information was then shared with the user's co-workers so that they could know what documents/artifacts their teammates was working on, and provided a common frame of reference so that users could n talk about these artifacts as if they were collocated. In Montage, users are given the ability to remotely activate the webcam on another user's computer for a brief amount of time. This capability to "glance" at another user lets users see if they are busy or preoccupied, which in turn helps them better determine the most opportune time to initiate a conversation.
Another popular context to share is a user's work activity, often by sharing video. In the Community Bar system, researchers developed a desktop application that periodically took screenshots of the user's display. This information was then shared with the user's co-workers so that they could know what documents/artifacts their teammates was working on, and provided a common frame of reference so that users could n talk about these artifacts as if they were collocated. In Montage, users are given the ability to remotely activate the webcam on another user's computer for a brief amount of time. This capability to "glance" at another user lets users see if they are busy or preoccupied, which in turn helps them better determine the most opportune time to initiate a conversation.
另一个流行的分享情景是用户的工作活动，通常是通过分享视频。在 Community Bar 系统中，研究人员开发了一个桌面应用程序，定期对用户的显示屏幕截图。然后，这些信息与用户的同事共享，以便他们能够知道他们的队友正在处理哪些文档/工件，并提供一个共同的参考框架，以便用户能够像自己做过一样谈论这些文件/工件。在蒙太奇中，用户可以在短时间内远程激活另一个用户电脑上的网络摄像头。这种“扫视”另一个用户的功能可以让用户看到他们是否忙碌或全神贯注，从而帮助他们更好地确定启动对话的最佳时机。
A third type of context to share to improve or enhance situational awareness is the user's audio. In the Thunderwire system,<ref>{{cite journal
A third type of context to share to improve or enhance situational awareness is the user's audio. In the Thunderwire system,<ref>{{cite journal
systems also rely heavily on audio in order to determine if and when a user was potentially interruptible. Unlike Thunderwire, however, these systems rely on machine learning algorithms in order to analyze the user's audio and determine if the user is talking. This allows the system to provide other users with the same context (i.e., whether or not the user is in a conversation) without having to share the actual audio, thereby making it more privacy centric.
systems also rely heavily on audio in order to determine if and when a user was potentially interruptible. Unlike Thunderwire, however, these systems rely on machine learning algorithms in order to analyze the user's audio and determine if the user is talking. This allows the system to provide other users with the same context (i.e., whether or not the user is in a conversation) without having to share the actual audio, thereby making it more privacy centric.
第三种可以分享以改进或增强情景识别的内容是用户的音频。在 Thunderwire 系统中，研究人员开发了一个只有音频的媒体空间，允许朋友们分享来自移动设备的麦克风的原始音频。这个系统本质上是一个永久性的电话会议，允许用户收听其他用户的音频，以确定他们是否以及何时参与了对话。WatchMe 和 ListenIn 系统还严重依赖音频，以确定用户是否以及何时可能被中断。然而，与 Thunderwire 不同的是，这些系统依赖于机器学习算法来分析用户的音频并确定用户是否在说话。这使得系统可以为其他用户提供相同的情景(例如，用户是否在对话中) ，而无需共享实际的音频，从而使其更加以隐私为中心。
A fourth type of context that is commonly shared is the user's overall activity. In the Hubbub<ref>{{cite conference
A fourth type of context that is commonly shared is the user's overall activity. In the Hubbub<ref>{{cite conference
A fourth type of context that is commonly shared is the user's overall activity. In the Hubbub and Conchat systems, researchers developed a series of instant messenger applications that monitored when the user was active or idle using either software, or environmental sensors, respectively. This information could then be provided to other users to let them know if and when their friends were available to respond to their messages. In the Digital Family Portrait system, researchers developed a digital picture frame that provides qualitative visualizations of a user's (i.e., an elderly parent/grandparent) daily activities. This visualization is then provided to the user's adult children so that they could "check up" on their parents without having to explicitly bother them, thereby allowing them to "age in place."
A fourth type of context that is commonly shared is the user's overall activity. In the Hubbub and Conchat systems, researchers developed a series of instant messenger applications that monitored when the user was active or idle using either software, or environmental sensors, respectively. This information could then be provided to other users to let them know if and when their friends were available to respond to their messages. In the Digital Family Portrait system, researchers developed a digital picture frame that provides qualitative visualizations of a user's (i.e., an elderly parent/grandparent) daily activities. This visualization is then provided to the user's adult children so that they could "check up" on their parents without having to explicitly bother them, thereby allowing them to "age in place."
第四种通常共享的情景类型是用户的整体活动。在 Hubbub 和 Conchat 系统中，研究人员分别开发了一系列即时通信应用程序，可以通过软件或环境传感器监测用户的活动或空闲时间。这些信息可以提供给其他用户，让他们知道他们的朋友是否以及何时可以回复他们的消息。在数码家庭肖像系统中，研究人员开发了一种数码相框，可以提供用户(即年长的父母/祖父母)日常活动的定性可视化效果。然后，这个可视化图像被提供给用户的成年子女，这样他们就可以“检查”他们的父母，而不必直接地打扰他们，从而允许他们“在适当的地方长大”
Although these system demonstrate how context awareness can be used to support situational and social awareness, the long term effectiveness of these systems are not yet fully understood. Many of the systems described above have only been evaluated at a conceptual level, or to demonstrate that the system is technically feasible. Consequently, while initial results from these studies suggest that context awareness can support situational awareness tasks, more longitudinal data is required.
Although these system demonstrate how context awareness can be used to support situational and social awareness, the long term effectiveness of these systems are not yet fully understood. Many of the systems described above have only been evaluated at a conceptual level, or to demonstrate that the system is technically feasible. Consequently, while initial results from these studies suggest that context awareness can support situational awareness tasks, more longitudinal data is required.
Although these system demonstrate how context awareness can be used to support situational and social awareness, the long term effectiveness of these systems are not yet fully understood. Many of the systems described above have only been evaluated at a conceptual level, or to demonstrate that the system is technically feasible. Consequently, while initial results from these studies suggest that context awareness can support situational awareness tasks, more longitudinal data is required.
Although these system demonstrate how context awareness can be used to support situational and social awareness, the long term effectiveness of these systems are not yet fully understood. Many of the systems described above have only been evaluated at a conceptual level, or to demonstrate that the system is technically feasible. Consequently, while initial results from these studies suggest that context awareness can support situational awareness tasks, more longitudinal data is required.
虽然这些系统展示了如何使用情景感知来支持情景和社会感知，但是这些系统的长期效果还没有尚未可知。上述许多系统只是在概念层面上进行了评估，或只证明该系统在技术上是可行的。因此，虽然这些研究的初步结果表明，情景感知可以支持情势察觉任务，但还需要更多的纵向数据。
== Application in health care ==
== Application in health care ==