IEEE 1589-2020 pdf free download – IEEE Standard for Augmented Reality Learning Experience Model
aetlvlrs: The caution of a planned woetfiow following a specific process, leading typically from heginning to end. regardless of whether the anticipated learning outcome is achieved.
augineatatlo.: The digital representation of ellector oiaputs that serve to stinsilate the sensory npcrieire oldie user, including output to visual, audio, haptie. and other modalities.
atigmetitad.. prlfltb’t: lit types of annotations available are defined in the augmented reality (AR) training systeiit They include, but are not limited to, audio, video. inages, animations, lahek, and vilirotactile patterns
augnietsird realIty (Alti: Human perception is enhanced with additional computer-generated sensorial input to create a new user cspcrscnce, including, his not restrictal to, enhancing human vision by cotribining natural with digital oilers.
augmented rralln (AR) tracking subssvtrm: A coniunerit ol the augrncnted reality tARt training system that detects position markers and anchors. typically (hut not Imitated to) using cotrgiiser vision to detenntne the location of makers, image targets, or spatial anchors in a room scan,
augninitrd rraliti (Alt) trai.i sisirm: An augmented reality (AR) training system asma%mst% ola single sottw-are application or a set of soliware applications, and connected delivery hardware (such as a head’ mounted display. LIMP), that allow trainees to practice and perform predefined leaning activities rn a given workplaee It may also include authorwtg functionality to facilitate the creation of new learning aetivitict
drtretablr: Entities that 111* to fiducial markers, target feature models, or other sensor state properties providing input to computer vision and other sensor processing systems, They have a unique identity and link to data enabling their tracking with the help of the sensor processing system referenced.
rsprrlrner API (5API): A leaning analytics application programming interface (API), standardizing comnsinicaaion with a learning record store for logging learner perfonnanee. Any augmented reality (AR) training system nay optionally use the sAPI to keep andor retrieve records of the users’ learning activities. ll’sAPI logging ts supported. zAPI iaatement queries naiy be used in the if.rules to control the activity
lranslmsg actlvlti: An activity that motivates the dcvelopnsent of competence (it. knowledge. skills, abilities, and other characteristics).
lranslmsg raperlener: The cognitive and sensory-motoric effect on the user from perfonning a learning activtty in a particular workplace.
predIcate: Reusable instructional augnientations, configuring a specific augmentation primitive for its use at activities. The set of predicates deitned in a workplace nsmdel is a domain-specific language for instruction in the workplace under conaidemaiiois. typically including all required verbs of handling and nanememit and their visual overlay animations smgnifynsg tlsent
sensar: A device that detects or measures physical clsaracicrrsiics and cotnnstnicases the data generated digitally. such as a heart rate sensor, a gyroscope, or a isindescript lniernet-of’Things sensor that aignala. kir esaiqale. whether a specific button Ins been pressed dunng operation of a manufacturing machine.
trlt,tzrr: A mechanism fmnng an event on conwsletmon of an action step that allows the statements in the esit section of the action step to be released.
al1datkm constraint: Obsened user behavior is checked. recorded in an experience application programming interface tsAPlI endpoint. to control the flow of actions. It includes a query and the corresponding if- then rules defining with which action step to react to the given rewlts’ constraitas.
warnltsg sigas: Graphical symbols that itsiicate a potential hazard. obstacle, a requirement relating to the slenufication and nauasgenrnt of risks in the workplace
wurkplaer: A physical environment in which users perfonn and learn to perform tasks with real-world and vtrtual objects.
4. Learning In activities and workplaces
I*scnxina LI 1csrr..in of two L. L.,s. L.arnits iitmiti,. wnt.nn task- dependent descriptions of how so instruct with real and virtual elements in the sequence of actions Workplace environment and context descriptions exitisisi of data concerning si*kh real and virtual elenunts exist and are featured within the experience.
The deflnttion of an activity mixture for learning by experience includes orchestration of user interaction across multiple devices. Furthermore, it integeates the trac king of and responses to user interaction across devices and sensors. Optionally. if-rules may be defined and evaluated as part of the activity to test for user achiewenients or action outcomes usrng data from sine or more software andor hardware senion
The atvlsv riwdrlsng lwegiragr (acrisin-MLS in this standard is a domain-specific language used to describe the activity inislure. The smrkpia’r mis/cling kmçuagr fworkplucr’SlLi at this standard coinplenieists the activity representation language to realise snaeropaab,lity of applications interpreting activityMl.. It is a doniain-spccilic language for describing the tangibles. configsnhles. arid basic triggers of a workplace (see Figure I).IEEE 1589 pdf download.