Semantic Location Based Services for Smart Spaces

Kolomvatsos, Kostas; Papataxiarhis, Vassilis; Tsetsos, Vassileios

doi:10.1007/978-0-387-77745-0_51

Cited by 11 publications

(8 citation statements)

References 8 publications

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“…They focused on indoor Location Based Services (LBS) and coding real world objects. In [4] next basic approaches and components for integration are suggested: spacial ontology, ontologydriven map annotation, GIS-based ontology population and navigation algorithms. This approach is very justified from application point of view but has several limitation if we consider context free integration (without any assumptions about application domain).…”

Section: Related Workmentioning

confidence: 99%

Geo-coding in Smart Environment: Integration Principles of Smart-M3 and Geo2Tag

Krinkin¹,

Yudenok

2013

Internet of Things, Smart Spaces, and Next Generation Networking

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Abstract. Geo-tagging and smart spaces are two promising directions in modern mobile market. Geo-tagging allows to markup any kind of data by geographical coordinates and time. This is the basis for defining geographical context which can be used in different types of applications e.g. semantic information search, machine-to-machine (M2M) interactions. Smart spaces as the basis for seamless distributed communication field for software services provides semantic level for data processing. Most desired feature of coming software is pro-activeness and context awareness, i.e. services will be able to adapt to the user's needs and situations and be able to manage decisions and behaviors on behalf of the user. The paper is dedicated discussion of integration most popular open platforms for smart spaces and geo-tagging (Smart-M3 and Geo2Tag) as possible solution for creation context aware proactive location based (LBS) services.

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Section: Related Workmentioning

confidence: 99%

Geo-coding in Smart Environment: Integration Principles of Smart-M3 and Geo2Tag

Krinkin¹,

Yudenok

2013

Internet of Things, Smart Spaces, and Next Generation Networking

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“…This work proposed a semantic model that can be used to describe indoor navigation paths. Similarly, a semantic description model derived from a spatial ontology was used to describe the basic elements of navigation paths in [28]. A human-centered semantic indoor navigation system was also proposed in [29].…”

Section: Related Workmentioning

confidence: 99%

Activity Recognition and Semantic Description for Indoor Mobile Localization

Guo

Xiong

Zheng

et al. 2017

Sensors

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As a result of the rapid development of smartphone-based indoor localization technology, location-based services in indoor spaces have become a topic of interest. However, to date, the rich data resulting from indoor localization and navigation applications have not been fully exploited, which is significant for trajectory correction and advanced indoor map information extraction. In this paper, an integrated location acquisition method utilizing activity recognition and semantic information extraction is proposed for indoor mobile localization. The location acquisition method combines pedestrian dead reckoning (PDR), human activity recognition (HAR) and landmarks to acquire accurate indoor localization information. Considering the problem of initial position determination, a hidden Markov model (HMM) is utilized to infer the user’s initial position. To provide an improved service for further applications, the landmarks are further assigned semantic descriptions by detecting the user’s activities. The experiments conducted in this study confirm that a high degree of accuracy for a user’s indoor location can be obtained. Furthermore, the semantic information of a user’s trajectories can be extracted, which is extremely useful for further research into indoor location applications.

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“…Kolomvatsos et al. (2007) presented Indoor Navigation Ontology (INO), a spatial ontology, which is an extended version of INO presented by Tsetsos et al.…”

Section: Related Workmentioning

confidence: 99%

“…(2005) and the visually impaired in Swobodzinski and Raubal (2009). The technique developed by Kolomvatsos et al. (2007) is also not based on any standards making the result unreliable with respect to applicability to the needs of impaired individuals.…”

Section: Related Workmentioning

confidence: 99%

Indoor Routing for Individuals with Special Needs and Preferences

Karimi

Ghafourian

2010

Transactions in GIS

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Recently much research has been focused on developing techniques and systems for providing routes within buildings. While outdoor routing is based on criteria such as shortest, fastest and least turns, indoor routing is primarily based on accessibility and safety criteria, and while outdoor routing could adversely be impacted by weather and traffic, among other conditions, such conditions do not affect indoor routing. However, developing techniques that meet user's indoor routing preferences, especially those with special needs, is a challenging task. An example is development of a set of techniques that avoids a hallway with a protruding object to allow safe passage by the visually impaired or that avoids stairs for the mobility impaired. In this article, we present and analyze new techniques based on the Americans with Disabilities Act (ADA) standards that provide routes within buildings and meet user's special needs and preferences.t gis_1198 299..330 little provision for user preferences (Birgri 2007). Functionality beyond those generic functions (e.g. navigation both indoors and outdoors), may require a user to carry multiple devices. Even the most capable handheld navigation devices suffer from limitations of the underlying techniques and technologies such as GPS, the most prevalent geo-positioning technology for navigation (Barnes et al. 2003), map databases, and the lack of navigation support for people with special needs. Such shortcomings compel users to accept solutions that may not meet their needs and preferences (Byron 2004).To overcome the shortcomings of current navigation systems, we are developing techniques and technologies for UNAVIT (Universal NAVIgation Technology), which we define as a navigation framework capable of providing navigation assistance anywhere, anytime, and for any user, transparently and adaptively Karimi 2009, 2010;Karimi and Ghafourian 2009). With respect to anywhere, UNAVIT supports navigation both in indoors and outdoors. In other words, UNAVIT would address the navigation needs of users with special needs and different preferences regardless of their location (e.g., indoor or outdoor). For this, UNAVIT considers the differences between the physical structures of indoors and outdoors, as each environment requires different sets of data, techniques, and technologies. Of such differences, those between road networks and hallway networks and those between outdoor routing, which are affected by such factors as weather and traffic, and indoor routing, which are affected by accessibility, are worth mentioning.While there exist techniques and technologies that provide routes for people with special needs and preferences, they have shortcomings. For example, some techniques and technologies only address the special needs of a given group (e.g. the visually impaired), and some do not adhere to the standards set for the mobility impaired (e.g. accessibility of buildings).In this article, we leverage our research on indoor routing, ONALIN, which is an indoor routing ontology and th...

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Semantic Location Based Services for Smart Spaces

Cited by 11 publications

References 8 publications

Geo-coding in Smart Environment: Integration Principles of Smart-M3 and Geo2Tag

Geo-coding in Smart Environment: Integration Principles of Smart-M3 and Geo2Tag

Activity Recognition and Semantic Description for Indoor Mobile Localization

Indoor Routing for Individuals with Special Needs and Preferences

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