Journal of Location Based Services
`Vol. 1, No. 2, June 2007, 89–111
`
`REVIEW ARTICLE
`
`Applications of location–based services: a selected review
`
`Jonathan Rapera*, Georg Gartnerb, Hassan Karimic and Chris Rizosd
`
`aInformation Science, Northampton Square, City University, London, EC1V OHB, UK;
`bDepartment of Geoinformation and Cartography, Vienna University of Technology,
`Erzherzog–Johannplatz 1, Vienna A–1040, Austria; cUniversity of Pittsburgh, PA, USA;
`dSchool of Surverying 2 SIS, University of New South Wales, Sydney, 2052, Australia
`
`(Accepted 18 December 2007)
`
`This article reviews a selected set of location–based services (LBS) that have been
`published in the research literature, focussing on mobile guides, transport
`support, gaming, assistive technology and health. The research needs and
`opportunities in each area are evaluated and the connections between each
`category of LBS are discussed. The review illustrates the enormous diversity
`of forms in which LBS are appearing and the wide range of application sectors
`that are represented. However, very few of these applications are implemented
`pervasively on a commercial basis as this is still challenging technically and
`economically.
`
`Keywords: mobile guides; location–based gaming; intelligent transport systems
`
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`1. Introduction
`
`In this second Editorial Lead Paper for the Journal of Location Based Services (JLBS) we
`aim to review a selection of published applications studies in the field and assess the way
`they implement the theoretical developments discussed in the first Editorial Lead Paper
`(Raper et al. 2007). The distribution of the papers found in a thorough but selective
`literature review is also assessed as an indication of the real domain of utility for LBS and
`to indicate where further theoretical work is needed. This work is intended to be inclusive
`of all disciplines in which location can be a driver for information selection, processing and
`delivery, so that the Journal can facilitate the exchange of experiences between application
`sectors developing LBS.
`
`2. Literature review
`
`Inevitably in such a fractured and multi-disciplinary field, many applications will have
`escaped our attention or will lie in the gap between implementation and appearance in
`the literature. This review is being completed in the second half of 2007 and represents the
`state of knowledge as close to this date as possible. However, note that this review only
`
`*Corresponding author. Email: raper@soi.city.ac.uk
`
`ISSN 1748–9725 print/ISSN 1748–9733 online
`ß 2007 Taylor & Francis
`DOI: 10.1080/17489720701862184
`http://www.informaworld.com
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`90
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`J. Raper et al.
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`covers the published literature, and no material from white papers or online presentations
`is included as it is impossible to know the origin or validity of some (much?) of
`this material. It is a medium term aspiration of this Journal to establish an online
`repository/link library of this ‘grey literature’, so that it may be accessed and read on
`a ‘caveat emptor’ basis, and curated for the long term when patent disputes may make
`such documentation particularly important.
`The rest of this article reviews the key areas where LBS technology has been influential,
`looking at established areas such as mobile guides and intelligent transport systems as well
`as emerging areas such as location-based gaming, assistive technology and location-based
`health applications.
`
`3. Mobile guides
`
`The largest group of LBS applications is in a field known as ‘mobile guides’. A mobile
`guide can be defined as a portable, location-sensitive and information-rich digital guide to
`the user’s surroundings. This definition covers a wide range of designs and usage
`situations, which can be classified and evaluated in a variety of different ways.
`Most mobile guides are offering new services to users, but a part of all mobile guides
`is the potential replacement of paper guides and map books. This has opened a debate
`about what functions are best provided on paper or digitally, with the update rate and
`need for spatial precision being the best discriminators. Most paper guidebooks are
`published no more than annually and do not have built-in positioning, which creates a
`natural opportunity for digital mobile guides to fill.
`A survey of mobile guides by Baus et al. (2005) characterised them by:
`. Geopositioning (whether GPS, wifi or other)
`. Architecture (client-server or distributed applications)
`. Situational factors (focussed on what the user is doing and how this changes)
`. Adaptation (e.g. handling varying positional quality)
`. Interface (multi-modal or text/pointing systems)
`. Network access (whether connected or using local caching)
`. Maps used (map interfaces on a small screen should be schematised if possible)
`
`Baus et al. (2005) argued that the greatest future potential lay in collaborative usage of
`mobile guides where users are able to view the tracks and recommendations of colleagues,
`i.e. mobile social networking.
`Kruger et al. (2007) reviewed ‘adaptive mobile guides’ with a navigation focus,
`which they considered to be classic examples of context-sensitive applications.
`They divided mobile guides into the following categories:
`. Resource adapted– optimised in advance for regular patterns of usage
`. Resource adaptive– rely on a single strategy for resource usage
`. Resource adapting– has ability to adapt to resource situations using multiple
`strategies
`
`They argued that these categories of adaptation are particularly important for location
`determination (where the outdoor/indoor transition requires a switch between methods),
`and for situational responsiveness. They further explore modelling of users, context and
`
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`Journal of Location Based Services
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`91
`
`the conceptual model
`for adaptation through the use of
`situations as drivers
`UBISWORLD, the user markup language UserML and the ontology model Gumo.
`Kruger et al. (2007) developed a further classification of indoor and outdoor
`mobile guides (including shopping guides not considered here) along the following axes:
`. Adaptivity (using the Kruger et al. 2007 template)
`. Geopositioning (GPS or wifi outdoors, infrared indoors)
`. Knowledge representation (relational model or ontology model)
`. Number of users (mostly one)
`. User model (based on stereotypes, user preferences or UBISWORLD)
`. Social context (multi-user approach)
`. Presentation metaphor (map, virtual model, book, kiosk)
`. Platform (PDA, phone, kiosk)
`
`However, this classification is strongly influenced by the user modelling approach,
`and it does not evaluate whether the information is pushed or pulled by the user, the
`spatio-temporal expression of the location-based content, or the use case for the system.
`Based on a wide survey of the many systems now being built, and building on these
`previous classifications, it is argued here that the canonical axes of comparison for mobile
`guides should be defined from a broader perspective. It is argued therefore that the
`following factors should be used to characterise mobile guides:
`. Positioning quality (focussing on the accuracy and pervasiveness of
`technology)
`. Architecture (client-server or distributed applications)
`. Presentation metaphor (map, web page, book, kiosk, AR, VR)
`. Content relevance (geographic and semantic relevance of the content for the user)
`. Delivery (focussing on whether the user actively selects or passively receives)
`. Use case (whether navigation, mobile search, tour etc.)
`. Adaptivity (using the Kruger et al. 2007 template)
`
`the
`
`Though a classification with seven axes is complex, and some of these axes are part-
`correlated (e.g. presentation metaphor and use case), by classifying the existing mobile
`guides, patterns of design choices and evolution through time can clearly be seen.
`Searching the current JLBS bibliography of 500 research publications yields 34 mobile
`guides that have progressed beyond temporary laboratory existence, been tested with real
`users and published in the literature. This is an approximation of the total number
`of mobile guides as some have been developed and not published, some lack distinguishing
`characteristics, e.g. a screen, and others such as commercial personal navigation devices
`have proprietary and unpublished architectures and limited informational features and so
`cannot be evaluated easily.
`The list of mobile guides has been clustered using two different strategies to explore
`the commonalities, firstly by architecture/positioning, secondly by use case, and the
`resulting groupings are discussed below and shown in Tables 1 and 2. As the scoring of
`the mobile guides is based on published (and interpreted) information, the groups are
`inherently conjectural, however, the exercise serves to erect some hypotheses that may be
`tested by further analysis. The citations to each of the systems mentioned are in
`the tables.
`
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`

`Client/serverMap/book
`Client/serverMap/book/VR
`Client/serverMap/book/AR/VRAroundMe/aheadPull/pushMobileSearch/tourAdaptingM’tain&MacFarl’ne(2007)
`Client/serverMap/book
`AroundMe
`Client/serverMap
`Route
`Client/serverMap
`Route
`Client/serverMap/book
`AroundMe
`Client/serverMap/VR
`AroundMe
`Client/serverMap/book/speechAroundMe
`AroundMe
`Client/serverMap/book
`AroundMe
`Client/serverMap/book
`AroundMe/aheadPull
`Client/serverMap/book
`Pull
`AroundMe
`Client/serverMap/book
`Push/pull
`AroundMe
`Client/serverMap/book
`AroundMe/aheadPull
`Client/serverMap/book
`Push
`AroundMe
`Client/serverMap/book
`Push/pullMobileSearch
`AroundMe
`Client/serverBook/map
`MobileSearch
`Push
`AroundMe
`Client/serverBook/map
`MobileSearch
`Pull
`AroundMe
`Client/serverMap/book
`
`Adaptive
`Adapted
`Adapting
`AdaptiveKwonetal.(2005)
`Adapted
`AdaptingYueetal.(2005)
`AdaptiveGo¨keretal.(2004)
`Adapted
`Adapting
`Adapted
`Adapted
`AdaptingMountain&Raper(2000)
`AdaptingMalakaandZipf(2000)
`AdaptingKindbergetal.(2000)
`AdaptingDaviesetal.(1999)
`Abowdetal.(1997)
`Adapted
`
`Jimisonetal.(2007)
`Topi(2006)
`Sarjakoskietal.(2005)
`
`Schillingetal.(2005)
`
`Simcocketal.(2003)
`Edwardesetal.(2003)
`Schmidt-Belzetal.(2003)
`Pospischiletal.(2002)
`
`Dunlopetal.(2004)
`
`Adapted
`
`MobileSearch
`
`AdaptingCoppolaetal.(2004)
`
`MobileSearch
`
`Pull
`
`Push
`
`AroundMe
`
`Map/book
`
`Sync
`
`WiFi/self
`
`Tourism
`
`TaenebCityGuide
`
`AroundMe
`
`Map/book
`
`Applets
`
`WiFi/Tags
`
`Tourism
`
`MOBE
`
`AdaptiveHechtetal.(2007)
`AdaptiveHechtetal.(2007)
`Adaptive
`Santoroetal.(2007)
`AdaptedMo¨hringetal.(2004)
`
`MobileSearch
`Tour
`Tour
`MobileSearch
`
`Push
`Push
`Push/pull
`Pull
`
`EventtriggerMap/book
`Authored
`EventtriggerMap/book/speechAuthored
`EventtriggerMap/book/speechAroundMe
`EventtriggerVideoimagery
`
`AR
`
`Self/gesture
`GPS
`IR/tags/gesture
`Tags
`
`Tourism
`Tourism
`Museum
`Tourism
`
`WikiEye
`Minotour
`MarbleMuseum
`PhoneGuide
`
`Eisenhaueretal.(2005)
`
`Aokietal.(2002)
`Bausetal.(2002)
`
`Adaptive
`AdaptedWooetal.(2004)
`AdaptingKru¨ger(2004)
`Adapted
`Adapting
`
`Tour
`Tour
`Navigation
`Tour
`
`Push
`Push
`Push
`Push
`Push/pullNavigation
`
`AroundMe
`Authored
`Route
`AroundMe
`AroundMe/AR
`
`Soundscape
`Soundscape
`Map/speech/VR
`Book/speech
`Map/speech
`
`Museum
`Broadcast
`Museum
`Broadcast
`TransportGPS/IR
`Broadcast
`Museum
`Broadcast
`TransportGPS/IR/compassBroadcast
`
`WiFi
`GPS/compass
`
`WiFi
`
`LISTEN
`Syren
`BPN
`SottoVoce
`REAL
`
`AdaptingKoutsiourisetal.(2007)
`AdaptingRocchietal.(2004)
`Adapting
`Adapted
`
`Sparacino(2002)
`Feineretal.(1997)
`
`Push/pullMobileSearch
`Push
`Push
`Push
`
`Tour
`Tour
`MobileSearch
`
`AroundMe
`Authored
`AR
`AR
`
`Client/serverVideoimagery
`Client/serverVideoimagery
`Client/serverVideoimagery
`Client/serverVideoimagery
`
`GPS
`IR/WiFi
`IR
`GPS
`
`EntertainmentGuideTourism
`PEACH
`Museum
`MuseumWearableMuseum
`Tourism
`MARS
`
`AdaptiveO’Gradyetal.(2005)
`AdaptingArikawaetal.(2007a)
`
`Push/agentMobileSearch
`Pull
`
`Navigation
`
`Pull
`MobileSearch
`Pull
`Navigation
`Pull
`Navigation
`Pull
`MobileSearch
`Pull
`Navigation
`Pull
`MobileSearch
`Push/pullMobileSearch
`Push/pullMobileSearch
`MobileSearch
`Tour
`Tour
`MobileSearch
`Tour
`
`AroundMe
`Route
`
`Tourism
`TransportGPS/compass
`Tourism
`GPS/compass
`Tourism
`GPS
`TransportGPS
`RecreationGPS
`GPS
`Tourism
`TransportGPS/self
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`
`GPS
`Tags
`GPS/DGPS
`GPS
`GPS
`GPS/self
`GPS
`WiFi
`IR
`WiFi/self
`GPS/IR
`
`GPS
`
`GulliversGenie
`Navitime
`Camineo
`Wigglestick
`MUMS
`GIMODIG
`MobileSeoulSearch
`Tellmaris
`TGH
`Ambiesense
`TouristGuide
`WebPark
`CRUMPET
`Lol@
`Hypergeo
`DeepMap
`Cooltown
`Guide
`Cyberguide
`
`AdaptivityPublication
`
`Usecase
`
`ContentrelevanceDelivery
`
`ArchitecturePresentation
`
`ApplicationPositioning
`
`ShortName
`
`Table1.Mobileguidesclassifiedbyarchitectureandpresentation.
`
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`Client/serverMap/book
`Client/serverMap/book/VR
`Client/serverMap/book/AR/VRAroundMe/aheadPull/pushMobileSearch/tourAdaptingM’tain&MacFarl’ne(2007)
`Client/serverMap/book
`AroundMe
`Client/serverMap
`Route
`Client/serverMap
`Route
`Client/serverMap/book
`AroundMe
`Client/serverMap/VR
`AroundMe
`Client/serverMap/book/speechAroundMe
`AroundMe
`Client/serverMap/book
`AroundMe
`Client/serverMap/book
`AroundMe/aheadPull
`Client/serverMap/book
`Pull
`AroundMe
`Client/serverMap/book
`Push/pull
`AroundMe
`Client/serverMap/book
`AroundMe/aheadPull
`Client/serverMap/book
`Push
`AroundMe
`Client/serverMap/book
`Push/pullMobileSearch
`AroundMe
`Client/serverBook/map
`MobileSearch
`Push
`AroundMe
`Client/serverBook/map
`MobileSearch
`Pull
`AroundMe
`Client/serverMap/book
`
`Adaptive
`Adapted
`Adapting
`AdaptiveKwonetal.(2005)
`Adapted
`AdaptingYueetal.(2005)
`AdaptiveGo¨keretal.(2004)
`Adapted
`AdaptingEdwardesetal.(2003)
`Adapted
`Adapted
`AdaptingMountain&Raper(2000)
`AdaptingMalakaandZipf(2000)
`AdaptingKindbergetal.(2000)
`AdaptingDaviesetal.(1999)
`Abowdetal.(1997)
`Adapted
`
`Simcocketal.(2003)
`
`Schmidt-Belzetal.(2003)
`Pospischiletal.(2002)
`
`Jimisonetal.(2007)
`Topi(2006)
`Sarjakoskietal.(2005)
`
`Schillingetal.(2005)
`
`AdaptingCoppolaetal.(2004)
`
`MobileSearch
`
`Push
`
`AroundMe
`
`Map/book
`
`Applets
`
`WiFi/Tags
`
`Tourism
`
`MOBE
`
`AdaptiveHechtetal.(2007)
`AdaptiveHechtetal.(2007)
`Adaptive
`Santoroetal.(2007)
`AdaptedMo¨hringetal.(2004)
`
`MobileSearch
`Tour
`Tour
`MobileSearch
`
`Push
`Push
`Push/pull
`Pull
`
`EventtriggerMap/book
`Authored
`EventtriggerMap/book/speechAuthored
`EventtriggerMap/book/speechAroundMe
`EventtriggerVideoimagery
`
`AR
`
`Self/gesture
`GPS
`IR/tags/gesture
`Tags
`
`Tourism
`Tourism
`Museum
`Tourism
`
`WikiEye
`Minotour
`MarbleMuseum
`PhoneGuide
`
`Eisenhaueretal.(2005)
`
`Adaptive
`AdaptedWooetal.(2004)
`AdaptingKru¨ger(2004)
`Adapted
`Aokietal.(2002)
`AdaptingBausetal.(2002)
`
`Tour
`Tour
`Navigation
`Tour
`
`Push
`Push
`Push
`Push
`Push/pullNavigation
`
`AroundMe
`Authored
`Route
`AroundMe
`AroundMe/AR
`
`Soundscape
`Soundscape
`Map/speech/VR
`Book/speech
`Map/speech
`
`Museum
`Broadcast
`Museum
`Broadcast
`TransportGPS/IR
`Broadcast
`Museum
`Broadcast
`TransportGPS/IR/compassBroadcast
`
`WiFi
`GPS/compass
`
`WiFi
`
`LISTEN
`Syren
`BPN
`SottoVoce
`REAL
`
`AdaptingKoutsiourisetal.(2007)
`AdaptingRocchietal.(2004)
`Adapting
`Adapted
`
`Sparacino(2002)
`Feineretal.(1997)
`
`Push/pullMobileSearch
`Push
`Push
`Push
`
`Tour
`Tour
`MobileSearch
`
`AroundMe
`Authored
`AR
`AR
`
`Client/serverVideoimagery
`Client/serverVideoimagery
`Client/serverVideoimagery
`Client/serverVideoimagery
`
`GPS
`IR/WiFi
`IR
`GPS
`
`EntertainmentGuideTourism
`PEACH
`Museum
`MuseumWearableMuseum
`Tourism
`MARS
`
`AdaptiveO’Gradyetal.(2005)
`AdaptingArikawaetal.(2007)
`
`Push/agentMobileSearch
`Pull
`
`Navigation
`
`Pull
`MobileSearch
`Pull
`Navigation
`Pull
`Navigation
`Pull
`MobileSearch
`Pull
`Navigation
`Pull
`MobileSearch
`Push/pullMobileSearch
`Push/pullMobileSearch
`MobileSearch
`Tour
`Tour
`MobileSearch
`Tour
`
`AroundMe
`Route
`
`Tourism
`TransportGPS/compass
`Tourism
`GPS/compass
`Tourism
`GPS
`TransportGPS
`RecreationGPS
`GPS
`Tourism
`TransportGPS/self
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`Tourism
`
`GPS
`Tags
`GPS/DGPS
`GPS
`GPS
`GPS/self
`GPS
`WiFi
`IR
`WiFi/self
`GPS/IR
`
`GPS
`
`GulliversGenie
`Navitime
`Camineo
`Wigglestick
`MUMS
`GIMODIG
`MobileSeoulSearch
`Tellmaris
`TGH
`Ambiesense
`TouristGuide
`WebPark
`CRUMPET
`Lol@
`Hypergeo
`DeepMap
`Cooltown
`Guide
`Cyberguide
`
`AdaptivityPublication
`
`Usecase
`
`ContentrelevanceDelivery
`
`ArchitecturePresentation
`
`ApplicationPositioning
`
`ShortName
`
`Table2.Mobileguidesclassifiedbyusecaseanddelivery.
`
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`3.1. Classification by architecture and presentation
`
`Dividing the 34 mobile guides by system architecture produces three groups and two
`individual outliers. Since one of these groups consists of more than half the systems, this
`largest group was divided once more by presentation type into those systems using maps
`and those using video imagery. The result is four groups and two individual outliers.
`The largest group in this classification can be perhaps considered to contain the
`archetypal mobile guide: a GPS positioned, client-server solution with map presentation
`and pull information delivery in which the user selects the content and display on an
`ongoing basis. However, before client/server technology matured sufficiently for mobile
`solutions, CyberGuide, Guide and Deep Map all defined ad hoc architectures based on
`message-passing, object oriented software and distributed processing respectively.
`Hypergeo may have been the first system to use a mini web portal on the device extended
`to handle position, however, many subsequent mobile guides have implemented a wide
`variety of client-server approaches. The dominant approach to content relevance in this
`group is the ‘around me’ proximity filter: only Hypergeo and its descendents WebPark and
`Camineo have implemented other spatial filters such as ‘look ahead’ based on recent
`movement behaviour. The most advanced mobile guides now using this architecture
`(such as Navitime) are delivering location-based information across telecom networks to
`mobile phones with GPS and presenting situated VR models in real time. A final
`distinction that can be made in this category lies between the experimental systems such as
`Lol@, Crumpet and Tellmaris and the operational systems such as Ambiesense,
`GIMODIG, Camineo and Navitime, which are all in revenue earning service.
`The second group (also based on client/server architecture) is composed of systems
`delivering live augmented reality displays or location-based video to support tours or local
`discovery. MARS is the classic antecedent system that defined the system components and
`the augmented reality concept, though at the time (1997) a rucksack and headset was
`needed to use the system! Only five years later in 2002, the Museum Wearable consisted
`of a shoulder bag and spectacles, and by 2004 PEACH was delivering personalised video
`in a museum on a PDA.
`The third group of mobile guides in this classification are speech-oriented systems
`based on broadcast architectures, i.e. information is fed to the user in a stream after the
`task is defined. Some of these systems are authored tours or soundscapes delivered
`through mobile guides such as Sotto Voce or LISTEN, while others are speech-based
`navigation describers such as REAL and BPN.
`The fourth group defined in this classification are ‘event triggered’ systems that deliver
`information on demand, for example, when scanning a RFID tag or reaching a node in a
`tour. These systems are the least ‘adapting’ systems using Kru¨ ger’s classification as
`they can only respond in a pre-programmed way to the events. The increasing maturity
`of the collaboratively written Wikipedia has allowed Minotour and WikiEye to develop
`mobile guides based on the delivery of wiki entries at defined locations, though note that
`WikiEye is a tool to browse a map rather than real space.
`Two mobile guides are architectural outliers in this classification. The Taeneb City
`Guide would belong in the first group but for its method of caching all content on the
`device with update by periodic sync operations. However, MOBE is a unique approach
`to mobile guides based on the location-based triggering of downloadable applets to
`provide customised information in a city environment where there is pervasive wifi
`coverage.
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`Journal of Location Based Services
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`95
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`3.2. Classification by use case and delivery
`
`If the 34 mobile guides are divided by use case then three groups are formed consisting of
`mobile search, tour and navigation cases. However, the mobile search case is much larger
`than the others: if this group is sub-divided by delivery then two sub-groups defined by
`push and pull approaches are formed to make four groups in all. Notably,
`in this
`classification, the application areas closely approximate the use case groupings, as might
`be expected.
`The mobile search/pull group closely corresponds to the first group in the architecture
`and presentation classification and includes the classic early mobile guides such as
`CyberGuide and Hypergeo. This use case can be characterised as the ‘GIS-in-the-hand’
`approach in which many of the designers have seen their aim as to move existing GIS
`functionality off the desktop onto the mobile device. Only the more recent Wigglestick has
`come up with new concepts in this use case suggesting that the role of a mobile guide is to
`augment and filter rather than ‘map’ the environment. In this group, the Camineo mobile
`guide (the commercial successor to WebPark) is the only system to be running in a variety
`of different places with different content. Delivering Camineo mobile guides in cycle
`touring, open air museums and national parks has shown the importance of geospatial
`content management systems for mobile guides. This is, as yet, an under researched
`challenge in this field.
`The mobile search/push group can be characterised as ‘urban markup’ in which the
`mobile guide is the artefact that allows the user to browse the situated resources of the
`mobile web such as Wikipedia entries. There are differing architectural approaches to
`satisfying this use case such as the tag approach used by Ambiesense in which users get
`local content delivered by Bluetooth from installed mini servers or the downloadable
`applet approach of MOBE.
`Mobile guides are also widely used as tour guides, especially in museums and are
`predominantly push-oriented. This third group of systems is very diverse in architecture
`and positioning terms, as developers have searched for the best way to augment ‘the tour’
`with digital information. These systems are hard to compare as they mostly are only
`installed in one place, and only Minotour could be implemented anywhere with minimal
`customisation.
`The fourth group of navigation-focussed systems are generally the richer pedestrian
`equivalent of the personal navigation devices (PND) (also known as ‘satnav’) available for
`cars. The massive commercial success of PNDs in cars has depended to a great extent on
`the well-defined nature of the ‘driving use case’. The mobile guides in this group are
`examples of attempts to explore the pedestrian navigation use case: thus, BPN shows how
`the multimodal challenge can be met across driving and walking modes and GIMODIG
`shows how to deliver the right kind of map for the (outdoor leisure) activity being
`undertaken. However, Navitime is the undisputed leader in this group as it has almost
`2 million users in Japan across all of the major mobile phone networks, and is functionally
`advanced with deep integration with public transportation information and a virtual
`reality interface option.
`
`3.3. Mobile guide research agenda
`
`One of the deep challenges associated with the creation of mobile guides is that they need
`to be ‘invented’: there are no analogue equivalents of many of the digital artefacts that are
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`being created. This has placed a special focus on design and user needs studies, which have
`been conducted using ethnography, questionnaire approaches and formal requirements
`studies. The iPod-based maPodWalk (based on self-positioning) is an example of the kind
`of new forms of guide being considered (Arikawa et al. 2007b).
`Brown and Laurier (2005) carried out an ethnographic study of map use to help inform
`the design of electronic maps and guides finding that collaborative use, localisation and
`intentional wandering were not well supported by the systems that had been developed.
`Ruchter et al. (2005) compared map and mobile guide usage by different groups walking
`in a nature reserve, finding that although there were few differences in performance, the
`mobile guide strongly motivated children, while the electronic maps were rated poorer
`than their paper counterparts. Krug et al. (2003) carried out a questionnaire survey on
`the information needs of nearly 1600 national park visitors as the first stage in the
`development of the WebPark project, finding that 54% expressed an interest in the
`prospective system. Of those expressing an interest, 55–75% agreed that real time position-
`fixing, the location of key park attractions and safety information would be ‘very
`important’ or ‘important’ in the prospective system. Although this was a solid basis for
`launching a system, 35% said that a ‘virtual trail guide’ was not necessary. This survey
`shows the contradictions and challenges of a consumer audience: there is a desire to have
`access to information but not if the technology is a barrier. May et al. (2003) carried out a
`requirements analysis on the information desired by potential users of a pedestrian
`navigation system finding that 72% of the cues identified as important were landmarks
`(and not street names or distances). Zipf and Joest (2004) carried out a survey on (young)
`user expectations of LBS, finding inter alia that users prefer rotating maps to static ones
`and that users would walk a maximum of 300–400 m to find a point of interest on a mobile
`guide.
`Once a mobile guide has been built, a further challenge is to evaluate the system: in an
`important paper Kjeldskov et al. (2005 p. 52) undertook a comparative study of evaluation
`techniques as
`
`‘Mobile guides take many of the well-known methodological challenges of evaluating the
`usability of both stationary and mobile computer systems to an extreme’.
`
`The use of multiple forms of evaluation on the same system shows a high level
`of agreement between methods, though a video analysis with detailed log files and
`usability evaluation is regarded as the gold standard of evaluation. Klompmaker et al.
`(2007) have developed an immersive mobile guide testing platform using panoramic
`imagery, which supports Wizard-of-Oz evaluations.
`Though many mobile guides have now been created, there are a number of areas where
`research is still needed including:
`. Hardware adaptation, e.g. Norrie and Signer (2005) experimented with the use of
`digital paper as an interface to a mobile guide
`. New mixed reality interfaces and their effectiveness e.g. comparisons of map, AR
`and VR interfaces to the Camineo Guide by Mountain and Liarokapis (2007)
`. Development of the concepts of mobile guide ‘authorship’ e.g. Kjeldskov and
`Paay (2007) who suggested that mobile guide authorship could be organised
`around a set of metaphors
`. Incorporation of greater intelligence into the configuration of mobile guides, e.g.
`using agents (O’Grady et al. 2005)
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`. The creation of content collections and the integration of geospatial content
`management systems into mobile guides.
`. Incorporation of decision support into LBS as Ba¨ umer et al. (2007) have shown
`is desirable, for example, when trading off multiple criteria in the selection of
`a hotel
`
`While the research community has created dozens of mobile guides and commercialised
`a handful, the commercial sector have developed the PND market to reach millions of
`users by building hardware/software integrated navigation devices for drivers. At present
`these devices are highly focussed on a single navigation use case, however, these systems
`are slowly becoming more like mobile guides with points of interest, 3D viewing and
`mobile social networking. It can be anticipated that these systems will ‘cross over’ at some
`point, when the mobile guides can bring content relevance and adaptivity to PND, and the
`PND can bring routing to the pedestrian use case.
`
`4. Transport LBS
`
`Intelligent transport systems (ITS) are a developing technology vision for information
`integration among the wide range of organisations and services active in transport
`planning and operations. These systems are referred to as ‘intelligent’ because their
`capabilities allow them to perform higher order operations such as situational analysis and
`adaptive reasoning. The ongoing challenge is to build a transportation system of the future
`that will be more efficient, less polluting and safer with users who were better informed.
`In the last two decades, ITS have progressed from the creation of institutions like the
`Intelligent Transport Systems and Services for Europe (ERTICO) to the development of
`ITS architectures (Bossom 2000) and the implementation of standards such as ISO 14813
`(ISO 2007).
`The key technologies that can enable this ITS vision are many of the same technologies
`that underpin LBS in general: geopositioning, wireless communications, mobile computing
`platforms, and spatial databases. The term Telematics has often been used by the
`transportation sector to refer to these technologies and applications, even though the term
`has a broader remit. In this section, the focus will be on those vehicle-based products and
`services that may be considered synonymous with mainstream LBS. These applications
`will be termed transport LBS and include driver assistance, passenger information, vehicle
`management and vehicle-to-vehicle applications.
`
`4.1. Driver assistance
`
`In the last few years the huge growth of PND systems has brought LBS technology to the
`consumer marketplace. However, today’s PND systems are still limited to the navigation
`use case and there is still great potential for further development. Rizos and Drane (2004)
`presented a layered conceptual model of the Vehicle Navigation System (VNS) as follows:
`
`(1) The Electronic Street Directory (ESD) is the most rudimentary form of VNS and
`consists of a fixed in-vehicle screen or removable smartphone, PND or PDA, upon
`which map data can be panned and zoomed.
`(2) The Electronic Vehicle Locator (EVL) is an enhancement of the ESD, and permits
`the current vehicle’s location determined by GPS to be displayed.
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`(3) The Electronic Navigation Assistant (ENA) makes use of digital road map (DRM)
`data to aid the driver using enhanced geopositioning via map-matching, best-route
`calculation and point of interest querying.
`(4) The Server-assisted ENA (SENA) is the logical extension of the ENA, which can
`receive additional dynamic data such as congestion information via mobile data
`link and find the location of other drivers in a group.
`
`The geopositioning capabilities required by the EVL, ENA and SENA pose some
`special challenges as GPS suffers from lowered availability and reliability in urban
`environments due to obstruction of the satellite signals in urban canyons, tunnels and
`multi-storey car parks (Drane and Rizos 1997). Improving the availability and
`performance of GPS in such environments may involve:
`. Other signals-of-opportunity (e.g. digital TV, mobile telephony) in places where
`GPS reception will always be poor;
`. Addition of inertial measurement units with accelerometers, odometers and
`gyroscopes for tunnels;
`. Integration of other positioning infrastructures such as RFID.
`
`This work is part of a significant effort towards what is more generally referred to as
`‘Ubiquitous Positioning’ (Brzezinska 2004; Mok et al. 2006) which will be the foundation
`of further development of transport LBS for driver assistance.
`The SENA is now perhaps the defining example of the transport LBS for driver
`assistance. In fact the SENA concept, if carried to its natural conclusion, means that all of
`the services can be accessed from a very ‘thin’ mobile device in the vehicle. The SENA
`device need not even be permanently installed within a vehicle, and the various concierge
`and LBS can be offered to all mobile users, whether in a vehicle or not. All they require is
`a mobile device with the necessary geopositioning and wireless communication link
`services. R