On Metrics for Location-Aware Games

Rodríguez-Pupo, Luis E.; Casteleyn, Sven; Granell, Carlos

doi:10.3390/ijgi6100299

Cited by 8 publications

(9 citation statements)

References 52 publications

(81 reference statements)

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“…The analytics platform for computing spatio-temporal metrics presented here grew out of our previous work in location-aware games, a specific class of location-based applications [31]. Rodríguez-Pupo et al [32] analysed existing game analytic platforms to assess their level of support of spatio-temporal features for analytic processes. Results suggested that little support is currently available, and existing solutions lack generality and re-usability.…”

Section: Architectural View Of the Analytics Platformmentioning

confidence: 99%

“…In video-games, metrics are must-have tools for game developers and designers to monitor aspects of the game (e.g., game mechanics, strategies, user interface, player behaviour) and consequently make informed decisions to improve overall gameplay experience [43]. Specifically in location-aware games, the role of spatio-temporal metrics is as important as other metrics [32], and more generally, in locationand context-aware applications, spatio-temporal metrics can help developers to quantify and better understand the phenomena and dynamics that occur in real-world applications [44,45].…”

Section: Conceptual Model Of Spatio-temporal Metricsmentioning

confidence: 99%

“…Notification is another type of supported action. Using simple reactive rules (if-then rules), users can specify when an action is triggered [32]. For example, a user gets notified only if the output is greater than a given threshold.…”

Section: Actionsmentioning

confidence: 99%

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An Analytics Platform for Integrating and Computing Spatio-Temporal Metrics

Rodríguez-Pupo

Granell

Casteleyn

2019

IJGI

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In large-scale context-aware applications, a central design concern is capturing, managing and acting upon location and context data. The ability to understand the collected data and define meaningful contextual events, based on one or more incoming (contextual) data streams, both for a single and multiple users, is hereby critical for applications to exhibit location-and context-aware behaviour. In this article, we describe a context-aware, data-intensive metrics platform -focusing primarily on its geospatial support-that allows exactly this: to define and execute metrics, which capture meaningful spatio-temporal and contextual events relevant for the application realm. The platform (1) supports metrics definition and execution; (2) provides facilities for real-time, in-application actions upon metrics execution results; (3) allows post-hoc analysis and visualisation of collected data and results. It hereby offers contextual and geospatial data management and analytics as a service, and allow context-aware application developers to focus on their core application logic. We explain the core platform and its ecosystem of supporting applications and tools, elaborate the most important conceptual features, and discuss implementation realised through a distributed, micro-service based cloud architecture. Finally, we highlight possible application fields, and present a real-world case study in the realm of psychological health. IntroductionNotwithstanding the early promise of location-and context-aware applications (see e.g., [1] for a survey of early systems), only in the last decade have we witnessed the required technological and infrastructural enablers to truly unleash their potential [2,3]. For the technological enablers, the increasing availability of a variety of context-capturing machinery, in which embedded sensors, local processing and communication capabilities are combined, allows for large-scale, high-volume capturing and streaming of a broad variety of context data. Examples notably include sensor-packed smart vehicles, mobile hand-held devices (e.g., smart phones, tables) and smart, wearable devices (e.g., smart watches and bracelets, sport trackers, smart clothing), which can effectively collect an individual's real-time location, along with other relevant contextual information (e.g., [4]). A second technological milestone is the rapid evolution and proliferation of powerful mobile hand-held computing devices, a condition sine qua non to run full-fledged, context-aware applications [5].On the other hand, infrastructure-related enablers are now in place: fully rolled-out communication networks (e.g., 3G and 4G) with resulting ubiquitous internet access, and commercially available, economised cloud-based storage and computing infrastructures [6], provide unprecedented means to build the next-generation of context-aware applications and services, based on multi-user, real-time and high-frequency input streams; real-time data handling, processing and analytics; and real-time, location-and context-based r...

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Section: Architectural View Of the Analytics Platformmentioning

confidence: 99%

Section: Conceptual Model Of Spatio-temporal Metricsmentioning

confidence: 99%

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An Analytics Platform for Integrating and Computing Spatio-Temporal Metrics

Rodríguez-Pupo

Granell

Casteleyn

2019

IJGI

Self Cite

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“…The authors proposed storing the location of each 'Thing' and other geographic-related features such as orientation, size, and shape. However, the ability to handle and analyze the location of Things in near real time is still limited with existing analytical platforms, despite its opportunities(McCullough et al 2011;Rodríguez-Pupo et al 2017).…”

mentioning

confidence: 99%

Internet of Things

Granell

Kamilaris

Kotsev

et al. 2019

Manual of Digital Earth

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Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things (IoT) emerged as a holistic proposal to enable an ecosystem of varied, heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today's pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth. Keywords Internet of Things • Geospatial standards • Smart scenarios The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission.

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“…Ahlqvist & Schlieder [241] completed an in-depth analysis in the realm of geogames or location-aware games [242] to align existing theories of core geographic concepts in the GIScience field, namely Kuhn [243], Kuhn & Ballatore [244], and Janelle & Goodchild [245], to location-based game patterns such as exploring, collecting objects, co-locality, and spatial structure [246]. The authors propose a unified set of core geographic concepts and compare them to existing spatial game patterns [246], which resulted in two main groups of spatial patterns: locality and proximity.…”

Section: Contextmentioning

confidence: 99%

Analysis and Development of a Platform for Generating Context-Aware Apps for Mental Health

Tena¹

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This work gathers a research carried out on the use of context-aware technologies in their application to the field of mental health. It begins by performing a deep state of the art of mobile technologies used in psychological interventions and extracting the characteristics and disorders most discussed in the literature; It continues to propose a series of considerations to take into account in the development of this type of technologies to increase its chances of success, focusing on three areas of study: Context, Mental Health and the Technology itself; The next contribution is the process of developing a platform that allows therapists to create their own mobile applications with geolocation to customize their own intervention tools without the need for high technical knowledge, the development is based on the learning obtained in the first two contributions, it is described as an intervention example a hypothetical case of depression; Finally, the platform is validated with three patients suffering from two different disorders: Panic disorder and agoraphobia; and gambling disorder.

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On Metrics for Location-Aware Games

Cited by 8 publications

References 52 publications

An Analytics Platform for Integrating and Computing Spatio-Temporal Metrics

An Analytics Platform for Integrating and Computing Spatio-Temporal Metrics

Internet of Things

Analysis and Development of a Platform for Generating Context-Aware Apps for Mental Health

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