A Gamified Flexible Transportation Service for On-Demand Public Transport

Drakoulis, Richardos; Bellotti, Francesco; Bakas, Ioannis; Berta, Riccardo; Paranthaman, Pratheep Kumar; Dange, Gautam Ravindra; Lytrivis, Panagiotis; Paglé, Katia; Gloria, Alessandro De; Amditis, Angelos

doi:10.1109/tits.2018.2791643

Cited by 32 publications

(11 citation statements)

References 31 publications

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“…Real-world input has also been utilized to gamify real-world processes [16]. The empirical effects of a number of serious games in changing knowledge, behavior and attitude towards energy-saving have been positive [17], with reported energy savings in the range of 3-6% on average and >10% achievable on a number of studies featuring the application of gamification to reduce energy consumption [18].…”

Section: Gamification For Energy Conservationmentioning

confidence: 99%

Employee Profiles and Preferences towards IoT-enabled Gamification for Energy Conservation

Kotsopoulos

Bardaki

Lounis

et al. 2018

IJSG

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Section: Gamification For Energy Conservationmentioning

confidence: 99%

Employee Profiles and Preferences towards IoT-enabled Gamification for Energy Conservation

Kotsopoulos

Bardaki

Lounis

et al. 2018

IJSG

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“…We nevertheless believe that the area of Serious Games, or more in general of "gamification", should be the path forward. Serious Games are games that not only focus on pure diversion but that also take advantage of the potential of game technology and game mechanics for learning and training [46], [47]. The general objective here is to reward proper user behavior through virtual and/or realworld incentives.…”

Section: Vsn System Modelmentioning

confidence: 99%

Data Transmissions Using Hub Nodes in Vehicular Social Networks

Vegni

Souza

Loscrì

et al. 2020

IEEE Trans. on Mobile Comput.

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…Reality-enhanced serious games (RESGs) is an emerging game genre, spurred also by the spread of the Internet of Things (IoT) [1], in which a player's progress is not only due to his or her digital gaming ability, but also tied to measurements from the field [2,3]. In this way, a user's performance in the field becomes an immediate gaming factor [2].…”

Section: Introductionmentioning

confidence: 99%

IoT Sensing for Reality-Enhanced Serious Games, a Fuel-Efficient Drive Use Case

Massoud

Berta

Poslad

et al. 2021

Sensors

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Internet of Things technologies are spurring new types of instructional games, namely reality-enhanced serious games (RESGs), that support training directly in the field. This paper investigates a key feature of RESGs, i.e., user performance evaluation using real data, and studies an application of RESGs for promoting fuel-efficient driving, using fuel consumption as an indicator of driver performance. In particular, we propose a reference model for supporting a novel smart sensing dataflow involving the combination of two modules, based on machine learning, to be employed in RESGs in parallel and in real-time. The first module concerns quantitative performance assessment, while the second one targets verbal recommendation. For the assessment module, we compared the performance of three well-established machine learning algorithms: support vector regression, random forest and artificial neural networks. The experiments show that random forest achieves a slightly better performance assessment correlation than the others but requires a higher inference time. The instant recommendation module, implemented using fuzzy logic, triggers advice when inefficient driving patterns are detected. The dataflow has been tested with data from the enviroCar public dataset, exploiting on board diagnostic II (OBD II) standard vehicular interface information. The data covers various driving environments and vehicle models, which makes the system robust for real-world conditions. The results show the feasibility and effectiveness of the proposed approach, attaining a high estimation correlation (R2 = 0.99, with random forest) and punctual verbal feedback to the driver. An important word of caution concerns users’ privacy, as the modules rely on sensitive personal data, and provide information that by no means should be misused.

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A Gamified Flexible Transportation Service for On-Demand Public Transport

Cited by 32 publications

References 31 publications

Employee Profiles and Preferences towards IoT-enabled Gamification for Energy Conservation

Employee Profiles and Preferences towards IoT-enabled Gamification for Energy Conservation

Data Transmissions Using Hub Nodes in Vehicular Social Networks

IoT Sensing for Reality-Enhanced Serious Games, a Fuel-Efficient Drive Use Case

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