Scenarios for Educational and Game Activities using Internet of Things Data

Tziortzioti, Chrysanthi; Mavrommati, Irene; Mylonas, Georgios; Vitaletti, Andrea; Chatzigiannakis, Ioannis

doi:10.1109/cig.2018.8490370

Cited by 7 publications

(6 citation statements)

References 27 publications

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“…Later, they [55] developed an approach which utilizes the information provided by IoT devices to monitor individual occupants' energyuse behaviors in commercial buildings. Mylonas et al [56], Paganelli et al [57], and Tziortzioti et al [113] demonstrated how IoT along with gamification (i.e., interactive services, games, and web applications for occupants to increase their overall awareness) can be utilized to promote energyaware behaviors and getting occupants engaged into energy-efficient activities. In addition, research projects such as Green-Awareness-In-Action (gaia-project.eu), Personal-Energy- Motivated by this, we propose iSEA which is an IoT-based personalized feedback mechanism.…”

Section: Iot-based Occupancy Sensing and Energy-use Monitoring In Commercial Buildingsmentioning

confidence: 99%

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

2020

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Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants.Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings.iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants' EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs.

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Section: Iot-based Occupancy Sensing and Energy-use Monitoring In Commercial Buildingsmentioning

confidence: 99%

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

2020

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Section: Introductionmentioning

confidence: 99%

“…Edugame(educational game), very interesting to develop [10][11][12][13][14][15]. Because by playing educational games on any platform, they will indirectly learn something knowledge in the form of a game [11,13]. In this game, the game agent (intelligent agent) will give action-reaction, observe, and act on a condition so that it looks like itself.…”

Section: Introductionmentioning

confidence: 99%

Development Finite State Machine Agent in Edugame "Hangug Word" Learning Media of Korea Hangul Letters

Nursobah

Andrea

Kurniawan

2021

mib

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Development the edugame "Hangug Word", learning media of to Korean Hangul letters with game Agent Finite State Machine based on Android. The application used in making the game is Swish max4. In this game, a game agent character is given. In the game agent using the Finite State Machine (FSM) method, the Game Agent will notify the players if they answer incorrectly or correctly in the game. The Finite State Machine method of designing a control system that describes the working principle of the system using three things: state, event, action used in the game agent can provide action and reaction to players when the game is played. The results of making this edugame are .Apk and .Swf which can be run on an Android smartphone.

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“…Drawing from human-computer interaction, psychology, sociology, several efforts have been made to achieve behaviour change concerning energy usage, through gamification, i.e., the introduction of game elements in everyday environmental behaviours [17]. In the aquatic enviroments, ealy attempts followed a crowdsourcing approach to collect data based on portable sensor devices developed within the Maker Movement approach [19], [33], [35].…”

Section: Introductionmentioning

confidence: 99%

Using IoT Data-Driven Analysis of Water Consumption to support Design for Sustainable Behaviour during the COVID-19 Pandemic

Zecchini

Griesi

Chatzigiannakis

et al. 2021

2021 6th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM

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Aquatic environments are cornerstone for the existence of life, while water scarcity and unsafe water supply are major global issues affecting citizens [37]. Recently, the deployment of Internet of Things over water distribution networks has indicated ways to address some of these issues. Yet, policies for sustainable and efficient use of the aquatic resources depend largely on citizen's engagement.The use of data arriving from water metering and water quality sensors in educational environments as a mean to educate citizens and inspire environmental friendly behaviours has not been studied throughly in the past, mainly due to the lack of real-world data. Towards this end, real-world data collected by smart water meters can become a powerful tool to bridge digital and physical environments to support design for sustainable behaviour. A data-driven approach is adopted here that evaluates the effect of human actions related to the consumption of water within an educational setting. The data used in this study is collected from a pilot deployment of a 24 months period and is analyzed on weekly, daily and hourly basis to identify usage patterns. The examined period also includes the restrictions imposed by the local authorities as a response to the COVID-19 emergency taking place during the first quarter of 2020. The evaluation of water consumption before, during and after the lockdown period highlights the impact of human actions within the educational environment. The paper investigates how to design educational activities for sustainable behaviour based on the analysis of the data collected from the smart water grid.

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Scenarios for Educational and Game Activities using Internet of Things Data

Cited by 7 publications

References 27 publications

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

Development Finite State Machine Agent in Edugame "Hangug Word" Learning Media of Korea Hangul Letters

Using IoT Data-Driven Analysis of Water Consumption to support Design for Sustainable Behaviour during the COVID-19 Pandemic

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