376 research outputs found
Using an Educational IoT Lab Kit and Gamification for Energy Awareness in European Schools
The use of maker community tools and IoT technologies inside classrooms is
spreading in an increasing number of education and science fields. GAIA is a
European research project focused on achieving behavior change for
sustainability and energy awareness in schools. In this work, we report on how
a large IoT deployment in a number of educational buildings and real-world data
from this infrastructure, are utilized to support a "maker" lab kit activity
inside the classroom, together with a serious game. We also provide some
insights to the integration of these activities in the school curriculum, along
with a discussion on our feedback so far from a series of workshop activities
in a number of schools. Our initial results show strong acceptance by the
school community.Comment: This is the submitted preprint version of a paper published in the
FabLearn Europe'18 conferenc
Scenarios for Educational and Game Activities using Internet of Things Data
Raising awareness among young people and changing their behavior and habits concerning energy usage and the environment is key to achieving a sustainable planet. The goal to address the global climate problem requires informing the population on their roles in mitigation actions and adaptation of sustainable behaviors. Addressing climate change and achieve ambitious energy and climate targets requires a change in citizen behavior and consumption practices. IoT sensing and related scenario and practices, which address school children via discovery, gamification, and educational activities, are examined in this paper. Use of seawater sensors in STEM education, that has not previously been addressed, is included in these educational scenaria
Experiences from Using Gamification and IoT-based Educational Tools in High Schools towards Energy Savings
Raising awareness among young people, and especially students, on the
relevance of behavior change for achieving energy savings is increasingly being
considered as a key enabler towards long-term and cost-effective energy
efficiency policies. However, the way to successfully apply educational
interventions focused on such targets inside schools is still an open question.
In this paper, we present our approach for enabling IoT-based energy savings
and sustainability awareness lectures and promoting data-driven energy-saving
behaviors focused on a high school audience. We present our experiences toward
the successful application of sets of educational tools and software over a
real-world Internet of Things (IoT) deployment. We discuss the use of
gamification and competition as a very effective end-user engagement mechanism
for school audiences. We also present the design of an IoT-based hands-on lab
activity, integrated within a high school computer science curricula utilizing
IoT devices and data produced inside the school building, along with the
Node-RED platform. We describe the tools used, the organization of the
educational activities and related goals. We report on the experience carried
out in both directions in a high school in Italy and conclude by discussing the
results in terms of achieved energy savings within an observation period.Comment: to be presented at 2019 European Conference on Ambient Intelligenc
Internet of Everything in the Teaching-Learning Approach: An Integrative Review
Introduction: The fourth industrial revolution or industry 4.0 has brought a variety of technologies to different societies. One of these technologies is the Internet of Things (IoT), primarily conceptualized in engineering fields and then found its way to the field of education. Internet of Everything (IoE) has been discussed in the evolution of the IoT concept. IoE mainly focuses on things, people, processes, and data. This paper aims to investigate different studies from the emergence of IoT concept and its development to IoE based teaching-learning process.Methods: The integrative review was applied as the research method, Web of Science and Scopus databases were directly investigated and 139 articles were finalized as the result of this integrative review.Results: Findings of this study demonstrated that the teaching learning process with the focus on IoE could be categorized into logic models, including inputs, activities, outputs, outcomes, and external factors. Based on extracted components, the final model showed that the teaching-learning approach with the focus on IoE is a process that mainly occurs through integration and connection of IoT-based infrastructures, stakeholder’s interactions, teaching and learning activities. Eventually, this has brought personal and general outputs to achieve sustainability, Green IoT, and meeting the needs of industry. Simultaneously with the implementation or application of this system, several challenges can arise in the process, namely Security, Privacy, Financing, Reliable connectivity, and Cloud infrastructure.Conclusion: Therefore, this model can help policymakers or educators to be aware of the different parts of an IoE-based education system
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iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings
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
Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations
Recently, tremendous interest has been devoted to develop data fusion
strategies for energy efficiency in buildings, where various kinds of
information can be processed. However, applying the appropriate data fusion
strategy to design an efficient energy efficiency system is not
straightforward; it requires a priori knowledge of existing fusion strategies,
their applications and their properties. To this regard, seeking to provide the
energy research community with a better understanding of data fusion strategies
in building energy saving systems, their principles, advantages, and potential
applications, this paper proposes an extensive survey of existing data fusion
mechanisms deployed to reduce excessive consumption and promote sustainability.
We investigate their conceptualizations, advantages, challenges and drawbacks,
as well as performing a taxonomy of existing data fusion strategies and other
contributing factors. Following, a comprehensive comparison of the
state-of-the-art data fusion based energy efficiency frameworks is conducted
using various parameters, including data fusion level, data fusion techniques,
behavioral change influencer, behavioral change incentive, recorded data,
platform architecture, IoT technology and application scenario. Moreover, a
novel method for electrical appliance identification is proposed based on the
fusion of 2D local texture descriptors, where 1D power signals are transformed
into 2D space and treated as images. The empirical evaluation, conducted on
three real datasets, shows promising performance, in which up to 99.68%
accuracy and 99.52% F1 score have been attained. In addition, various open
research challenges and future orientations to improve data fusion based energy
efficiency ecosystems are explored
Mapping Participatory Sensing and Community-led Environmental Monitoring Initiatives: Making Sense H2020 CAPS Project
This report presents a summary of the state of the art in urban participatory sensing and community-led environmental monitoring, the types of engagement approaches typically followed, contextual examples of current developments in this field, and current challenges and opportunities for successful interventions. The goal is to better understand the field and possible options for reflection and action around it, in order to better inform future conceptual and practical developments inside and outside the Making Sense project.JRC.I.2-Foresight, Behavioural Insights and Design for Polic
GSGS'18 ::3rd Gamification & Serious Game Symposium : health and silver technologies, architecture and urbanism, economy and ecology, education and training, social and politics
The GSGS’18 conference is at the interface between industrial needs and original answers by highlighting the playful perspective to tackle technical, training, ecological, management and communication challenges. Bringing together the strengths of our country, this event provides a solid bridge between academia and industry through the intervention of more than 40 national and international actors. In parallel with the 53 presentations and demos, the public will be invited to participate actively through places of exchange and round tables
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