open, digital, online, education, distance education

Environmental educational activities using data from the Internet of Things


Published: Nov 26, 2018
Keywords:
ΙοΤ sensors educational scenarios environmental awareness energy efficiency education
Χρυσάνθη Τζιωρτζιώτη
https://orcid.org/0000-0001-9652-6063
Ειρήνη Μαυρομμάτη
https://orcid.org/0000-0002-8870-746X
Γεώργιος Μυλωνάς
https://orcid.org/0000-0003-2128-720X
Ιωάννης Χατζηγιαννάκης
https://orcid.org/0000-0001-8955-9270
Abstract
Raising awareness among young people and changing their behavior and habits concerning energy usage and the environment is key to achieving a sustainable planet. Promoting sustainable behavior at school impacts the home behavior, as children communicate their newly acquired knowledge to parents.  In this context, reinforcing the educational community on educating new generations potentially has a multiplier effect for reducing our environmental footprint.  IoT sensing and related scenario and practices, which engage school children via discovery and educational activities, focusing on encouraging sustainability of energy and natural resources, are examined in this paper. As an example of such an approach, the GAIA platform can act as the basis for scenarios utilizing real world data for educational activities that encourage energy efficient behavior. In addition, the use of seawater sensors in STEM education, that has been realized in very few cases, is proposed as educational scenarios utilizing real-world data that are worth exploring.  The GAIA platform (Mylonas et al, Amaxilatis et al, 2017) is one of a number of recent IoT systems that focus on the educational community. A real-world IoT deployment is spread in 3 countries (Greece, Italy, Sweden), monitoring in real time 18 school buildings in terms of electricity consumption and indoor/outdoor environmental conditions. The data collected is used as input in educational scenarios, whose goal is to educate and attempt to transform the behavior of students through a series of trials conducted in the educational environment. Feedback mechanisms inform the students and teachers on current energy consumption at school; in this way, they assist towards raising awareness regarding environmental effects of energy spending and promote energy literacy among students.  GAIA (Mylonas et al, Nov. 2017) is based on the assumption that continuous monitoring of the power consumption-related behavior of students can positively contribute towards energy savings. Since the IoT deployment is multi-site and multicountry can motivate, e.g., to identify energy consumption patterns in different countries and across different climate zones. This can be used to draw comparisons or kickstart competitions; for instance, students of school A can compete with students of school B in terms of energy efficiency. This could also help to better understand cultural differences with respect to energy efficiency awareness and sustainability. The devices deployed provide 880 sensing points organized in four main categories: (1) classroom environmental comfort sensors (devices within classrooms); (2) atmospheric sensors (devices positioned outdoors); (3) weather stations (devices positioned on rooftops); and (4) power consumption meters (devices attached to the main breakout box of the buildings, measuring energy consumption). The IoT deployments vary significantly from school to school (e.g., in number of sensors, hardware manufacturer, networking technology, communication protocols for delivering sensor data, etc.). The IoT devices used are either open-source hardware IoT nodes (based on the Arduino popular electronics prototyping platform, Pocero et al, 2017) or off-the-shelf products, acquired from IoT device manufacturers.  The platform also incorporates participatory sensing technologies for periodical collection of energy usage to acquire information in buildings where no IoT sensing elements are available, e.g., utilizing web/smartphone/social networking applications for acquiring information on room occupancy, usage of conditioning or special machinery, opening of windows, etc. The goal of GAIA is to include the users in the loop of monitoring the energy consumption in the buildings they use daily, thus making the first steps towards raising awareness, connecting the educational activities carried out at schools with their activities at their home environment and also engaging the parents and relatives at home. The teachers can initiate participatory sensing sessions during the courses, so that students can use phones and tablets to gather data in real time and then review them in class, as part of an educational activity. Bringing IoT into the sea: Most IoT related research focuses on terrestrial applications. Even when offshore infrastructures or vessels are considered, IoT devices are mostly deployed in “dry” surfaces and only some specific transducers are actually deployed into the water. The underwater environment is hostile, and consequently underwater IoT devices are very expensive. If you only consider a reliable water-proof housing for shallow water, it costs at least 2 orders of magnitude more than the respective terrestrial solutions, or even more in the case of deep water scenarios. Underwater operations are complex and challenging. As an example, the fast growth of algae or microorganisms can rapidly affect the quality of sensors readings that have to be often cleaned up. In addition, underwater communications are still extremely difficult and energy hungry; RF propagates only at a few centimeters and only acoustic or optical communications can be used for longer distances. The energy cost of underwater communications strongly limits the device lifetime that is usually in the order of few months at best and requires frequent replacements of the batteries, a time and resource-consuming task. Finally, communication standards are emerging only in the last years. Due to these reasons, the availability of underwater IoT data is still very limited. One of the few attempts to provide a federation of underwater testbeds for the Internet of Underwater Things is the EU project SUNRISE (SUNRISE Project website). While SUNRISE clearly showed us the potential of exploring underwater data, it was not originally conceived for STEM educational activities, and both the complexity of the tools and the costs of the equipment are not yet suitable to be operated by students. Despite these difficulties, there are already some efforts for more affordable tools for underwater investigations (Baichtal, 2015) (OpenROV website) (The Cave Pearl Project website) and is, however, possible to design significant STEM activities that focus on shallow water and/or surface sampling that significantly lower the above discussed difficulties. Indeed, the focus on the shallow water and/or the sea surface allow us to a) engage students in participatory sampling (i.e., they are directly involved in the sampling procedure at sea), b) deploy relatively simple networking infrastructures capable to deliver the data acquired by possible underwater transducers.  In the latter case, the transducers can be placed underwater and the collected data are delivered by a cable to a wireless device on the surface that makes them available on the cloud. In order to achieve better use of the potential of the sea and protect it at the same time, more detailed studies are still required (Green Paper Marine Knowledge 2020, 2012). In this paper, we propose a set of educational scenarios, whereby sensors are used to measure physical and chemical marine parameters. Bringing the IoT into the sea is still very difficult, therefore the focus of these scenarios is on surface sampling activities that are more affordable in the context of STEM educational activities.  The steps of the pedagogical activities followed are: awareness, observation, experimentation and action. School students located in Europe's coastal areas use portable equipment to carry out relevant measurements and submit them to a database they have access to. Depending on the teaching needs and priorities, students can collect and analyze the following:  real-time values and any fluctuations of them during the observation period of the activity,   changing values for longer periods of time, e.g., making comparisons between different times of the day, between months, seasons, or years,  variance of the phenomena between different areas. The mathematical and scientific thinking developed in the above process can be exploited in various ways by tutors, in the context of teaching mathematical and other science skills, not only during science courses but also in cross-thematic approaches that combine such observations and analyze the economic, social and other aspects of our efforts for clean seas. Discussion: During spring 2017, a set of preliminary GAIA testing was conducted over several weeks to get feedback regarding the educational scenarios that promote energy efficiency and sustainability. Several hundreds of students and teachers had a first interaction with the GAIA platform, while a form-based survey was conducted focusing on the gamification component. 78% of the students found the content of its gamification component interesting, and an 89% found the activity user-friendly. Regarding the acceptance of the tools from educators, the direct response gathered through a set of workshops, addressed specifically at educators, has been positive and several schools have provided their own proposals for schedules to integrating GAIA 

tools in their curriculum. Thus, in terms of overall acceptance of both the tools and the infrastructure inside buildings and the schools’ curricula, these results indicate that GAIA’s educational scenarios had a quite positive initial response. In addition to the GAIA platform that facilitates educational activities and scenarios for energy awareness and environmental sustainability utilizing real data from IoT sensors, we present here a number of alternative scenarios utilizing different data sets. Marine water scenarios remain an undiscovered but challenging territory that remains unexplored in STEM education. IoT platforms such as GAIA can facilitate educational scenarios towards the sustainability of the environment, based on understanding the implications of real world data.

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References
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