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

A trajectory-based recruitment strategy of social sensors for participatory sensing

Participatory sensing, a promising sensing paradigm, enables people to collect and share sensor data on phenomena of interest using mobile devices across many applications, such as smart transportation and air quality monitoring. This article presents a framework of participatory sensing and then focuses on a key technical challenge: developing a trajectory-based recruitment strategy of social sensors in order to enable service providers to identify well suited participants for data sensing based on temporal availability, trust, and energy. To devise a basic recruitment strategy, the Dynamic Tensor Analysis algorithm is initially adopted to learn the time-series tensor of trajectory so that the users' trajectory can be predicted. To guarantee reliable sensing data collection and communication, the trust and energy factors are taken into account jointly in our multi-objective recruitment strategy. In particular, friend-like social sensors are also defined to deal with an emergency during participatory sensing. An illustrative example and experiment are conducted on a university campus to evaluate and demonstrate the feasibility and extensibility of the proposed recruitment strategy

Data quality issues in environmental sensing with smartphones

This paper presents the results of a study about the performance and, consequently, challenges of using smartphones as data gatherers in mobile sensing campaigns to environmental monitoring. It is shown that there are currently a very large number of devices technologically enabled for tech-sensing with minimal interference of the users. On other hand, the newest devices seem to broke the sensor diversity trend, therefore making the approach of environmental sensing in the ubiquitous computing scope using smartphones sensors a more difficult task. This paper also reports on an experiment, emulating different common scenarios, to evaluate if the performance of environmental sensor-rich smartphones readings obtained in daily situations are reliable enough to enable useful collaborative sensing. The results obtained are promising for temperature measurements only when the smartphone is not being handled because the typical use of the device pollutes the measurements due to heat transfer and other hardware aspects. Also, we have found indicators of data quality issues on humidity sensors embedded in smartphones. The reported study can be useful as initial information about the behaviour of smartphones inner sensors for future crowdsensing application developers.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

CITIZEN SCIENCE FOR EARTH OBSERVATION: APPLICATIONS IN ENVIRONMENTAL MONITORING AND DISASTER RESPONSE

Citizen science is a promising way to increase temporal and spatial coverages of in-situ data, and to aid in data processing and analysis. In this paper, we present how citizen science can be used together with Earth observation, and demonstrate its value through three pilot projects focusing on forest biomass analysis, data management in emergencies and water quality monitoring. We also provide recommendations and ideas for follow-up activities. In the forest biomass analysis pilot, in the state of Durango (Mexico), local volunteers make in-situ forest inventory measurements with mobile devices. The collected data is combined with Landsat-8 imagery to derive forest biomass map of the area. The study area includes over 390 permanent sampling plots that will provide reference data for concept validation and verification. The emergency data management pilot focuses in the Philippines, in the areas affected by the typhoons Haiyan in November 2013 and Hagupit in December 2014. Data collected by emergency workers and citizens are combined with satellite data (Landsat-8, VHR if available) to intensify the disaster recovery activities and the coordination efforts. Simple processes for citizens, nongovernmental organisations and volunteers are developed to find and utilize up to date and freely available satellite imagery for coordination purposes and for building new not-for-profit services in disaster situations. In the water quality monitoring pilot, citizens around the Baltic Sea area contribute to the algae situation awareness by collecting algae observations using a mobile application. In-situ observations are compared with surface algal bloom products based on the satellite imagery, e.g. Aqua MODIS images with 500 meter resolution. As an outcome, the usability of the citizen observations together with satellite data in the algae monitoring will be evaluated

Environmental educational activities using data from the Internet of Things

Η ευαισθητοποίηση των νέων και η αλλαγή των συνηθειών τους όσον αφορά στην προστασία του περιβάλλοντος και την εξοικονόμηση ενέργειας, θα είναι καθοριστικής σημασίας για την διατήρηση ενός βιώσιμου πλανήτη στο εγγύς μέλλον. Σε αυτό το πλαίσιο, η αντιμετώπιση της κλιματικής αλλαγής απαιτεί αρχικά την ενημέρωση και κατόπιν την αλλαγή νοοτροπίας και εφαρμογή συμπεριφορών φιλικότερων προς το περιβάλλον. Σε αυτό το κείμενο, παρουσιάζουμε μερικές εκπαιδευτικές πρακτικές STEM που αξιοποιούν συστήματα Διαδικτύου των Αντικειμένων με αισθητήρες (Internet of Things, IoT), σε συνδυασμό με κατάλληλα σχεδιασμένες εκπαιδευτικές δραστηριότητες διερευνητικής μάθησης. Η ενίσχυση της εκπαιδευτικής κοινότητας στην περιβαλλοντική εκπαίδευση των νέων έχει πολλαπλασιαστικό αποτέλεσμα, καθώς η υιοθέτηση ενεργειακά αποδοτικών συνηθειών επηρεάζει και το άμεσο οικογενειακό τους περιβάλλον. Ως ένα τέτοιο παράδειγμα, η πλατφόρμα του έργου GAIA αξιοποιεί πραγματικά δεδομένα από σχολικά κτίρια, και μπορεί να χρησιμοποιηθεί ως βάση για τη σχεδίαση εκπαιδευτικών δραστηριοτήτων STEM, αντλώντας δεδομένα από διάφορα περιβάλλοντα. Επιπλέον, προτείνεται η χρήση αισθητήρων για τη μέτρηση βασικών ωκεανογραφικών παραμέτρων όπως η θερμοκρασία, η αλατότητα, το διαλυμένο οξυγόνο, η αλκαλικότητα και η θολερότητα σε παράκτια περιβάλλοντα, η οποία δεν έχει εξεταστεί  στο παρελθόν, ως ένα επόμενο βήμα για το σχεδιασμό εκπαιδευτικών σεναρίων αυτού του τύπου.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

THE LOOPER CO-CREATION METHODOLOGY: ENHANCING URBAN TRANSFORMATION THROUGH PARTICIPATORY SENSING AND URBAN LIVING LABS IN LEARNING LOOPS

My research aims to test how the participatory co-creation methodology can help to solve different urban issues, and wants to show some practicalities to organisers about how to set up a Urban Living Lab to involve stakeholders in a co-creation process. This research involved both the study of the state of the art, but also some practical work to experience which are the positive results and found criticalities. The study of the state of the art gave me a more complete comprehension of the situation in which my research is framed, and it included: the Scandinavian \u2018cooperative design\u2019 in the \u201860s; De Carlo participatory design of the Terni project; the concept of \u2018Participatory design\u2019 in the USA during the \u201870s; Siza and the SAAL process in the \u201870s; the \u2018User-centred design\u2019 concept by Donald Dorman in the \u201880s; the idea of \u2018Participatory budgeting\u2019 in Portugal from the 2000 on. The methodology has been that of \u2018practice-led\u2019. In my work, I applied the co-creation methodology in different urban environments to: check which practices can be considered good or bad; cross data collected from the state of the art and the field research; compare collected data. The research I have done focused on an European Research Project, funded under the JPI Urban Europe, called LOOPER (Learning Loops in the Public Realm) which applies the learning loop to the co-design process. A comparison background case was used as well: the planning of the City of Sports in San Don\ue0 di Piave (Italy). This research has the ambition of creating a new way of decision-making which brings together all stakeholders, including policymakers, that iteratively learn how to address urban challenges. This then results in an implemented co-design process since stakeholders in the end are called to evaluate what they have done. Future implementations of my research would allow the creation of a complete set of guidelines that can be used to solve different urban issues, by triggering the co-creation methodology applied within Urban Living Labs

Sobre a qualidade dos dados em sensoriamento de baixo custo para caracterização ambiental de espaços urbanos

Tese de Doutoramento (Programa Doutoral em Engenharia Eletrónica e de Computadores)This work investigates the quality of low – and ultra-low – cost sensors that may be applied in environmental monitoring campaigns in urban areas, given its nominal operation features. Sensors of temperature, humidity, atmospheric pressure, carbon monoxide, carbon dioxide and ozone were investigated, chosen from a selection of commercial models available, often used in the instrumentation of initiatives in operation. The climatic sensors were analysed under the conditions of a climatic controlled chamber where different situations for temperature and humidity were programmed. As results, it was observed that: most of the temperature sensors shown satisfactory performance; the humidity sensors have shown moderate performance; the pressure sensors shown good agreement between them, but it was observed that they suffer some interference from temperature, and it can be crucial to its accuracy when applied outdoors. The carbon dioxide sensors were evaluated by the comparison of their data with a reference instrument during indoors exposition to indoors concentrations and has shown good results, and some of them are ready for use. The carbon monoxide sensors have not shown conclusive results about its accuracy, but it has promising performance for configuration to lower concentrations. Ozone sensors did not provide conclusive results: either positive neither negative. In general terms, it can be concluded that climatic sensors can provide useful data if used carefully. Gas sensors, however, are much more critic, considering that its handling is not intuitive, and its readings, without treatment, presented limited quality.Este trabalho investiga a qualidade dos dados de sensores de baixo, e ultrabaixo custo que podem ser utilizados em campanhas de monitoramento ambiental para áreas urbanas, dadas as suas características nominais de operação. Foram investigados sensores de temperatura, humidade, pressão atmosférica, monóxido de carbono, dióxido de carbono e ozono, escolhidos a partir de uma triagem de modelos comerciais disponíveis, utilizados na instrumentação de iniciativas em funcionamento. Os sensores – então chamados de – climáticos foram analisados sob as condições de uma câmara de ambiente controlado, onde foi possível programar condições específicas de temperatura e humidade. O resultado da avaliação destes sensores foram: satisfatórios para maior parte dos sensores de temperatura; os de humidade apresentaram desempenho moderado; os sensores de pressão apresentaram boa concordância em condições ambientais específicas, sugerindo que as condições climáticas podem interferir na exatidão destes sensores. Os sensores de CO2 foram avaliados pela comparação com um instrumento de referência enquanto mediam concentrações em ambiente interior e apresentaram bons resultados. Os sensores de monóxido de carbono, apesar da necessidade de resultados mais conclusivos, demonstraram ser promissores para sensoriamento de baixas concentrações. Da avaliação dos sensores de ozono não se obtiveram resultados significativos que permitissem concluir sobre a qualidade dos dados por si fornecidos. Em termos gerais, conclui-se que os sensores climáticos são capazes de fornecer dados úteis, desde que sejam utilizados com cuidado. Os sensores de gases, por sua vez, são consideravelmente mais críticos, uma vez que seu manuseio não é intuitivo e suas leituras, sem tratamento, apresentaram uma qualidade limitada