Proceedings of the Conference on Information Technology for Social Good最新文献

{"title":"Jammo Virtual Robot Enhances the Social Skills of Children With HFA: Development and Deployment","authors":"Maha Abdelmohsen, Y. Arafa","doi":"10.1145/3462203.3475928","DOIUrl":"https://doi.org/10.1145/3462203.3475928","url":null,"abstract":"This study investigates the impact of combining virtual environment with a social VRobot as a novel approach to train the social skills of children with high-functioning autism (HFA). A 3D social virtual robot is used in a non-immersive (desktop) virtual environment to enhance the social skills of children with HFA through a social skills training program guided by a parent or a teacher. The motivation of this research is to provide a tool that can be widely accessible, cheap, and easily used by parents and teachers either at home or school. The training program targets three social skills: imitation, emotion recognition, and expression, and intransitive gestures skills. Experimental sessions were conducted with 15 children with HFA (4-12 years) both online and on-site. The participants were taught to recognize six basic emotions and 11 intransitive gestures (Phase I), to imitate these emotions and gestures (Phase II), and to produce them inappropriate social contexts (Phase III). Across all the three phases for each skill, significant differences were found between the pre-test, post-test, and follow-up test results.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115259473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disseminating Data using LoRa and Epidemic Forwarding in Disaster Rescue Operations","authors":"Yamani Dalpathadu, Thumma Showry, Vishnupriya Kuppusamy, A. Udugama, Anna Förster","doi":"10.1145/3462203.3475917","DOIUrl":"https://doi.org/10.1145/3462203.3475917","url":null,"abstract":"In the wake of a disaster, when all communication infrastructure has been damaged, it is critical to find a way to maintain communications to disseminate critical information collected by the rescuers. Even though many proposals and systems have surfaced, the critical drawback found in these systems is the communication range. Here we propose a solution for communication in post-disaster rescue operations based on LoRa, a long-range, low power technology. Using the concepts of Opportunistic Networks, we employ the epidemic forwarding protocol to disseminate data between the rescuers as well as other external parties. In this work, we present our solution, the implementation in a commercially available LoRa platform, built an experimental setup, identified a set of test cases, and evaluated the performance based on these test cases. Based on the initial results, we show that our proposal is a viable solution to be used by rescuers. We intend to work further on this solution to improve it by identifying optimum configurations for its best performance in realistic post-disaster rescue operations.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122537117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Handling of Labeling Uncertainty in Smart Homes using Generalizable Fuzzy Features","authors":"Cédric Demongivert, K. Bouchard, S. Gaboury, M. Lussier, Hubert Kenfack Ngankam, M. Couture, N. Bier, S. Giroux","doi":"10.1145/3462203.3475909","DOIUrl":"https://doi.org/10.1145/3462203.3475909","url":null,"abstract":"Smart homes research is now entering a phase of real deployment and of early commercialization. For the type of smart homes used to monitor the daily life of residents, activity recognition is one of the key artificial intelligence components necessary. In labs, it is mostly based on machine learning methods, but in real deployments, due to the difficulty to build labeled datasets, it still usually depends largely on logical systems and inference rules. In this work, we try to leverage generalizable fuzzy features to evaluate the quality of the label inferred by commonsense inference. The fuzzy rules are built from annotated instances in CASAS's dataset and by transferring them to our own infrastructure. The data exploited include 11 of our deployed smart homes and shows promising results. Our experiments shows that it is likely possible to exploit those rules to evaluate the quality of our data labeling.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131295929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IoT & AI Based System for Fish Farming: Case study of Benin","authors":"B. Agossou, Takahara Toshiro","doi":"10.1145/3462203.3475873","DOIUrl":"https://doi.org/10.1145/3462203.3475873","url":null,"abstract":"Agriculture including aquaculture has been changing through multiple technological transformations in recent years. The Internet of Things (IoT) and Artificial Intelligence (AI) are providing remarkable technological innovations on fish farming. In this research, we present an automated IoT and AI-based system to improve fish farming. The proposed system uses multiple sensors to measure in real-time water quality chemical parameters such as: temperature, pH, turbidity, electrical conductivity, total dissolved solids, etc., from the fish pond and send them on a cloud database to allow fish farmers to access them in realtime with their devices (mobile phone, PC, tablets). The system contains three web applications which fish farmers can use. The first web application enables farmers with realtime visualizations of sensors data, issues alerts and remote pumps controls. Fish farmers can use the second web application for fish disease detection and to receive suggestions for diseases' care. This would help to classify two fish diseases which are: Epizootic Ulcerative Syndrome(EUS), and Ichthyophthirus(Ich). The third web application is a digital community platform for knowledge sharing, capacity building, market opportunities and collaboration among fish farmers. Our system can help reduce human efforts, reinforce capacity building, increase fish production and market opportunities for fish farmers.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114890213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coronabot: A Conversational AI System for Tackling Misinformation","authors":"Nancie Gunson, Weronika Maria Sieińska, Yanchao Yu, Daniel Hernández García, Jose L. Part, C. Dondrup, Oliver Lemon","doi":"10.1145/3462203.3475874","DOIUrl":"https://doi.org/10.1145/3462203.3475874","url":null,"abstract":"Covid-19 has brought with it an onslaught of information for the public, some true and some false, across virtually every platform. For an individual, the task of sifting through the deluge for reliable, accurate facts is significant and potentially off-putting. This matters since fundamentally, containment of the pandemic relies on individuals' compliance with public health measures and their understanding of the need for them, and any barrier to this, including misinformation, can have profoundly negative effects. In this paper we present a conversational AI system which tackles misinformation using a two-pronged approach: firstly, by giving users easy, Natural Language access via speech or text to concise, reliable information synthesised from multiple authoritative sources; and secondly, by directly rebutting commonly circulated myths surrounding coronavirus. The initial system is targeted at staff and students of a University, but has the potential for wide applicability. In tests of the system's Natural Language Understanding (NLU) we achieve an F1-score of 0.906. We also discuss current research challenges in the area of conversational Natural Language interfaces for health information.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116282704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-Driven Time Series Forecasting for Social Studies Using Spatio-Temporal Graph Neural Networks","authors":"Yifan Li, Bo Dong, L. Khan, B. Thuraisingham, Patrick T. Brandt, Vito D'Orazio","doi":"10.1145/3462203.3475929","DOIUrl":"https://doi.org/10.1145/3462203.3475929","url":null,"abstract":"Time series forecasting with additional spatial information has attracted a tremendous amount of attention in recent research, due to its importance in various real-world applications on social studies, such as conflict prediction and pandemic forecasting. Conventional machine learning methods either consider temporal dependencies only, or treat spatial and temporal relations as two separate autoregressive models, namely, space-time autoregressive models. Such methods suffer when it comes to long-term forecasting or predictions for large-scale areas, due to the high nonlinearity and complexity of spatio-temporal data. In this paper, we propose to address these challenges using spatio-temporal graph neural networks. Empirical results on Violence Early Warning System (ViEWS) dataset and U.S. Covid-19 dataset indicate that our method significantly improved performance over the baseline approaches.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124768632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Connectivity Management in an Integrated Heterogeneous Social Networks Framework in Vehicular Environments","authors":"H. Minh, A. Vegni, V. Loscrí, A. Benslimane","doi":"10.1145/3462203.3475899","DOIUrl":"https://doi.org/10.1145/3462203.3475899","url":null,"abstract":"In the last decade, Online Social Networks (OSNs) have emerged as one of the most disruptive communication platforms with high socio-economic value, used every day by billions of users to connect with friends, colleagues, and any other user with social ties and common interests. Social features are pervasively penetrating in our daily life not only by means of OSNs, but also in other contexts, such as that of vehicular ad-hoc networks. Vehicular Social Networks (VSNs) are enhanced with social features that impact not only on societal services, but especially on connectivity and communication performance. As a result, the coexistence of both OSNs and VSNs can represent a benefit for both two domains, allowing the creation of a unique network framework for connectivity maintenance. This paper presents a connectivity management technique in a heterogeneous network framework, namely SOLVER, comprised of both OSN and VSN communities for data exchange among nodes belonging to different networks. Connectivity switching is allowed in case of expected connectivity loss, as well as degradation of network performance. Results assess the effectiveness of SOLVER framework as compared to traditional Client-Server and Peer-to-Peer architectural modes.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123828694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Inter-Regional Tourism in the Spread of COVID-19 in Italy during the 2020 Summer: A Confirmatory Study","authors":"M. Roccetti, Luca Casini","doi":"10.1145/3462203.3475888","DOIUrl":"https://doi.org/10.1145/3462203.3475888","url":null,"abstract":"Going into 2021 many European countries have faced subsequent strong waves of COVID-19 infections that forced governments to reestablish many of the restrictions imposed in the 2020 spring, after a period of relative calm in the summer when the pandemic seemed to be under control. Here, we examine the period prior to the resurgence of the pandemic in autumn, following the interregional mobility due to Italian tourism. Further to a preliminary analysis, we investigate on the spread of the pandemic in Italy during the summer 2020, relating the number of infections with tourism data. In particular, we put the focus on the internal tourism (as international mobility was restricted at the time) between the various Italian regions for the summer holidays. The intuition is that tourist flows, due to the lift of travel restriction in the period when most people went on vacation, has been a determining factor in bringing back the virus, in areas where there were only a handful of cases, thus kick starting the second wave that hit Italy in autumn.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132297732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radioactivity Monitoring in Ocean Ecosystems (RAMONES)","authors":"T. Mertzimekis, P. Nomikou, E. Petra, Pedro Batista, David Cabecinhas, A. Pascoal, L. Sebastiño, J. Escartín, K. Kebkal, K. Karantzalos, A. Mallios, K. Nikolopoulos, L. Maigne","doi":"10.1145/3462203.3475906","DOIUrl":"https://doi.org/10.1145/3462203.3475906","url":null,"abstract":"Natural radioactivity in the marine environment has been present since the Earth's formation, while artificial radionuclides were introduced into the oceans in 1944. More recent direct sources exist that feed the oceans, such as low-level liquid discharges from reprocessing plants, large-scale releases due to disasters (e.g. Fukushima hit by the tsunami in 2011), and smaller-scale radiological events. Exploration of submarine environments should consider the existence of radioactivity in terms of its short- and long-term impact on marine and coastal ecosystems, also in correlation to natural hazards, such as seismic activity over submarine faults or activity of hydrothermal vent fields near the seabed. Significantly undersampled in oceans, radioactivity poses real risks to marine ecosystems and human population, urging for detailed, data-driven modeling. RAMONES is a new H2020-EU FET Proactive Project [2] aiming to offer new and efficient solutions for in in situ, continuous, long-term monitoring of radioactivity in harsh subsea environments. A new generation of submarine radiation sensing instruments, assisted by state-of-the-art (SoA) robotics and artificial intelligence (AI) will be developed towards understanding radiation related risks near and far from coastal areas, while providing data towards shaping new policies and guidelines for environmental sustainability, economic growth and human health, offering a framework for defining future environmental intelligence guidelines and practices. The main ambition is to lay a radical new path to close the existing marine radioactivity under-sampling gap and foster new interdisciplinary research in threatened natural deep-sea ecosystems. RAMONES will invest a significant effort to provide tools for long-term, rapid deployments, propose new robotics and AI-driven supported methodologies, and offer scaled-up solutions to researchers, policy makers and communities. RAMONES will combine SoA equipment from various disciplines and advanced modeling in fine synergy, and design new and effective approaches for the marine environment to provide efficient response to natural and man-made hazards, shaping future policies for the global population.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132017055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SMARTLAGOON: Innovative modelling approaches for predicting socio-environmental evolution in highly anthropized coastal lagoons","authors":"José M. Cecilia, Pietro Manzoni, D. Trolle, Anders Nielsen, Pablo Blanco, Catia Prandi, S. Peña-Haro, L. Barkved, D. Pierson, Javier Senent","doi":"10.1145/3462203.3475925","DOIUrl":"https://doi.org/10.1145/3462203.3475925","url":null,"abstract":"Coastal lagoons are ecosystems with significant environmental and socio-economic value. However, these natural systems are especially vulnerable to climatic and anthropogenic pressures, such as intensive agriculture and extensive urbanization as a consequence of the tourist development. Despite the vulnerability and complexity of these ecosystems, there has been limited development of novel techniques which can provide real-time monitoring, analysis and management of these critical resources. Beyond being useful for policy-making procedures at multiple levels of granularity, such tools can increase local and citizen awareness of environmental impacts. This paper introduces the key concept behind the SMARTLAGOON project, which intends to develop a digital twin to build a systemic understanding of the socio-environmental inter-relationships affecting coastal lagoons and their ecosystem. Particularly, we focus on the main research activities carried out since the beginning of the project (January 1st, 2021), which are mainly based on initial mapping and reporting of the main stakeholders' needs and wishes in relation to the technological products to be developed in SMARTLAGOON. This will onset the initial development pathway, while additional stakeholder inputs during the project lifetime will help to further explore and prioritize the key developments, thus maximizing the relevance and impact of the Mar Menor's digital twin.","PeriodicalId":336840,"journal":{"name":"Proceedings of the Conference on Information Technology for Social Good","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115393260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}