Pub Date : 2024-03-01DOI: 10.1109/MTS.2024.3372610
Faisal Shennib;Ursula Eicker;Ketra Schmitt
In this Article, we will introduce several interrelated problems present in municipal solid waste recycling efforts, both globally and locally. The introduction serves to demonstrate how the lack of adequate global waste tracking and community-level waste contamination are related issues. This article elaborates on how these issues could be addressed with the Internet of Things (IoT), artificial intelligence (AI), and open data technology deployment. We will investigate the existing and possible applicability of this solution in resource-constrained environments, as opposed to exclusive use in the typical “smart city” context. Finally, we will discuss the risks and limitations of this approach.
{"title":"OpenWasteAI—Open Data, IoT, and AI for Circular Economy and Waste Tracking in Resource-Constrained Communities","authors":"Faisal Shennib;Ursula Eicker;Ketra Schmitt","doi":"10.1109/MTS.2024.3372610","DOIUrl":"https://doi.org/10.1109/MTS.2024.3372610","url":null,"abstract":"In this Article, we will introduce several interrelated problems present in municipal solid waste recycling efforts, both globally and locally. The introduction serves to demonstrate how the lack of adequate global waste tracking and community-level waste contamination are related issues. This article elaborates on how these issues could be addressed with the Internet of Things (IoT), artificial intelligence (AI), and open data technology deployment. We will investigate the existing and possible applicability of this solution in resource-constrained environments, as opposed to exclusive use in the typical “smart city” context. Finally, we will discuss the risks and limitations of this approach.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 1","pages":"39-53"},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140546413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1109/MTS.2024.3363785
Ricardo L. Armentano;Leandro J. Cymberknop;Luis Kun
René Gerónimo Favaloro was a creator of cardiovascular bypass surgery, for which he has received little recognition and about whom little has been written or internationally acknowledged [1] . He was also a rural doctor, a committed citizen, and a teacher, researcher, and historian [2] . He was known not only for his scientific brilliance, but also for fighting for equality and social justice and for his commitment to education ( Figure 1 ). This article was written to celebrate the 100th anniversary of Favaloro’s birth and his legacy in education.
René Gerónimo Favaloro 是心血管搭桥手术的开创者，但他的成就却鲜有人知，关于他的著作和国际认可也寥寥无几[1]。他还是一名乡村医生、一名坚定的公民、一名教师、研究员和历史学家[2]。他不仅以其科学才华闻名于世，还为争取平等和社会正义以及致力于教育事业而奋斗（图 1）。撰写本文是为了纪念法瓦罗罗诞辰 100 周年及其在教育领域留下的遗产。
{"title":"Dr. René Favaloro: A Visionary With Pioneering Innovations and a Humanitarian Approach","authors":"Ricardo L. Armentano;Leandro J. Cymberknop;Luis Kun","doi":"10.1109/MTS.2024.3363785","DOIUrl":"https://doi.org/10.1109/MTS.2024.3363785","url":null,"abstract":"René Gerónimo Favaloro was a creator of cardiovascular bypass surgery, for which he has received little recognition and about whom little has been written or internationally acknowledged \u0000<xref>[1]</xref>\u0000. He was also a rural doctor, a committed citizen, and a teacher, researcher, and historian \u0000<xref>[2]</xref>\u0000. He was known not only for his scientific brilliance, but also for fighting for equality and social justice and for his commitment to education (\u0000<xref>Figure 1</xref>\u0000). This article was written to celebrate the 100th anniversary of Favaloro’s birth and his legacy in education.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 1","pages":"109-114"},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496877","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140546505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1109/MTS.2024.3370023
Katina Michael;Roba Abbas;Savvas Papagiannidis
In 1992, Stephenson [1] described a type of metaverse in his science fiction novel Snow Crash . Through his imagination, Stephenson is said to have directly influenced the makers of Google Earth, and, more recently, Silicon Valley’s “Metaverse” [2] . In addition, there was a spate of literature published 15–20 years ago, related to metaverse concepts with the introduction of Second Life in June 2003 by Linden Labs. Many users experienced virtual spaces, shopped with virtual currency (Linden dollar, L ${$}$ ), and even frequented virtual storefronts [3] .
{"title":"The Social Implications of XR: Promises, Perils, and Potential","authors":"Katina Michael;Roba Abbas;Savvas Papagiannidis","doi":"10.1109/MTS.2024.3370023","DOIUrl":"https://doi.org/10.1109/MTS.2024.3370023","url":null,"abstract":"In 1992, Stephenson \u0000<xref>[1]</xref>\u0000 described a type of metaverse in his science fiction novel \u0000<italic>Snow Crash</i>\u0000. Through his imagination, Stephenson is said to have directly influenced the makers of Google Earth, and, more recently, Silicon Valley’s “Metaverse” \u0000<xref>[2]</xref>\u0000. In addition, there was a spate of literature published 15–20 years ago, related to metaverse concepts with the introduction of Second Life in June 2003 by Linden Labs. Many users experienced virtual spaces, shopped with virtual currency (Linden dollar, L\u0000<inline-formula> <tex-math>${$}$ </tex-math></inline-formula>\u0000), and even frequented virtual storefronts \u0000<xref>[3]</xref>\u0000.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 1","pages":"91-108"},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140546506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1109/MTS.2024.3365592
Beatriz C. D. Sasse
Network analysis using mixed graphical modeling is a computational social science approach with the potential to transform decades of sustainable development goals (SDGs) open data from the official SDG Indicators Database into digestible insights using open-source software R. Flexible and free, R provides the ability to perform network analysis. As we demonstrate, network analysis is a promising tool for exploratory analysis in policy evaluation accounting for the systemic nature of the SDG relationships, with a new opportunity to benefit from its statistical power based on large sample sizes without limiting its interpretability and approachability.
使用混合图形建模的网络分析是一种计算社会科学方法，它可以利用开源软件 R 将来自官方 SDG 指标数据库的数十年可持续发展目标（SDGs）公开数据转化为可消化的见解。正如我们所展示的那样，网络分析是一种很有前途的工具，可用于政策评估中的探索性分析，考虑到了可持续发展目标关系的系统性，并提供了一个新的机会，在不限制其可解释性和可接近性的情况下，从其基于大样本量的统计能力中获益。
{"title":"The Interdependence of the Sustainable Development Goals: Network Analysis as a Methodology for Policy Impact Evaluation","authors":"Beatriz C. D. Sasse","doi":"10.1109/MTS.2024.3365592","DOIUrl":"https://doi.org/10.1109/MTS.2024.3365592","url":null,"abstract":"Network analysis using mixed graphical modeling is a computational social science approach with the potential to transform decades of sustainable development goals (SDGs) open data from the official SDG Indicators Database into digestible insights using open-source software R. Flexible and free, R provides the ability to perform network analysis. As we demonstrate, network analysis is a promising tool for exploratory analysis in policy evaluation accounting for the systemic nature of the SDG relationships, with a new opportunity to benefit from its statistical power based on large sample sizes without limiting its interpretability and approachability.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 1","pages":"86-90"},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140546424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1109/MTS.2024.3372605
David Kolevski;Katina Michael
Edge computing is an emerging computing paradigm representing decentralized and distributed information technology architecture [1] . The demand for edge computing is primarily driven by the increased number of smart devices and the Internet of Things (IoT) that generate and transmit a substantial amount of data, that would otherwise be stored on cloud computing services. The edge architecture enables data and computation to be performed in close proximity to users and data sources and acts as the pathway toward upstream data centers [2] . Rather than sending data to the cloud for processing, the analysis and work is done closer to where the source of the data is generated ( Figure 1 ). Edge services leverage local infrastructure resources allowing for reduced network latency, improved bandwidth utilization, and better energy efficiency compared to cloud computing.
{"title":"Edge Computing and IoT Data Breaches: Security, Privacy, Trust, and Regulation","authors":"David Kolevski;Katina Michael","doi":"10.1109/MTS.2024.3372605","DOIUrl":"https://doi.org/10.1109/MTS.2024.3372605","url":null,"abstract":"Edge computing is an emerging computing paradigm representing decentralized and distributed information technology architecture \u0000<xref>[1]</xref>\u0000. The demand for edge computing is primarily driven by the increased number of smart devices and the Internet of Things (IoT) that generate and transmit a substantial amount of data, that would otherwise be stored on cloud computing services. The edge architecture enables data and computation to be performed in close proximity to users and data sources and acts as the pathway toward upstream data centers \u0000<xref>[2]</xref>\u0000. Rather than sending data to the cloud for processing, the analysis and work is done closer to where the source of the data is generated (\u0000<xref>Figure 1</xref>\u0000). Edge services leverage local infrastructure resources allowing for reduced network latency, improved bandwidth utilization, and better energy efficiency compared to cloud computing.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 1","pages":"22-32"},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496887","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140546504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1109/MTS.2024.3363784
Analia Lourdes Pastran
Since 2020, residents of cities, especially the poor and vulnerable, have been disproportionately affected by the social, economic, and political consequences of the COVID pandemic and other global crises.
{"title":"Sustainability in the Built Environment: The Galapagos Experience","authors":"Analia Lourdes Pastran","doi":"10.1109/MTS.2024.3363784","DOIUrl":"https://doi.org/10.1109/MTS.2024.3363784","url":null,"abstract":"Since 2020, residents of cities, especially the poor and vulnerable, have been disproportionately affected by the social, economic, and political consequences of the COVID pandemic and other global crises.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 1","pages":"17-21"},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496890","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140546412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1109/MTS.2024.3377459
Hossein Masoumi Karakani
In 2015, the United Nations (UN) launched an ambitious set of 17 Sustainable Development Goals (SDGs) to end poverty, protect the planet, and ensure prosperity for all as part of the 2030 Agenda for Sustainable Development. Achieving these far-reaching goals requires effective tracking of progress across 169 targets and over 230 indicators. Furthermore, adopted in 2015, Africa Agenda 2063 is a strategic framework developed by the African Union (AU) to optimize the use of the continent’s resources for sustainable and inclusive growth. It aims to deliver on key aspirations shared by African nations including a high standard of living, well-educated citizens, good governance, strong cultural identity, and Africa’s strong voice in global affairs. Built around 20 goals and seven priority areas, Agenda 2063 provides a shared vision and roadmap for socioeconomic transformation in Africa over the next 50 years. However, numerous countries in Africa face considerable challenges in collecting, timely, granular, high-quality data to adequately monitor SDG metrics. Traditional data sources like surveys and administrative records often have gaps, especially at subnational levels. As a result, national statistics offices, particularly in Africa, lack the data needed to properly inform SDG-related policies and interventions.
{"title":"Supporting the Measurement of Sustainable Development Goals in Africa: Geospatial Sentiment Data Analysis","authors":"Hossein Masoumi Karakani","doi":"10.1109/MTS.2024.3377459","DOIUrl":"https://doi.org/10.1109/MTS.2024.3377459","url":null,"abstract":"In 2015, the United Nations (UN) launched an ambitious set of 17 Sustainable Development Goals (SDGs) to end poverty, protect the planet, and ensure prosperity for all as part of the 2030 Agenda for Sustainable Development. Achieving these far-reaching goals requires effective tracking of progress across 169 targets and over 230 indicators. Furthermore, adopted in 2015, Africa Agenda 2063 is a strategic framework developed by the African Union (AU) to optimize the use of the continent’s resources for sustainable and inclusive growth. It aims to deliver on key aspirations shared by African nations including a high standard of living, well-educated citizens, good governance, strong cultural identity, and Africa’s strong voice in global affairs. Built around 20 goals and seven priority areas, Agenda 2063 provides a shared vision and roadmap for socioeconomic transformation in Africa over the next 50 years. However, numerous countries in Africa face considerable challenges in collecting, timely, granular, high-quality data to adequately monitor SDG metrics. Traditional data sources like surveys and administrative records often have gaps, especially at subnational levels. As a result, national statistics offices, particularly in Africa, lack the data needed to properly inform SDG-related policies and interventions.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 1","pages":"70-85"},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140550175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1109/MTS.2024.3375173
{"title":"IEEE Technology and Society Magazine Publication Information","authors":"","doi":"10.1109/MTS.2024.3375173","DOIUrl":"https://doi.org/10.1109/MTS.2024.3375173","url":null,"abstract":"","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 1","pages":"1-1"},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496878","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140546474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1109/MTS.2024.3365591
Apurva Kulkarni;Chandrashekar Ramanathan;Vinu E. Venugopal
Achieving sustainable development goals (SDGs) necessitates the adoption of sustainable policies, which entails a crucial task of policy formulation. Policymakers must consider multiple factors, such as the present development status, which can be assessed using diverse data points, as well as the policy’s impact and an action plan outlining its implementation [1] . These data points typically originate from various sources, primarily governmental bodies encompassing statistics, budgets, legislation, public services, and geospatial data (maps, satellite imagery), along with domain users comprising individuals, organizations, and governments [2] . The SDGs are intricately crafted, taking into account a multitude of factors and pinpointing key indicators that influence these factors. These factors typically span across diverse data points sourced from various sectors. For instance, in assessing the student dropout rate, it is imperative to consider factors such as the availability of transportation facilities, basic hygiene amenities, access to drinking water, and the effectiveness of government-organized schemes in utilization and impact. Employing an open data framework coupled with advanced artificial intelligence (AI) models has the potential to facilitate in-depth exploration and analysis, providing valuable insights into the complex interplay of these factors and contributing to a more comprehensive understanding of SDG-related challenges and opportunities.
{"title":"Toward Sustainable Data Practices: Integrating Open Data With SDG-Based Data Lake Frameworks","authors":"Apurva Kulkarni;Chandrashekar Ramanathan;Vinu E. Venugopal","doi":"10.1109/MTS.2024.3365591","DOIUrl":"https://doi.org/10.1109/MTS.2024.3365591","url":null,"abstract":"Achieving sustainable development goals (SDGs) necessitates the adoption of sustainable policies, which entails a crucial task of policy formulation. Policymakers must consider multiple factors, such as the present development status, which can be assessed using diverse data points, as well as the policy’s impact and an action plan outlining its implementation \u0000<xref>[1]</xref>\u0000. These data points typically originate from various sources, primarily governmental bodies encompassing statistics, budgets, legislation, public services, and geospatial data (maps, satellite imagery), along with domain users comprising individuals, organizations, and governments \u0000<xref>[2]</xref>\u0000. The SDGs are intricately crafted, taking into account a multitude of factors and pinpointing key indicators that influence these factors. These factors typically span across diverse data points sourced from various sectors. For instance, in assessing the student dropout rate, it is imperative to consider factors such as the availability of transportation facilities, basic hygiene amenities, access to drinking water, and the effectiveness of government-organized schemes in utilization and impact. Employing an open data framework coupled with advanced artificial intelligence (AI) models has the potential to facilitate in-depth exploration and analysis, providing valuable insights into the complex interplay of these factors and contributing to a more comprehensive understanding of SDG-related challenges and opportunities.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 1","pages":"62-69"},"PeriodicalIF":2.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140546508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1109/MTS.2023.3341465
Mackenzie Jorgensen;Madeleine Waller;Oana Cocarascu;Natalia Criado;Odinaldo Rodrigues;Jose Such;Elizabeth Black
Algorithmic Decision-Making Systems (ADMS) 1 fairness issues have been well highlighted over the past decade [1] , including some facial recognition systems struggling to identify people of color [2] . In 2021, Uber drivers filed a claim with the U.K. ’s employment tribunal for unfair dismissal resulting from automated facial recognition technology by Microsoft [3] . Bias mitigation methods have been developed to reduce discrimination from ADMS. These typically operationalize fairness notions as fairness metrics to minimize discrimination [4] . We refer to ADMS to which bias mitigation methods have been applied as “mitigated ADMS” or, in the singular, a “mitigated system.”
{"title":"Investigating the Legality of Bias Mitigation Methods in the United Kingdom","authors":"Mackenzie Jorgensen;Madeleine Waller;Oana Cocarascu;Natalia Criado;Odinaldo Rodrigues;Jose Such;Elizabeth Black","doi":"10.1109/MTS.2023.3341465","DOIUrl":"https://doi.org/10.1109/MTS.2023.3341465","url":null,"abstract":"Algorithmic Decision-Making Systems (ADMS) \u0000<xref>1</xref>\u0000 fairness issues have been well highlighted over the past decade \u0000<xref>[1]</xref>\u0000, including some facial recognition systems struggling to identify people of color \u0000<xref>[2]</xref>\u0000. In 2021, Uber drivers filed a claim with the U.K. ’s employment tribunal for unfair dismissal resulting from automated facial recognition technology by Microsoft \u0000<xref>[3]</xref>\u0000. \u0000<italic>Bias mitigation methods</i>\u0000 have been developed to reduce discrimination from ADMS. These typically operationalize fairness notions as \u0000<italic>fairness metrics</i>\u0000 to minimize discrimination \u0000<xref>[4]</xref>\u0000. We refer to ADMS to which bias mitigation methods have been applied as “mitigated ADMS” or, in the singular, a “mitigated system.”","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"42 4","pages":"87-94"},"PeriodicalIF":2.2,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139504483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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