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Journal : West Science Nature and Technology

Implementation of Internet of Things (IoT) Technology in Air Pollution Monitoring in Jakarta: Quantitative Analysis of the Influence of Air Quality Change and Its Impact on Public Health in Jakarta Arief Budi Pratomo; Hanifah Nurul Muthmainah; Natal Kristiono; Gogor Christmass Setyawan
West Science Nature and Technology Vol. 1 No. 01 (2023): West Science Nature and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsnt.v1i01.225

Abstract

Air pollution is a pressing global issue, particularly in urban areas where rapid industrialization and urbanization have led to deteriorating air quality. Jakarta, as one of the world's most populous megacities, faces significant challenges in managing air pollution and safeguarding public health. This research paper explores the implementation of Internet of Things (IoT) technology for air pollution monitoring in Jakarta and quantitatively assesses the influence of air quality changes on public health outcomes. The study involves the deployment of IoT sensors to collect real-time data on key air pollutants, including particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3). Statistical analyses, including regression and correlation analyses, reveal strong associations between air quality variables and health indicators. Findings indicate that elevated levels of PM2.5 and NO2 are linked to increased hospital admissions for respiratory diseases, and CO levels are associated with hypertension and cardiovascular diseases. The study also explores public perception through surveys and questionnaires, highlighting a high level of awareness and support for government initiatives to improve air quality. The results emphasize the need for informed policy decisions, including stricter emission standards and public awareness campaigns, to combat air pollution and protect public health in Jakarta.
Multidisciplinary Research Mapping in Automation and Artificial Intelligence: A Bibliometric Analysis to Identify Science Convergence Nanny Mayasari; Hanifah Nurul Muthmainah; Natal Kristiono
West Science Nature and Technology Vol. 1 No. 01 (2023): West Science Nature and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsnt.v1i01.234

Abstract

The field of Automation and Artificial Intelligence (AI) has witnessed rapid evolution, marked by interdisciplinary collaborations and groundbreaking advancements. This bibliometric analysis delves into the multidisciplinary research landscape within Automation and AI, aiming to identify science convergence and key trends. Utilizing a comprehensive dataset, we employed co-authorship analysis, citation analysis, keyword analysis, temporal analysis, and VOSviewer visualizations to map the dynamic landscape of Automation and AI research. Our analysis revealed extensive interdisciplinary collaboration among researchers from diverse domains, highlighting the role of cross-disciplinary innovation in advancing the field. Influential authors and highly cited papers were identified, emphasizing the impact of key contributions. Dominant research themes, such as machine learning, ethics in AI, and AI applications in healthcare, emerged from keyword analysis, reflecting the field's evolving priorities. VOSviewer visualizations provided clear representations of science convergence, showcasing the interconnectedness of disciplines like computer science, engineering, ethics, and economics. Interdisciplinary hubs and bridges were identified, underscoring the importance of cross-disciplinary research in shaping the future of Automation and AI. The findings of this analysis offer valuable insights for researchers, policymakers, and practitioners, providing a foundation for enhanced collaboration, ethical considerations, innovation in healthcare, and tailored education and training programs to meet evolving demands.