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New Perspectives in Information Systems for Urban Environment and Public Health

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Global Health".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 8199

Special Issue Editors

Dr. Sameera Mubarak

E-Mail Website
Leading Guest Editor
School of Information Technology and Mathematical Sciences, University of South Australia, Adelaide, SA 5001, Australia
Interests: smart city; e-governance; e-learning; information security management
Special Issues, Collections and Topics in MDPI journals
Dr. Mubarak Ali Rahamathulla

E-Mail Website
Co-Guest Editor
School of Allied Health, The University of Western Australia, Perth, WA 6009, Australia
Interests: social issues; policy formation; problems with young adult; e-governance
Dr. Santoso Wibowo

E-Mail Website
Co-Guest Editor
School of Engineering and Technology, Central Queensland University, Melbourne, QLD 4701, Australia
Interests: artificial intelligence; deep learning; machine learning; intelligent information systems; performance evaluation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Due to the unprecedented nature, severity, and scale of COVID-19, societies, government agencies, and businesses alike have been forced to adopt and leverage existing information systems to collect, process, store, and distribute, in real time, relevant data that enhances our understanding of the epidemiological situation and how to minimize the impact of current pandemic. With the distribution of COVID-19 vaccinations and the resumption of international travel, the urban environment and public health will be faced with more challenges. Thus, information systems are expected to play more significant roles in societies and organizations, as they adjust to the new normal.  

Therefore, this Special Issue aims to expand the emerging work and encourage research on new perspectives in information systems for the urban environment and public health. We invite papers that address significant research questions around the adoption and development of information systems in different domains related to the urban environment and public health management, including but not limited to, healthcare, public administration, education, transportation, tourists and visitors, and waste management. We welcome a wide range of interdisciplinary research articles which may vary in content, theory, perspectives, and methods.

Dr. Sameera Mubarak
Dr. Mubarak Ali Rahamathulla
Dr. Santoso Wibowo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • urban environment
  • public health
  • public health management
  • information systems
  • adoption and development of information systems
  • public administration
  • education
  • transportation
  • waste management
  • COVID-19

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Published Papers (2 papers)

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Research

15 pages, 3262 KiB  
Article
Forecasting the Status of Municipal Waste in Smart Bins Using Deep Learning
by Sabbir Ahmed, Sameera Mubarak, Jia Tina Du and Santoso Wibowo
Int. J. Environ. Res. Public Health 2022, 19(24), 16798; https://doi.org/10.3390/ijerph192416798 - 14 Dec 2022
Cited by 23 | Viewed by 5263
Abstract
The immense growth of the population generates a polluted environment that must be managed to ensure environmental sustainability, versatility and efficiency in our everyday lives. Particularly, the municipality is unable to cope with the increase in garbage, and many urban areas are becoming [...] Read more.
The immense growth of the population generates a polluted environment that must be managed to ensure environmental sustainability, versatility and efficiency in our everyday lives. Particularly, the municipality is unable to cope with the increase in garbage, and many urban areas are becoming increasingly difficult to manage. The advancement of technology allows researchers to transmit data from municipal bins using smart IoT (Internet of Things) devices. These bin data can contribute to a compelling analysis of waste management instead of depending on the historical dataset. Thus, this study proposes forecasting models comprising of 1D CNN (Convolutional Neural Networks) long short-term memory (LSTM), gated recurrent units (GRU) and bidirectional long short-term memory (Bi-LSTM) for time series prediction of public bins. The execution of the models is evaluated by Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Coefficient determination (R2) and Root Mean Squared Error (RMSE). For different numbers of epochs, hidden layers, dense layers, and different units in hidden layers, the RSME values measured for 1D CNN, LSTM, GRU and Bi-LSTM models are 1.12, 1.57, 1.69 and 1.54, respectively. The best MAPE value is 1.855, which is found for the LSTM model. Therefore, our findings indicate that LSTM can be used for bin emptiness or fullness prediction for improved planning and management due to its proven resilience and increased forecast accuracy. Full article
(This article belongs to the Special Issue New Perspectives in Information Systems for Urban Environment and Public Health)
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26 pages, 9743 KiB  
Article
Multiscale Characteristics and Drivers of the Bundles of Ecosystem Service Budgets in the Su-Xi-Chang Region, China
by Yue Wang, Qi Fu, Tinghui Wang, Mengfan Gao and Jinhua Chen
Int. J. Environ. Res. Public Health 2022, 19(19), 12910; https://doi.org/10.3390/ijerph191912910 - 9 Oct 2022
Cited by 3 | Viewed by 2308
Abstract
Managing ecosystem services (ESs) to meet human needs is critical to achieving sustainable development in rapidly urbanizing regions. Identifying ES budget bundles and analyzing their drivers at a multiscale level can facilitate management decision-making; however, further research is required in areas undergoing rapid [...] Read more.
Managing ecosystem services (ESs) to meet human needs is critical to achieving sustainable development in rapidly urbanizing regions. Identifying ES budget bundles and analyzing their drivers at a multiscale level can facilitate management decision-making; however, further research is required in areas undergoing rapid urbanization. This study quantified the supply, demand, and budgets of six typical ESs at the county, township, and village scales in the Su-Xi-Chang region in 2020. Additionally, the influence of natural environmental and socioeconomic factors on ES budget bundles was investigated based on K-means cluster analysis and the Geodetector model. The results showed that ESs on all three scales showed a mismatch between supply and demand. The similarity in the spatial pattern of supply, demand, and budgets of ESs at the township and village scales was higher than that at the township and county scales. The location and area of surplus, balance, and deficit varied with scale. We found that population density and the proportion of impervious surfaces are the main factors influencing the formation of the ES budget bundles at different scales. In addition, the diversity and degree of interpretation of drivers varied with scale. We believe that focusing on the overall situation on a large scale and implementing precise management on a small scale can make management decisions more effective. This study can provide a scientific basis for the sustainable utilization of ESs in the Su-Xi-Chang region, and the research results and methods can provide a reference for similar studies in other rapidly urbanizing areas in the world. Full article
(This article belongs to the Special Issue New Perspectives in Information Systems for Urban Environment and Public Health)
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