Designing a Web Spatial Decision Support System Based on Analytic Network Process to Locate a Freight Lorry Parking

Crimi, Alessandro; Jones, Tom; Sgalambro, Antonino

doi:10.3390/su11205629

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…Automated analysis of large data sets can replace manual monitoring, reducing costs and increasing the efficiency of monitoring programs [15,16]; -global collaboration: Web-based applications facilitate global collaboration in environmental monitoring. Researchers and organizations from around the world can share and access data, collaborate on projects, and contribute to a more complete understanding of global environmental trends [17][18][19].…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Neural Networks for Environmental Monitoring: A Web Application for Image Recognition

Bernatska,

Dzhumelia,

Typilo

et al. 2024

Advances in Transdisciplinary Engineering

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Environmental monitoring is increasingly reliant on image recognition through neural networks, automating the identification and classification of environmental threats. This automation optimizes resource allocation, enhances monitoring accuracy, and empowers researchers to address climate-related challenges. In response to this, we present a web application built using React.js and TensorFlow.js, which enables real-time image recognition. This application facilitates tasks ranging from climate analysis to disaster response and wildlife conservation, offering valuable insights into environmental trends. Moreover, it engages the public, promotes awareness, and contributes to conservation efforts, making it a versatile and cost-effective tool for environmental monitoring. The application leverages advancements in image recognition technology, availability of datasets, open-source frameworks, and cloud computing infrastructure. It supports a wide range of applications, promotes global collaboration, and ensures data security. While challenges exist, the potential of neural networks in environmental monitoring is promising. The web application combines the power of React.js and artificial neural networks, enhancing environmental monitoring efficacy and fostering sustainable practices on a global scale. Ongoing research and standardization efforts are essential for refining and expanding this approach.

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Section: Literature Reviewmentioning

confidence: 99%

“…A web application for a neural network is software that allows users to interact with a neural network through a web browser [16][17]. Web applications can be used for various purposes, such as training, testing, and utilizing neural networks [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37].…”

Section: Literature Reviewmentioning

confidence: 99%

Neural Networks for Environmental Monitoring: A Web Application for Image Recognition

Bernatska,

Dzhumelia,

Typilo

et al. 2024

Advances in Transdisciplinary Engineering

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“…For example, Mwaura and Kada (2017) presented a web-based SDSS in which a multi-criteria decision making model was used to evaluate potential sites of geothermal wells in Kenya, east Africa. Crimi et al (2019) investigated the identification of priority regions in Bradford, UK for freight lorry parking within a web-based SDSS environment. Lan et al (2020) applied web-based SDSS that guides the monitoring and sharing of water quality information of private wells in Gaston County, NC, USA.…”

Section: Literature Reviewmentioning

confidence: 99%

A Web-based Spatial Decision Support System of Wastewater Surveillance for COVID-19 Monitoring: A Case Study of a University Campus

Tang

Chen

Slocum

et al. 2022

Preprint

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The ongoing COVID-19 pandemic has produced substantial impacts on our society. Wastewater surveillance has increasingly been introduced to support the monitoring, and thus mitigation, of COVID-19 outbreaks and transmission. Monitoring of buildings and sub-sewershed areas via a wastewater surveillance approach has been a cost-effective strategy for mass testing of residents in congregate living situations such as universities. A series of spatial and spatiotemporal data are involved with wastewater surveillance, and these data must be interpreted and integrated with other information to better serve as guidance on response to a positive wastewater signal. The management and analysis of these data poses a significant challenge, in particular, for the need of supporting timely decision making. In this study, we present a web-based spatial decision support system framework to address this challenge. Our study area is the main campus of the University of North Carolina at Charlotte. We develop a spatiotemporal data model that facilitates the management of space-time data related to wastewater surveillance. We use spatiotemporal analysis and modeling to discover spatio-temporal patterns of COVID-19 virus abundance at wastewater collection sites that may not be readily apparent in wastewater data as they are routinely collected. Web-based GIS dashboards are implemented to support the automatic update and sharing of wastewater testing results. Our web-based SDSS framework enables the efficient and automated management, analytics, and sharing of spatiotemporal data of wastewater testing results for our study area. This framework provides substantial support for informing critical decisions or guidelines for the prevention of COVID-19 outbreak and the mitigation of virus transmission on campus.

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“…For instance, Bradford City experiences urban growth, limited network capacity, and disturbances in urban delivery networks, including parking space challenges. 71 In addition, several city logistics challenges related to the growth of commercial areas in the city of Seville, 6 movement of goods in Stuttgart, 72 traffic congestion, 73 and the growing demand in Singapore 74 were identified.…”

Section: Developed Economies Regionmentioning

confidence: 99%

City logistics challenges and innovative solutions in developed and developing economies: A systematic literature review

Arvianto

Sopha

Asih

et al. 2021

International Journal of Engineering Business Management

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Varying characteristics of developed and developing countries have resulted in different challenges and innovative solutions of city logistics. This study aimed to identify research clusters on city logistics between developed and developing economies and to systematically compare city logistics challenges and associated innovative solutions for both economies. Bibliometric analysis and a systematic literature review were applied to analyze 328 peer-reviewed publications, comprising 229 (70%) and 99 (30%) articles addressing case studies in developed and developing economies, respectively. We discovered six research clusters in city logistics literature for developed countries, compared with only four for developing economies in which public policy has not been addressed. Urban growth, environmental challenges, and traffic congestion are the three major city logistics challenges in both types of economies. Furthermore, fleet increment and inadequate loading/unloading spaces are the city logistics challenges analyzed in the literature on developing countries compared with the literature on developed economies that addresses the challenges of education deficiency, regulation, emergence of new business models, and network accessibility and capacity. Consequently, innovative solutions adopted by developed countries demonstrate varied processes involving technology, policy (including public policy and sustainability measures), infrastructure, and economic measures, while for developing countries, the focus remains on effective and efficient distribution operations using optimization and collaboration efforts.

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Designing a Web Spatial Decision Support System Based on Analytic Network Process to Locate a Freight Lorry Parking

Cited by 7 publications

References 12 publications

Neural Networks for Environmental Monitoring: A Web Application for Image Recognition

Neural Networks for Environmental Monitoring: A Web Application for Image Recognition

A Web-based Spatial Decision Support System of Wastewater Surveillance for COVID-19 Monitoring: A Case Study of a University Campus

City logistics challenges and innovative solutions in developed and developing economies: A systematic literature review

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