Enhancing GIS models for sustainable development in human settlements using intelligent IoT infrastructure and human-machine interaction
Sustainable development (SD) in human settlements (HS) can be achieved by integrating intelligent IoT infrastructure and human-machine interaction (HMI) into geographic information system (GIS) models. This study proposes a method combining real-time (RT) data and automation to address gaps in techn...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-09-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S259012302502780X |
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| author | Mingxing Xu |
| author_facet | Mingxing Xu |
| author_sort | Mingxing Xu |
| collection | DOAJ |
| description | Sustainable development (SD) in human settlements (HS) can be achieved by integrating intelligent IoT infrastructure and human-machine interaction (HMI) into geographic information system (GIS) models. This study proposes a method combining real-time (RT) data and automation to address gaps in technology and urban planning. Current GIS models are ineffective due to limited RT data integration, poor urban system interaction, and lack of adaptability to dynamic changes. These shortcomings hinder sustainable urban growth, leading to suboptimal planning and resource management (RM). The proposed IoT-based framework for SD in HS (IoT-SD-HS) utilizes IoT devices and sensors to collect RT social, economic, and environmental data. This data enables adaptive decision-making (DM), smarter city planning, improved RM, and enhanced urban resilience. Intuitive HMI interfaces allow stakeholders to work effectively with the framework, facilitating data-driven decisions for urban planning and sustainability. Outcomes demonstrate significant improvements in energy consumption (EC), waste management (WM), and infrastructure development. The IoT-SD-HS model achieves high urban resilience (96.12%), WM efficiency (97.34%), and decision accuracy (98.12%), while reducing EC by 10.12%. By continuously evaluating power distribution during peak hours, smart cities reduce carbon footprints and save costs, demonstrating superior performance compared to existing methods.© 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Global Science and Technology Forum Pte Ltd |
| format | Article |
| id | doaj-art-c7cc7bf8a752489abe3eb5314a943f22 |
| institution | Kabale University |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-c7cc7bf8a752489abe3eb5314a943f222025-08-20T05:07:35ZengElsevierResults in Engineering2590-12302025-09-012710671310.1016/j.rineng.2025.106713Enhancing GIS models for sustainable development in human settlements using intelligent IoT infrastructure and human-machine interactionMingxing Xu0College of Architectural Arts, Guangxi Arts University, Nanning 530000, Guangxi, ChinaSustainable development (SD) in human settlements (HS) can be achieved by integrating intelligent IoT infrastructure and human-machine interaction (HMI) into geographic information system (GIS) models. This study proposes a method combining real-time (RT) data and automation to address gaps in technology and urban planning. Current GIS models are ineffective due to limited RT data integration, poor urban system interaction, and lack of adaptability to dynamic changes. These shortcomings hinder sustainable urban growth, leading to suboptimal planning and resource management (RM). The proposed IoT-based framework for SD in HS (IoT-SD-HS) utilizes IoT devices and sensors to collect RT social, economic, and environmental data. This data enables adaptive decision-making (DM), smarter city planning, improved RM, and enhanced urban resilience. Intuitive HMI interfaces allow stakeholders to work effectively with the framework, facilitating data-driven decisions for urban planning and sustainability. Outcomes demonstrate significant improvements in energy consumption (EC), waste management (WM), and infrastructure development. The IoT-SD-HS model achieves high urban resilience (96.12%), WM efficiency (97.34%), and decision accuracy (98.12%), while reducing EC by 10.12%. By continuously evaluating power distribution during peak hours, smart cities reduce carbon footprints and save costs, demonstrating superior performance compared to existing methods.© 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Global Science and Technology Forum Pte Ltdhttp://www.sciencedirect.com/science/article/pii/S259012302502780XGeographic Information System (GIS)IoTHuman SettlementsSustainable Management (SM)Human- Machine Interaction (HMI) |
| spellingShingle | Mingxing Xu Enhancing GIS models for sustainable development in human settlements using intelligent IoT infrastructure and human-machine interaction Results in Engineering Geographic Information System (GIS) IoT Human Settlements Sustainable Management (SM) Human- Machine Interaction (HMI) |
| title | Enhancing GIS models for sustainable development in human settlements using intelligent IoT infrastructure and human-machine interaction |
| title_full | Enhancing GIS models for sustainable development in human settlements using intelligent IoT infrastructure and human-machine interaction |
| title_fullStr | Enhancing GIS models for sustainable development in human settlements using intelligent IoT infrastructure and human-machine interaction |
| title_full_unstemmed | Enhancing GIS models for sustainable development in human settlements using intelligent IoT infrastructure and human-machine interaction |
| title_short | Enhancing GIS models for sustainable development in human settlements using intelligent IoT infrastructure and human-machine interaction |
| title_sort | enhancing gis models for sustainable development in human settlements using intelligent iot infrastructure and human machine interaction |
| topic | Geographic Information System (GIS) IoT Human Settlements Sustainable Management (SM) Human- Machine Interaction (HMI) |
| url | http://www.sciencedirect.com/science/article/pii/S259012302502780X |
| work_keys_str_mv | AT mingxingxu enhancinggismodelsforsustainabledevelopmentinhumansettlementsusingintelligentiotinfrastructureandhumanmachineinteraction |