Enhancing GIS models for sustainable development in human settlements using intelligent IoT infrastructure and human-machine interaction - Mingxing Xu (Results in Engineering)
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