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 Internet of Things (IoT) infrastructure and human-machine interaction (HMI) into geographic information system (GIS) models. This study proposes a method that combines real-time data and automation to address the gaps in technology and urban planning. Current GIS models are ineffective because of limited real-time data integration, poor urban system interactions, and lack of adaptability to dynamic changes. These shortcomings hinder sustainable urban growth and lead to suboptimal planning and resource management. The proposed IoT-based framework for SD in HS (IoT-SD-HS) uses IoT devices and sensors to collect social, economic, and environmental data. These data enable adaptive decision-making, smart city planning, improved resource management, and enhanced urban resilience. Intuitive HMI interfaces enable stakeholders to work effectively within a framework, thereby facilitating data-driven decisions for urban planning and sustainability. The results demonstrate significant improvements in energy consumption, waste management, and infrastructure development. The IoT-SD-HS model achieved high urban resilience (96.12%), waste management efficiency (97.34%), and decision accuracy (98.12%) while reducing energy consumption by 10.12%. By continuously evaluating power distribution during peak hours, smart cities can reduce their carbon footprints and save costs, demonstrating superior performance compared to existing methods.