General parametric of four hybrid microconcentrator photovoltaic systems for electric car charging station

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

“…It involves deploying AI algorithms and techniques to analyze vast data collected from urban infrastructures and systems and diverse IoT devices embedded throughout the city's environment. This encompasses data from transportation systems, energy grids, water and waste management systems, smart buildings, public safety sensors, environmental monitoring devices, and other urban IoT deployments [ 8 , 10 , [13] , [14] , [15] , [16] , [74] ]. Urban AIoT aims to enhance cities' efficiency, sustainability, and livability by enabling intelligent decision-making, predictive analytics, and process automation across diverse domains.…”

“…[ 7 , 8 ] for detailed reviews). They rely heavily on data, AI algorithms, and AIoT tools to understand current environmental conditions, predict future trends, and make informed decisions to minimize environmental impact while promoting sustainability in smart cities and beyond [ [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [75] ]. In the context of sustainable smart cities, AIoT can enhance environmental sustainability strategies by enabling real-time monitoring, analysis, and optimization of resource use.…”

“…Targeted investigations pertain to renewable energies systems [ 10 ], hydrogen-based hybrid renewable energy systems [ 113 ], photovoltaic power generation forecasting [ 114 ], energy management systems [ 115 ], energy demand side [ 116 ], waste management [ 117 , 118 ], sustainable transportation development [ 119 ], ecosystem services [ 98 ], biodiversity protection [ 120 ], urban water resource management [ 99 , 121 ], air pollution [ 122 ], flood resistance [ 123 ], flood risk assessment [ 124 ], and flood prediction [ 16 ]. Important to note is that the energy sector is a primary user of AI in smart cities [ 8 , 125 ], with various technologies supporting the monitoring, analysis, and application of planning processes to combat pollution in urban environment.…”

“…This integrated approach highlights the synergistic potential of AI and AIoT technologies in reshaping urban planning strategies to address complex environmental challenges. Indeed, these technologies have significantly impacted multiple urban domains by optimizing resource management, enhancing energy efficiency, maximizing the utilization of renewable energy sources, streamlining waste management processes, improving transportation systems, preserving biodiversity, reducing environmental footprints, and mitigating the potential risks of climate change [ [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] ]. Through the provision of comprehensive environmental data, the facilitation of seamless integration of urban systems, and the coordination of various urban domains, AI and AIoT technologies closely align with the fundamental responsibilities of urban planners.…”