Nyhet

Smart Cities

8th Ibero-American Congress, ICSC-Cities 2025, Puebla, México, November 10–12, 2025, Revised Selected Papers

AvSergio Nesmachnow,Luis Hernández Callejo

Häftad, Engelska, 2026

Del 2742 i serien Communications in Computer and Information Science

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Beskrivning

This book constitutes the revised selected papers of the 8th Ibero-American Congress on Smart Cities, ICSC-Cities 2025, held in Puebla, México, during November 10–12, 2025.The 29 full papers included in these volumes were carefully reviewed and selected from 134 submissions. They were organized in the following topical sections: Internet of Things and Big Data; Computational Intelligence for Smart Cities; Optimization, Smart Industry, and Smart Public Services; and Innovative Approaches for Smart Cities.

Produktinformation

Utgivningsdatum:2026-04-07
Mått:155 x 235 x 25 mm
Vikt:680 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:432
Förlag:Springer Nature Switzerland AG
ISBN:9783032190185

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Informationsteknik: allmänt inom Data och IT

Innehållsförteckning

.- Internet of Things and Big Data..- Enhancing Solar Energy Research: A Database Approach for Photovoltaic Laboratories..- Smart meter based on demand forecasting for real-time architecture. .- IoT-Driven Smart Mobility: Enhancing Urban Transportation Efficiency with AI and Big Data..- Inspection of Land Surface Temperature Estimation Methods contrasted to in-situ Measurements: A Case Study in Panama..- IoT platform for detecting pavement irregularities on urban roads..- Flood analysis using remote sensing and cloud computing: a WebGIS tool for urban flood management..- Design and Implementation of a Low-Cost IoT Air-Quality Monitoring Network at Queen Mary University of London Mile End Campus..- Computational intelligence for smart cities..- Forecasting of Hospital Cardiovascular Emergency Demand in the Dominican Republic Using Time Series and Machine Learning Models..- Neural networks for modeling and predicting pollution in urban environments..- Estimation model for arrival times in urban public transportation of Cuernavaca using artificial neural networks..- Traffic sign detection for autonomous driving at 1:10 scale a YOLO approach..- Clustering Algorithm for Crack Detection on 2D Surfaces: Analysis of Its Dependence on Simulated Surface Size..- Clustering techniques to improve the prediction of the THD index for poorly correlated predictor variables..- Optimization, smart industry, and smart public services..- Evolutionary algorithms for the optimization of irrigation systems..- A biobjective model for the bins allocation and collection routing problem in waste management..- A multiobjective evolutionary algorithm for the bus stops location problem: optimizing demand coverage, travel times, and operational costs..- A Q-learning approach for long-term hydrothermal dispatch..- Electric Vehicles–based Microgrid for Demand Response Studies using a Stochastic Algorithm..- Implementation of a Metaheuristic based on K-means and Ant Colony Optimization..- Intelligent Operation of BESS for Active and Reactive Power Management in AC Microgrids Using the Crow Search Optimizer..- An smart industry study approach in photovoltaic panels and FEM design..- Brazilian Bus Transport Efficiency: A Simar-Wilson DEA with Beta-Tobit Analysis..- Innovative approaches for smart cities..- Quantum-resilient smart cities: Cryptographic strategies and implementation challenge..- A biobjective model for task assignment with multi-skilled workers and customer deadlines in service companies..- QR-based traceability system for avocado production in Mexico..- Optimal Dispatch in a Multinodal AC Microgrid Model with Battery Energy Storage System (BESS) and Solid-State Transformer (SST)..- Neural Network Approach for Super-resolution of a Digital Elevation Model..- Eddies as indicators of local sargassum inundation risks on the south coast of Dominican Republic..- Towards timely detection of student stress and anxiety.