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Innovation, Transparency, and Participation in Smart Government
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Author(s)/Editor(s): Jorge A. Ruiz-Vanoye (Universidad Politécnica de Pachuca, Mexico), Ocotlan Díaz-Parra (Universidad Politécnica de Pachuca, Mexico)and Eric Simancas-Acevedo (Universidad Politécnica de Pachuca, Mexico)
Copyright: ©2026
DOI: 10.4018/979-8-3373-5535-1
ISBN13: 9798337355351
EISBN13: 9798337355375
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DescriptionThe rise of digital technologies reshapes public administration, giving rise to smart government, a governance model that leverages data, connectivity, and innovation to enhance the efficiency, responsiveness, and accountability of public services. Central to this are innovation, transparency, and citizen participation. Innovation drives the adoption of tools such as artificial intelligence (AI), blockchain, and Internet of Things (IoT) to streamline operations and deliver smarter services. Transparency ensures government processes and decisions are open, data-driven, and accessible. Participation empowers citizens to help create policies and engage in decision-making through digital platforms, ensuring governance is inclusive and aligned with public needs. Together, these elements may form a smart government that is technologically advanced while democratic, ethical, and citizen-centric. Innovation, Transparency, and Participation in Smart Government addresses the intersection between digital transformation in the public sector and the implementation of emerging technologies that optimize urban management and improve quality of life. It examines innovations that redefine governance, highlighting challenges and opportunities in the implementation of these systems. This book covers topics such as digital technology, smart grids, and data science, and is a useful resource for policymakers, government officials, engineers, academicians, researchers, and scientists.
Author's/Editor's Biography
Jorge Ruiz-Vanoye (Ed.)
Jorge Ruiz-Vanoye
is a Professor and Researcher at Universidad Politécnica de Pachuca (UPP), a National Researcher under the Secretaria de Ciencia, Humanidades, Tecnología e Innovación program, and an Adjunct Researcher at the National Laboratory of Autonomous Vehicles and Exoskeletons (LANAVEX). Additionally, he holds the title of Lecturer-level Researcher for the Agency for the Quality of the University System of Catalonia (Generalitat de Catalunya). His research interests include Smart Cities, Smart Water, Smart Education, Smart Government, Smart Healthcare, Smart Farming, Smart Energy, Smart Sports, Smart Food, Smart Tourism, Algorithmic Finance, Algorithmic Portfolio Management, Applications and Theory of Algorithms, Bio-inspired Algorithms, Combinatorial Optimization Problems, Compilers, Computational Intelligence, Computational Complexity Theory, Computational Financial Intelligence, Complexity of Algorithms, Complexity of Instances, Computational Statistics, Computer Networks, Computer Science Security, Cybercrimes, Data Mining, Education, Evolutionary Computation, Heuristic Optimization Techniques in Bioinformatics, Hybrid Evolutionary Algorithms, Hybrid Optimization Algorithms, Machine Learning, Meta-heuristics, Operations Research, Operations Management, Parallel & Distributed Computing, Production Planning and Logistics Optimization, Project Scheduling Problems, Software Engineering, and Transgenic Algorithms.
Ocotlan Díaz-Parra (Ed.)
Dra.
Diaz-Parra
is a Professor and Researcher at Universidad Politécnica de Pachuca (UPP), a National Researcher under the CONAHCYT program, and an Adjunct Researcher at the National Laboratory of Autonomous Vehicles and Exoskeletons (LANAVEX). His research interests include Smart Cities, Smart Water, Smart Education, Smart Government, Smart Healthcare, Smart Farming, Smart Energy, Smart Sports, Smart Food, Smart Tourism, Algorithmic Finance, Algorithmic Portfolio Management, Applications and Theory of Algorithms, Bio-inspired Algorithms, Combinatorial Optimization Problems, Compilers, Computational Intelligence, Computational Complexity Theory, Computational Financial Intelligence, Complexity of Algorithms, Complexity of Instances, Computational Statistics, Computer Networks, Computer Science Security, Cybercrimes, Data Mining, Education, Evolutionary Computation, Heuristic Optimization Techniques in Bioinformatics, Hybrid Evolutionary Algorithms, Hybrid Optimization Algorithms, Machine Learning, Meta-heuristics, Operations Research, Operations Management, Parallel & Distributed Computing, Production Planning and Logistics Optimization, Project Scheduling Problems, Software Engineering, and Transgenic Algorithms.
Eric Simancas-Acevedo (Ed.)
Eric Simancas Acevedo
(Phd. in Electro-communications), graduated from the Postgraduate Studies and Research Section (SEPI-ESIME Culhuacan) of the National Polytechnic Institute (IPN) in 2015; he had a postgraduate study stays in Tokyo, Japan 2001-2003; He is currently a Senior Research Professor and Posgraduate teacher at the Polytechnic University of Pachuca in Engineering and Graduate degrees. His research interests are: Signal and image processing, artificial intelligence, neuroengineering, adaptive filters, neural networks, fuzzy logic, stochastic models, embedded systems, machine learning, security and control systems based on biometric features and embedded systems.
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