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Related Concept Videos

Design Example: Sustainability in Concrete Building01:26

Design Example: Sustainability in Concrete Building

As the construction industry moves towards more eco-friendly practices, concrete's adaptability and its ability to incorporate sustainable features make it a key material in the drive towards greener building solutions.
There are multiple approaches to achieve sustainability in a commercial concrete building. For instance, construct a concrete parking area under the building, utilizing pervious concrete paver blocks in open areas to facilitate rainwater collection through an underground cistern.
Introduction to GIS01:28

Introduction to GIS

Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...
Creative Thinking01:25

Creative Thinking

Creative thinking encompasses innovative and unconventional methods for addressing challenges, often leading to groundbreaking solutions. Instead of focusing solely on enhancing existing systems, such as increasing smartphone battery capacity, creative thinking might inspire advancements like energy-efficient batteries or processors that minimize power consumption. This multidimensional approach underscores the importance of exploring novel pathways to innovation.
Divergent thinking is the...
Sustainable Development01:43

Sustainable Development

As the human population continues to grow and use resources, we must be mindful of our planet’s natural limits. Sustainable development provides a pathway to maintain and improve human life now while also ensuring that future generations will have the resources that they need. The long-term success of sustainability efforts rests on understanding the interplay between human actions and ecological systems.
Thematic Layering in GIS01:30

Thematic Layering in GIS

In the past, planning projects such as schools or public facilities required extensive manual effort to gather and compile data. Information such as property boundaries, soil characteristics, road networks, zoning regulations, and flood zones had to be sourced individually from courthouses, utility providers, and registry offices. Assembling these datasets into a coherent format often took several months, delaying project timelines.The introduction of Geographic Information Systems (GIS)...
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...

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Related Experiment Videos

Editorial: Smart Cities, Innovating in the Transformation of Urban Environments.

Diego Rossit1, Sergio Nesmachnow2, Luis Hernández Callejo3

  • 1Department of Engineering, INMABB, Universidad Nacional del Sur (UNS)-CONICET, Bahía Blanca, Argentina.

Mathematical Biosciences and Engineering : MBE
|July 14, 2026
PubMed
Summary

This special issue showcases smart city innovations using mathematical modeling and machine learning for urban systems. Research impacts environmental engineering, transportation, and public health through data-driven solutions.

Keywords:
Industry 5.0deep learningmachine learningmathematical modelingoptimizationpublic healthsmart citiesurban sustainability

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Area of Science:

  • Urban Science
  • Data Science
  • Engineering

Background:

  • Smart cities integrate technology to improve urban living.
  • Complex urban systems require advanced analytical methods for effective management.
  • Existing research often lacks quantitative rigor and data-driven decision support.

Purpose of the Study:

  • To present original research on smart city innovations.
  • To apply mathematical modeling, optimization, machine learning, and deep learning to urban challenges.
  • To address critical issues in designing, monitoring, and operating smart urban systems.

Main Methods:

  • Mathematical modeling and optimization techniques.
  • Machine learning and deep learning algorithms.
  • Rigorous quantitative methodologies and data-driven analysis.

Main Results:

  • Contributions span environmental engineering, intelligent transportation, and urban mobility.
  • Demonstrated impact on ecological integrity, public health, and population well-being.
  • Provided context within the broader smart city research landscape.

Conclusions:

  • Advanced computational techniques are crucial for smart city development.
  • Data-driven decision support enhances urban system performance and sustainability.
  • This research aligns with the interdisciplinary focus of Mathematical Biosciences and Engineering.