From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities

• URL: http://arxiv.org/abs/2306.04653v1
• Date: Tue, 6 Jun 2023 10:22:43 GMT
• Title: From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities
• Authors: Tiago Dias, Tiago Fonseca, Jo\~ao Vitorino, Andreia Martins, Sofia Malpique and Isabel Pra\c{c}a
• Abstract summary: This work introduces an intelligent city management system that provides a data-driven approach to three use cases. A case study in Aveiro City demonstrates the system's effectiveness in generating actionable insights.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The emergence of smart cities demands harnessing advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) and promises to unlock cities' potential to become more sustainable, efficient, and ultimately livable for their inhabitants. This work introduces an intelligent city management system that provides a data-driven approach to three use cases: (i) analyze traffic information to reduce the risk of traffic collisions and improve driver and pedestrian safety, (ii) identify when and where energy consumption can be reduced to improve cost savings, and (iii) detect maintenance issues like potholes in the city's roads and sidewalks, as well as the beginning of hazards like floods and fires. A case study in Aveiro City demonstrates the system's effectiveness in generating actionable insights that enhance security, energy efficiency, and sustainability, while highlighting the potential of AI and IoT-driven solutions for smart city development.

Related papers

• MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility [52.0930915607703]
  Recent advances in Robotics and Embodied AI make public urban spaces no longer exclusive to humans. Micromobility enabled by AI for short-distance travel in public urban spaces plays a crucial component in the future transportation system. We present MetaUrban, a compositional simulation platform for the AI-driven urban micromobility research.
  arXiv  Detail & Related papers  (2024-07-11T17:56:49Z)
• Wireless Crowd Detection for Smart Overtourism Mitigation [50.031356998422815]
  This chapter describes a low-cost approach to monitoring overtourism based on mobile devices' wireless activity. The crowding sensors count the number of surrounding mobile devices, by detecting trace elements of wireless technologies. They run detection programs for several technologies, and fingerprinting analysis results are only stored locally in an anonymized database.
  arXiv  Detail & Related papers  (2024-02-14T13:20:24Z)
• Exploring IoT in Smart Cities: Practices, Challenges and Way Forward [0.0]
  Internet of things (IoT) technology has revolutionized urban living, offering immense potential for smart cities in which smart home, smart infrastructure, and smart industry are essential aspects that contribute to the development of intelligent urban ecosystems. The integration of smart home technology raises concerns regarding data privacy and security, while smart infrastructure implementation demands robust networking and interoperability solutions. This research paper offers a systematic literature review of published research in the field of IoT in smart cities including 55 relevant primary studies that have been published in reputable journals and conferences.
  arXiv  Detail & Related papers  (2023-08-25T19:23:33Z)
• Intelligent Traffic Monitoring with Hybrid AI [78.65479854534858]
  We introduce HANS, a neuro-symbolic architecture for multi-modal context understanding. We show how HANS addresses the challenges associated with traffic monitoring while being able to integrate with a wide range of reasoning methods.
  arXiv  Detail & Related papers  (2022-08-31T17:47:22Z)
• Smart City Intersections: Intelligence Nodes for Future Metropolises [8.690266225071772]
  Traffic intersections are the most suitable locations for the deployment of computing, communications, and intelligence services for smart cities of the future. This paper focuses on high-bandwidth, low-latency applications, and in that context it describes: (i) system design considerations for smart city intersection intelligence nodes; (ii) key technological components including sensors, networking, edge computing, low latency design, and AI-based intelligence; and (iii) applications such as privacy preservation, cloud-connected vehicles, a real-time "radar-screen", traffic management, and monitoring of pedestrian behavior during pandemics.
  arXiv  Detail & Related papers  (2022-05-03T17:22:57Z)
• IoT-based Route Recommendation for an Intelligent Waste Management System [61.04795047897888]
  This work proposes an intelligent approach to route recommendation in an IoT-enabled waste management system given spatial constraints. Our solution is based on a multiple-level decision-making process in which bins' status and coordinates are taken into account.
  arXiv  Detail & Related papers  (2022-01-01T12:36:22Z)
• Explainable, automated urban interventions to improve pedestrian and vehicle safety [0.8620335948752805]
  This paper combines public data sources, large-scale street imagery and computer vision techniques to approach pedestrian and vehicle safety. The steps involved in this pipeline include the adaptation and training of a Residual Convolutional Neural Network to determine a hazard index for each given urban scene. The outcome of this computational approach is a fine-grained map of hazard levels across a city, and an identify interventions that might simultaneously improve pedestrian and vehicle safety.
  arXiv  Detail & Related papers  (2021-10-22T09:17:39Z)
• Data Analytics for Smart cities: Challenges and Promises [3.1498833540989413]
  The goal of this study is to provide a comprehensive survey of data analytics in smart cities. In this paper, we aim to focus on one of the smart cities important branches, namely Smart Mobility. Intelligent decision-making systems in smart mobility offer many advantages such as saving energy, relaying city traffic, and more importantly, reducing air pollution by offering real-time useful information and imperative knowledge.
  arXiv  Detail & Related papers  (2021-09-12T18:33:24Z)
• Multi-Layered Diagnostics for Smart Cities [1.0828616610785522]
  Smart cities use technology to improve traffic patterns, energy distribution, air quality and more. The elements of a smart city can increase the convenience for its citizens, by integrating IT technology into many aspects of citizen interaction. Actual deployment cases exist in U.S., Europe, Singapore, and South Korea.
  arXiv  Detail & Related papers  (2021-07-20T06:58:11Z)
• AI in Smart Cities: Challenges and approaches to enable road vehicle automation and smart traffic control [56.73750387509709]
  SCC ideates on a data-centered society aiming at improving efficiency by automating and optimizing activities and utilities. This paper describes AI perspectives in SCC and gives an overview of AI-based technologies used in traffic to enable road vehicle automation and smart traffic control.
  arXiv  Detail & Related papers  (2021-04-07T14:31:08Z)
• Smart Urban Mobility: When Mobility Systems Meet Smart Data [55.456196356335745]
  Cities around the world are expanding dramatically, with urban population growth reaching nearly 2.5 billion people in urban areas and road traffic growth exceeding 1.2 billion cars by 2050. The economic contribution of the transport sector represents 5% of the GDP in Europe and costs an average of US $482.05 billion in the U.S.
  arXiv  Detail & Related papers  (2020-05-09T13:53:01Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.