LearningCity: Knowledge Generation for Smart Cities

• URL: http://arxiv.org/abs/2104.05286v1
• Date: Mon, 12 Apr 2021 08:31:10 GMT
• Title: LearningCity: Knowledge Generation for Smart Cities
• Authors: Dimitrios Amaxilatis, Georgios Mylonas, Evangelos Theodoridis, Luis Diez, Katerina Deligiannidou
• Abstract summary: We present LearningCity, our solution that has been validated over an existing smart city deployment in Santander. We discuss key challenges along with characteristic use cases, and report on our design and implementation, together with some preliminary results derived from combining large smart city datasets with machine learning.
• Score: 0.23624125155742054
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Although we have reached new levels in smart city installations and systems, efforts so far have focused on providing diverse sources of data to smart city services consumers while neglecting to provide ways to simplify making good use of them. In this context, one first step that will bring added value to smart cities is knowledge creation in smart cities through anomaly detection and data annotation, supported in both an automated and a crowdsourced manner. We present here LearningCity, our solution that has been validated over an existing smart city deployment in Santander, and the OrganiCity experimentation-as-a-service ecosystem. We discuss key challenges along with characteristic use cases, and report on our design and implementation, together with some preliminary results derived from combining large smart city datasets with machine learning.

Related papers

• LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation [60.920536939067524]
  We introduce LogiCity, the first simulator based on customizable first-order logic (FOL) for an urban-like environment with multiple dynamic agents. LogiCity models diverse urban elements using semantic and spatial concepts, such as IsAmbulance(X) and IsClose(X, Y) Key feature of LogiCity is its support for user-configurable abstractions, enabling customizable simulation complexities for logical reasoning.
  arXiv  Detail & Related papers  (2024-11-01T17:59:46Z)
• 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)
• MatrixCity: A Large-scale City Dataset for City-scale Neural Rendering and Beyond [69.37319723095746]
  We build a large-scale, comprehensive, and high-quality synthetic dataset for city-scale neural rendering researches. We develop a pipeline to easily collect aerial and street city views, accompanied by ground-truth camera poses and a range of additional data modalities. The resulting pilot dataset, MatrixCity, contains 67k aerial images and 452k street images from two city maps of total size $28km2$.
  arXiv  Detail & Related papers  (2023-09-28T16:06:02Z)
• Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks [82.82866901799565]
  We build a new set of multimodal remote sensing benchmark datasets (including hyperspectral, multispectral, SAR) for the study purpose of the cross-city semantic segmentation task. Beyond the single city, we propose a high-resolution domain adaptation network, HighDAN, to promote the AI model's generalization ability from the multi-city environments. HighDAN is capable of retaining the spatially topological structure of the studied urban scene well in a parallel high-to-low resolution fusion fashion.
  arXiv  Detail & Related papers  (2023-09-26T23:55:39Z)
• Smart Cities and Digital Twins in Lower Austria [1.7349132949643813]
  The project Smart Cities aNd Digital Twins in Lower Austria (SCiNDTiLA) extends the state of the art of research in several contributing disciplines. It uses the foundations of complexity theory and computational social science methods to develop a digital-twin-based smart city model. The outcomes will be translated into a roadmap highlighting methodologies, guidelines and policy recommendations for tackling societal challenges in smart cities.
  arXiv  Detail & Related papers  (2023-07-13T13:31:25Z)
• 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)
• 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)
• 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)
• Exploring the Smart City Adoption Process: Evidence from the Belgian urban context [1.3764085113103222]
  We consider a Smart City as a socio-technical system where the interplay between technologies and users ensures the sustainable development of smart city initiatives. The adoption of a Smart City required a participative approach where users are involved during the adoption process to joint optimise both systems.
  arXiv  Detail & Related papers  (2021-01-14T15:34:50Z)
• From elusive to ubiquitous: understanding smart cities [0.0]
  This paper reviews the existing definitions, as well as its architectures, based on an in-depth literature review of relevant studies and research fields alike. We also provide our own definition of the smart city concept.
  arXiv  Detail & Related papers  (2020-04-24T18:48:55Z)
• Smart City IoT Services Creation through Large Scale Collaboration [0.13048920509133805]
  Single-function components that are re-usable by other city services are packaged and published as standalone components. We identify 15 atomic services addressing smart city challenges in data analytics, data evaluation, data integration, data validation, and visualization. The resulting atomic services also generate a side market for smart city solutions, allowing expertise and know-how to be re-used by different stakeholders.
  arXiv  Detail & Related papers  (2020-03-10T16:43:13Z)

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.