The Hitchhiker's Guide to Fused Twins: A Review of Access to Digital
Twins in situ in Smart Cities
- URL: http://arxiv.org/abs/2202.07104v2
- Date: Wed, 8 Jun 2022 16:56:47 GMT
- Title: The Hitchhiker's Guide to Fused Twins: A Review of Access to Digital
Twins in situ in Smart Cities
- Authors: Jascha Gr\"ubel and Tyler Thrash and Leonel Aguilar and Michal
Gath-Morad and Julia Chatain and Robert W. Sumner and Christoph H\"olscher
and Victor R. Schinazi
- Abstract summary: This paper reviews Digital Twins (DTs) and Situated Analytics as the foundations of Fused Twins (FTs)
DTs represent their Physical Twin (PT) in the real world via models, simulations, (remotely) sensed data, context awareness, and interactions.
We advance the concept of embedding the DT into the PT through Situated Analytics to form Fused Twins (FTs)
- Score: 2.2515303891664358
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Smart Cities already surround us, and yet they are still incomprehensibly far
from directly impacting everyday life. While current Smart Cities are often
inaccessible, the experience of everyday citizens may be enhanced with a
combination of the emerging technologies Digital Twins (DTs) and Situated
Analytics. DTs represent their Physical Twin (PT) in the real world via models,
simulations, (remotely) sensed data, context awareness, and interactions.
However, interaction requires appropriate interfaces to address the complexity
of the city. Ultimately, leveraging the potential of Smart Cities requires
going beyond assembling the DT to be comprehensive and accessible. Situated
Analytics allows for the anchoring of city information in its spatial context.
We advance the concept of embedding the DT into the PT through Situated
Analytics to form Fused Twins (FTs). This fusion allows access to data in the
location that it is generated in an embodied context that can make the data
more understandable. Prototypes of FTs are rapidly emerging from different
domains, but Smart Cities represent the context with the most potential for FTs
in the future. This paper reviews DTs, Situated Analytics, and Smart Cities as
the foundations of FTs. Regarding DTs, we define five components (Physical,
Data, Analytical, Virtual, and Connection environments) that we relate to
several cognates (i.e., similar but different terms) from existing literature.
Regarding Situated Analytics, we review the effects of user embodiment on
cognition and cognitive load. Finally, we classify existing partial examples of
FTs from the literature and address their construction from Augmented Reality,
Geographic Information Systems, Building/City Information Models, and DTs and
provide an overview of future direction
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) - Can-Do! A Dataset and Neuro-Symbolic Grounded Framework for Embodied Planning with Large Multimodal Models [85.55649666025926]
We introduce Can-Do, a benchmark dataset designed to evaluate embodied planning abilities.
Our dataset includes 400 multimodal samples, each consisting of natural language user instructions, visual images depicting the environment, state changes, and corresponding action plans.
We propose NeuroGround, a neurosymbolic framework that first grounds the plan generation in the perceived environment states and then leverages symbolic planning engines to augment the model-generated plans.
arXiv Detail & Related papers (2024-09-22T00:30:11Z) - Smart City Digital Twin Framework for Real-Time Multi-Data Integration
and Wide Public Distribution [2.864893907775703]
Digital Twins are digital replica of real entities and are becoming fundamental tools to monitor and control the status of entities.
Digital Twins are becoming fundamental tools to monitor and control the status of entities.
Snap4City platform is released as open-source, and made available through GitHub and as docker compose.
arXiv Detail & Related papers (2023-09-23T14:53:04Z) - Enabling Spatial Digital Twins: Technologies, Challenges, and Future
Research Directions [13.210510790794006]
A Digital Twin (DT) is a virtual replica of a physical object or system, created to monitor, analyze, and optimize its behavior and characteristics.
A Spatial Digital Twin (SDT) is a specific type of digital twin that emphasizes the geospatial aspects of the physical entity.
We are the first to systematically analyze different spatial technologies relevant to building an SDT in layered approach.
arXiv Detail & Related papers (2023-06-11T06:28:44Z) - A New Era of Mobility: Exploring Digital Twin Applications in Autonomous
Vehicular Systems [0.0]
Digital twins (DTs) are virtual representations of physical objects or processes that can collect information from the real environment to represent, validate, and replicate the physical twin's present and future behavior.
DTs are becoming increasingly prevalent in a variety of fields, including manufacturing, automobiles, medicine, smart cities, and other related areas.
We addressed DTs and their essential characteristics, emphasized on accurate data collection, real-time analytics, and efficient simulation capabilities, while highlighting their role in enhancing performance and reliability.
arXiv Detail & Related papers (2023-05-09T06:39:57Z) - IDD-3D: Indian Driving Dataset for 3D Unstructured Road Scenes [79.18349050238413]
Preparation and training of deploy-able deep learning architectures require the models to be suited to different traffic scenarios.
An unstructured and complex driving layout found in several developing countries such as India poses a challenge to these models.
We build a new dataset, IDD-3D, which consists of multi-modal data from multiple cameras and LiDAR sensors with 12k annotated driving LiDAR frames.
arXiv Detail & Related papers (2022-10-23T23:03:17Z) - TRoVE: Transforming Road Scene Datasets into Photorealistic Virtual
Environments [84.6017003787244]
This work proposes a synthetic data generation pipeline to address the difficulties and domain-gaps present in simulated datasets.
We show that using annotations and visual cues from existing datasets, we can facilitate automated multi-modal data generation.
arXiv Detail & Related papers (2022-08-16T20:46:08Z) - 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) - VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and
Policy Learning for Autonomous Vehicles [131.2240621036954]
We present VISTA, an open source, data-driven simulator that integrates multiple types of sensors for autonomous vehicles.
Using high fidelity, real-world datasets, VISTA represents and simulates RGB cameras, 3D LiDAR, and event-based cameras.
We demonstrate the ability to train and test perception-to-control policies across each of the sensor types and showcase the power of this approach via deployment on a full scale autonomous vehicle.
arXiv Detail & Related papers (2021-11-23T18:58:10Z) - Embodied AI-Driven Operation of Smart Cities: A Concise Review [3.441021278275805]
Embodied AI focuses on learning through interaction with the surrounding environment.
We will go through its definitions, its characteristics, and its current achievements along with different algorithms, approaches, and solutions.
We will then explore all the available simulators and 3D interactable databases that will make the research in this area feasible.
arXiv Detail & Related papers (2021-08-22T19:14:59Z) - Injecting Knowledge in Data-driven Vehicle Trajectory Predictors [82.91398970736391]
Vehicle trajectory prediction tasks have been commonly tackled from two perspectives: knowledge-driven or data-driven.
In this paper, we propose to learn a "Realistic Residual Block" (RRB) which effectively connects these two perspectives.
Our proposed method outputs realistic predictions by confining the residual range and taking into account its uncertainty.
arXiv Detail & Related papers (2021-03-08T16:03:09Z)
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.