14,645 research outputs found
Multi-Paradigm Reasoning for Access to Heterogeneous GIS
Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn
the web into a geospatial web services enabled place. Mediation
architectures like VirGIS overcome syntactical and semantical heterogeneity
between several distributed sources. On mobile devices,
however, this kind of solution is not suitable, due to limitations,
mostly regarding bandwidth, computation power, and available storage
space. The aim of this paper is to present a solution for providing
powerful reasoning mechanisms accessible from mobile applications
and involving data from several heterogeneous sources.
By adapting contents to time and location, mobile web information
systems can not only increase the value and suitability of the
service itself, but can substantially reduce the amount of data delivered
to users. Because many problems pertain to infrastructures
and transportation in general and to way finding in particular, one
cornerstone of the architecture is higher level reasoning on graph
networks with the Multi-Paradigm Location Language MPLL. A
mediation architecture is used as a âgraph providerâ in order to
transfer the load of computation to the best suited component â
graph construction and transformation for example being heavy on
resources. Reasoning in general can be conducted either near the
âsourceâ or near the end user, depending on the specific use case.
The concepts underlying the proposal described in this paper are
illustrated by a typical and concrete scenario for web applications
Natural Language based Context Modeling and Reasoning with LLMs: A Tutorial
Large language models (LLMs) have become phenomenally surging, since
2018--two decades after introducing context-awareness into computing systems.
Through taking into account the situations of ubiquitous devices, users and the
societies, context-aware computing has enabled a wide spectrum of innovative
applications, such as assisted living, location-based social network services
and so on. To recognize contexts and make decisions for actions accordingly,
various artificial intelligence technologies, such as Ontology and OWL, have
been adopted as representations for context modeling and reasoning. Recently,
with the rise of LLMs and their improved natural language understanding and
reasoning capabilities, it has become feasible to model contexts using natural
language and perform context reasoning by interacting with LLMs such as ChatGPT
and GPT-4. In this tutorial, we demonstrate the use of texts, prompts, and
autonomous agents (AutoAgents) that enable LLMs to perform context modeling and
reasoning without requiring fine-tuning of the model. We organize and introduce
works in the related field, and name this computing paradigm as the LLM-driven
Context-aware Computing (LCaC). In the LCaC paradigm, users' requests, sensors
reading data, and the command to actuators are supposed to be represented as
texts. Given the text of users' request and sensor data, the AutoAgent models
the context by prompting and sends to the LLM for context reasoning. LLM
generates a plan of actions and responds to the AutoAgent, which later follows
the action plan to foster context-awareness. To prove the concepts, we use two
showcases--(1) operating a mobile z-arm in an apartment for assisted living,
and (2) planning a trip and scheduling the itinerary in a context-aware and
personalized manner.Comment: Under revie
Interactions of technology and society: Impacts of improved airtransport. A study of airports at the grass roots
The feasibility of applying a particular conception of technology and social change to specific examples of technological development was investigated. The social and economic effects of improved airport capabilities on rural communities were examined. Factors which led to the successful implementation of a plan to construct sixty small airports in Ohio are explored and implications derived for forming public policies, evaluating air transportation development, and assessing technology
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent âdevicesâ, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew âcognitive devicesâ are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
Can Urban Air Mobility become reality? Opportunities, challenges and selected research results
Urban Air Mobility (UAM) is a new air transportation system for passengers
and cargo in urban environments, enabled by new technologies and integrated
into multimodal transportation systems. The vision of UAM comprises the mass
use in urban and suburban environments, complementing existing transportation
systems and contributing to the decarbonization of the transport sector.
Initial attempts to create a market for urban air transportation in the last
century failed due to lack of profitability and community acceptance.
Technological advances in numerous fields over the past few decades have led to
a renewed interest in urban air transportation. UAM is expected to benefit
users and to also have a positive impact on the economy by creating new markets
and employment opportunities for manufacturing and operation of UAM vehicles
and the construction of related ground infrastructure. However, there are also
concerns about noise, safety and security, privacy and environmental impacts.
Therefore, the UAM system needs to be designed carefully to become safe,
affordable, accessible, environmentally friendly, economically viable and thus
sustainable. This paper provides an overview of selected key research topics
related to UAM and how the German Aerospace Center (DLR) contributed to this
research in the project "HorizonUAM - Urban Air Mobility Research at the German
Aerospace Center (DLR)". Selected research results that support the realization
of the UAM vision are briefly presented.Comment: 20 pages, 7 figures, project HorizonUA
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