A3ME - An Agent-Based Middleware Approach for Mixed Mode Environments

Herzog, Arthur; Jacobi, Daniel; Buchmann, Alejandro

doi:10.1109/ubicomm.2008.78

Cited by 36 publications

(21 citation statements)

References 5 publications

(4 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In this work, the authors propose an ontology for traffic management that combines both traffic concepts and general sensor ontology A3ME [7]. The added concepts are specializations of position, distance and acceleration sensor classes, and the different actions that take place in the car motions.…”

Section: Related Workmentioning

confidence: 99%

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

Fernández

Ito

2017

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARYIntelligent transportation systems (ITS) are a set of technological solutions used to improve the performance and safety of road transportation. Since one of the most important information sources on ITS are sensors, the integration and sharing the sensor data become a big challenging problem in the application of sensor networks to these systems. In order to make full use of the sensor data, is crucial to convert the sensor data into semantic data, which can be understood by computers. In this work, we propose to use the SSN ontology to manage the sensor information in an intelligent transportation architecture. The system was tested in a traffic light settings application, allowing to predict and avoid traffic accidents, and also for the routing optimization.

show abstract

Section: Related Workmentioning

confidence: 99%

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

Fernández

Ito

2017

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

show abstract

“…The ontologies of specific application are CESN [5], A3ME [6], SWAMO [7], MMI [8], OOSTethys [9] and ISTAR [10] etc.…”

Section: Ontologies Before Ssn Ontologymentioning

confidence: 99%

A Survey on Semantic Sensor Web: Sensor Ontology, Mapping and Query

Zhang¹,

Li²

2015

IJUNESST

View full text Add to dashboard Cite

show abstract

“…Existing ontologies structures like the SWEET Nasa ontology [34] and A3ME ontology [32] have been refined to fit our needs. The actual ontology describes the vehicles knowledge in terms of capabilities, conditions and restriction of uses, environment, vehicles structure and so on.…”

Section: B Space Exploration In the Context Of Multi-vehicles Missionsmentioning

confidence: 99%

“…• The A3ME [32] ontology defines heterogeneous mobile devices in order to allow communication interoperability,…”

Section: Introductionmentioning

confidence: 99%

Towards an Ontology for Autonomous Robots

Paull

Séverac

Raffo

et al. 2012

2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

Robots and Systems (IROS), pp. 1359-1364, 2012 Towards an ontology for autonomous robots Paull, Liam; Severac, Gaetan; Raffo, Guilherme V.; Angel, Julian Mauricio; Boley, Harold; Durst, Phillip J.; Gray, Wendell; Habib, Maki; Nguyen, Bao; Ragavan, S. Veera; Saeedi G., Sajad; Sanz, Ricardo; Seto, Mae; Stefanovski, Aleksandar; Trentini, Michael; Li, Howard Abstract-The IEEE RAS Ontologies for Robotics and Automation Working Group is dedicated to developing a methodology for knowledge representation and reasoning in robotics and automation. As part of this working group, the Autonomous Robots sub-group is tasked with developing ontology modules for autonomous robots. This paper describes the work in progress on the development of ontologies for autonomous systems. For autonomous systems, the focus is on the cooperation, coordination, and communication of multiple unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and autonomous underwater vehicles (AUVs). At the global mission level, the system ontologies must be able to model entities and relationship of multiple autonomous systems. At the individual system level, the ontologies must model the decision-making ability, control strategies, sensing abilities, map building, environment perception, motion planning, communication, autonomous behaviors and so on. The ontologies serve as a framework for working out concepts of employment with multiple vehicles for a variety of operational scenarios with emphasis on collaborative and cooperative missions.

show abstract

A3ME - An Agent-Based Middleware Approach for Mixed Mode Environments

Cited by 36 publications

References 5 publications

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

A Survey on Semantic Sensor Web: Sensor Ontology, Mapping and Query

Towards an Ontology for Autonomous Robots

Contact Info

Product

Resources

About