Device discovery strategies for the IoT

Ccori, Pablo Calcina; Biase, Laisa C. C. De; Zuffo, Marcelo Knörich; Silva, Flávio Soares Corrêa da

doi:10.1109/isce.2016.7797388

Cited by 16 publications

(5 citation statements)

References 2 publications

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“…The processor(s) are responsible for executing instructions and performing calculations, while the storage devices are used to store data and programs. The networking equipment is used to connect the ASV to other devices and networks, such as satellite or cellular networks, and to enable communication with other ASVs or control centers [27,28].…”

Section: Degree Two: Remotely Controlled Ship With Seafarers On Boardmentioning

confidence: 99%

Use of the geospatial technologies and its implications in the maritime transport and logistics

Scarlat

Ioanid

Andrei

2023

The International Maritime Transport and Logistic Journal

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Section: Degree Two: Remotely Controlled Ship With Seafarers On Boardmentioning

confidence: 99%

Use of the geospatial technologies and its implications in the maritime transport and logistics

Scarlat

Ioanid

Andrei

2023

The International Maritime Transport and Logistic Journal

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“…In the context of Smart cities, several works discuss the problems related to obtain, maintain and expose a registry of the IoT devices that are available in the network, e.g. [28], [29], [30] and [31] The proposed solutions show that IoT registries can be efficiently maintained, aiming at optimising multiple requirements, such as energy efficiency, QoS, or security. Instead, in the aeronautical field, solutions exist to manage the dissemination of monitoring information in challenging environments, e.g.…”

Section: Computing Infrastructuresmentioning

confidence: 99%

An Outlook on the Future Marine Traffic Management System for Autonomous Ships

Martelli¹,

Virdis

Gotta

et al. 2021

IEEE Access

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In the shipping digitalisation process, the peak will be reached with the advent of a wholly autonomous and at the same time safe and reliable ship. Full autonomy could be obtained by two linked Artificial-Intelligence systems representing the ship navigator and the ship engineer that possess sensing and analysis skills, situational awareness, planning, and control capabilities. Many efforts have been made in developing onboard systems; however, the shore facilities are not ready yet to deal with these new technologies. The paper aims to present the innovative technologies and methodologies needed to develop a futuristic Vessel Traffic System. The proposed systems will aim at faultless data acquisition and processing, provide input to decision-making systems, and suggest evasive manoeuvre; to deal with hazards and systems failure without human intervention onboard. The system is composed of three different and interacting layers. The first is an artificially intelligent tool to detect and control autonomous ships, thanks to situation recognition and obstacle avoidance strategies. The second is an orchestration and management platform designed to coordinate the sensing/actuation infrastructure and the AI algorithms' results made available by multiple ships, mustering edge, and distributed computing techniques to fulfil the specific harsh requirements of the sea environment. The final part is a holistic guidance-navigation-control framework to manage autonomous ships' navigation in a crowded area. Eventually, a cyber-physical scenario, using both a ship digital-twin and a real model-scale ship, is suggested to test and validate the innovative system without the availability of a full-scale scenario.

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“…This discovery service can be centralized [ 61 ] and/or decentralized [ 62 ]. There are several proposals in the literature focused on this service [ 63 , 64 ]. In this work, it is supposed that a proper discovery service is running to maintain the set ⅅ updated.…”

Section: Distributed Computational Architecturementioning

confidence: 99%

Collaborative Working Architecture for IoT-Based Applications

Mora

Pont

Gil

et al. 2018

Sensors

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The new sensing applications need enhanced computing capabilities to handle the requirements of complex and huge data processing. The Internet of Things (IoT) concept brings processing and communication features to devices. In addition, the Cloud Computing paradigm provides resources and infrastructures for performing the computations and outsourcing the work from the IoT devices. This scenario opens new opportunities for designing advanced IoT-based applications, however, there is still much research to be done to properly gear all the systems for working together. This work proposes a collaborative model and an architecture to take advantage of the available computing resources. The resulting architecture involves a novel network design with different levels which combines sensing and processing capabilities based on the Mobile Cloud Computing (MCC) paradigm. An experiment is included to demonstrate that this approach can be used in diverse real applications. The results show the flexibility of the architecture to perform complex computational tasks of advanced applications.

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Device discovery strategies for the IoT

Cited by 16 publications

References 2 publications

Use of the geospatial technologies and its implications in the maritime transport and logistics

Use of the geospatial technologies and its implications in the maritime transport and logistics

An Outlook on the Future Marine Traffic Management System for Autonomous Ships

Collaborative Working Architecture for IoT-Based Applications

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