scholarly journals Design and Testing of AUV Docking Modules for a Renewably Powered Offshore AUV Servicing Platform

2020 ◽  
Author(s):  
Maha N. Haji ◽  
Jimmy Tran ◽  
Johannes Norheim ◽  
Olivier L. de Weck
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Low Earth Orbit ◽  
Prototype System ◽  
Satellite Constellations ◽  
Processing Power ◽  
Battery Capacity ◽  
High Bandwidth ◽  
New Generation ◽  
Design And Testing ◽  
Data Latency

Abstract Autonomous Underwater Vehicle (AUV) missions are limited in range and duration by the vehicle’s battery capacity, and sensor payloads are limited by the processing power onboard which is also restricted by the vehicle’s battery capacity. Furthermore, the power consumption of a vehicle’s acoustic system limits the possibility of substantial data transmission, requiring the AUV be retrieved to download most data. The Platform for Expanding AUV exploRation to Longer ranges (PEARL), described in this paper, aims to extend the range and endurance of AUVs while reducing data latency and operating costs. PEARL is an integrated autonomous floating servicing station that utilizes renewable energy to simultaneously provide AUV battery recharging and data uplink via new generation high-bandwidth low-Earth orbit satellite constellations. This paper details the design and testing of two potential AUV docking modules of the PEARL system. The modules are uniquely located near the ocean surface, an energetic environment that presents a particular set of challenges for AUV docking. The results will be used to inform the design of a prototype system to be tested in an ocean setting.

Mobile Video Cloud Networks

2014 ◽  
pp. 157-182 ◽  
Author(s):  
Qi Wang ◽  
James Nightingale ◽  
Runpeng Wang ◽  
Naeem Ramzan ◽  
Christos Grecos ◽  
...  
Keyword(s):  
Cloud Computing ◽  
High Performance ◽  
Mobile Cloud ◽  
Mobile Video ◽  
Important Research ◽  
Multimedia Computing ◽  
Processing Power ◽  
Battery Capacity ◽  
Coding Standards ◽  
Cloud Technologies

Mobile multimedia computing has become ubiquitous in everyday life. However, mobile device users involved in resource-demanding visual applications such as video streaming often encounter performance degradations due to their mobile devices’ intrinsic constraints in processing power, storage, and battery capacity. Cloud computing can be explored to circumvent such problems thanks to the vast resources available in the cloud. Mobile video cloud computing has thus emerged as an important research and development topic to achieve high-performance, innovative networked video applications. This chapter discusses the recent advances in mobile video cloud technologies and applications. The authors investigate mobile video cloud systems starting with the various mobile cloud paradigms and then present challenges and solutions of mobile video cloud management for mobility, context, and security. Furthermore, the authors examine the latest video coding standards and explore methods based on parallelisation and scalability for their optimised application over mobile clouds, followed by three highlighted mobile cloud video applications including streaming, transcoding, and gaming. Finally, future directions in this area are envisioned.

Fog Computing and Virtualization

2018 ◽  
pp. 53-67
Author(s):  
Siddhartha Duggirala
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Main Concern ◽  
Time Data ◽  
Human Machine Interaction ◽  
Processing Power ◽  
New Generation ◽  
And Storage ◽  
Virtual Services ◽  
Machine Interaction

The essence of cloud computing is moving out the processing from the local systems to remote systems. Cloud is an umbrella of physical/virtual services/resources easily accessible over the internet. With more companies adopting cloud either fully through public cloud or hybrid model, the challenges in maintaining a cloud capable infrastructure is also increasing. About 42% of CTOs say that security is their main concern for moving into cloud. Another problem, which is mainly problem with infrastructure, is the connectivity issue. The datacenter could be considered as the backbone of cloud computing architecture. Handling this new generation of requirements of volume, variety, and velocity in IoT data requires us to evaluate the tools and technologies. As the processing power and storage capabilities of the end devices like mobile phones, routers, sensor hubs improve, we can increase leverage these resources to improve your quality and reliability of services. Applications of fog computing is as diverse as IoT and cloud computing itself. What IoT and fog computing have in common is to monitor and analyse real-time data from network connected things and acting on them. Machine-to-machine coordination or human-machine interaction can be a part of this action. This chapter explores fog computing and virtualization.

Long-term collision risk prediction for low earth orbit satellite constellations

2000 ◽  
Vol 47 (2-9) ◽  
pp. 707-717 ◽  
Author(s):  
R. Walker ◽  
P.H. Stokes ◽  
J.E. Wilkinson ◽  
G.G. Swinerd
Keyword(s):  
Risk Prediction ◽  
Low Earth Orbit ◽  
Earth Orbit ◽  
Collision Risk ◽  
Satellite Constellations ◽  
Orbit Satellite ◽  
Low Earth Orbit Satellite

scholarly journals A Mobile-Based Prototype for Skin Lesion Analysis: Towards a Patient-Oriented Design Approach

2013 ◽  
Vol 9 (S8) ◽  
pp. 27 ◽  
Author(s):  
Luís Rosado ◽  
Maria João Vasconcelos ◽  
Márcia Ferreira
Keyword(s):  
Skin Lesion ◽  
Active Role ◽  
Skin Lesions ◽  
Self Monitoring ◽  
Promising Tool ◽  
Processing Power ◽  
Skin Cancers ◽  
Lesion Analysis ◽  
New Generation

The wide spreading of the new generation of smartphones, with significant improvements in terms of image acquisition and processing power, is opening up the possibility of new approaches for skin lesion monitoring. Mobile Teledermatology appears nowadays as a promising tool with the potential to empower patients to adopt an active role in managing their own skin health status, while facilitates the early diagnosis of skin cancers. The main objective of this work is to create a mobile-based prototype for skin lesions analysis with patient-oriented features and functionalities. The presented self-monitoring system collects, processes and storages information of skin lesions through the automatic extraction and classification of specific visual features. The algorithms used to extract and classify these features are briefly described, as well as the overall system architecture and functionalities.

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