Processing of crowd-sourced data from an internet of floating things

Montella, Raffaele; Luccio, Diana Di; Marcellino, Livia; Galletti, Ardelio; Kosta, Sokol; Brizius, Alison; Foster, Ian

doi:10.1145/3150994.3150997

Cited by 8 publications

(7 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Again, some core elements of the analysis will be skimmed over, either due to protecting DockTech's proprietary technology, or when discussing MBES, skipping over what is considered general knowledge to keep this paper not unnecessarily lengthy. For further discussion, see (Montella et al, 2017;Stephens et al, 2020;Jia et al, 2022) For the sake of this paper, we shall divide the types of processing necessary into three categories:…”

Section: Data Processingmentioning

confidence: 99%

Evaluation of a crowd sourced bathymetric approach

Grinker¹,

Solomon²,

Hassin³

2022

IHR

View full text Add to dashboard Cite

Crowd-Sourced Bathymetry is the process of generating a harbor chart through collecting, enriching, processing, and aggregating depth (and other) measurements from a host of vessels, using standard navigation instruments, while engaged in routine maritime operations. This study explores the accuracy and limitations of one particular approach towards utilizing Crowd-Sourced data, comparing the results obtained from DockTech’s approach to that of a classic MBES survey. As DockTech is a for-profit startup that sells their product to various stakeholders in the maritime supply chain, a balance between protection of proprietary interest and scientific collaboration is necessary. As such, while specific details in regards to both chosen methodologies and their particular evaluations cannot be discussed, a general overview will be provided and the results of DockTech’s solution will be evaluated. This study is based on depth measurements collected by service vessels, active on a daily basis in Ashdod Port over the course of two months. Tug and Pilot boats use stand-alone GNSS navigation and navigation class Single Beam echo sounders for safety purposes when traversing the port and maneuvering between the wharfs. These depths, averaged over a relatively rough grid, were used to produce a chart of part of the port. Data from the service vessels did not include RTK GNSS navigation and hence ellipsoid referenced surveying techniques were not used in lieu of water level monitoring. This chart was then compared to another chart produced from a professional hydrographic survey of the port, using state of the art equipment and strict hydrographic control. The differences were then analyzed according to the latest edition of the IHO S-44 standards. Recommendations were suggested for some relatively simple measures which could enhance the accuracy achieved and the reliability of such a chart, at least for harbor maintenance purposes.

show abstract

Section: Data Processingmentioning

confidence: 99%

Evaluation of a crowd sourced bathymetric approach

Grinker¹,

Solomon²,

Hassin³

2022

IHR

View full text Add to dashboard Cite

show abstract

“…Moreover, some coastal areas present challenges for such traditional methods: for example, they might be too dangerous to be investigated using large ships. To overcome these limitations, crowdsourcing techniques such as the FairWind system that we developed previously [51] have been proposed. These methods can be used on small leisure vessels to collect data from their sensors, allowing ordinary citizens to contribute data of considerable importance for science, engineering, and management of natural resources.…”

Section: Leisure Vessels As Sensorsmentioning

confidence: 99%

“…In previous work, we developed an Android crowdsourcing application, FairWind, accessible in the Google Play Store [51]. This approach allowed for fast and easy deployment, but the Android operating system leads to limitations concerning the amount of memory that can be allocated, Garbage Collector management [52], and CPU utilization.…”

Section: Leisure Vessels As Sensorsmentioning

confidence: 99%

Workflow-based automatic processing for Internet of Floating Things crowdsourced data

Montella

Luccio

Marcellino

et al. 2019

Future Generation Computer Systems

Self Cite

View full text Add to dashboard Cite

Data from sensors incorporated into mobile devices, such as networked navigational sensors, can be used to capture detailed environmental information. We describe here a workflow and framework for using sensors on boats to construct unique new datasets of underwater topography (bathymetry). Starting with a large number of measurements of position, depth, etc., obtained from such an Internet of Floating Things, we illustrate how, with a specialized protocol, data can be communicated to cloud resources, even when using delayed, intermittent, or disconnected networks. We then propose a method for automatic sensor calibration based on a novel reputation approach. Sampled depth data are interpolated efficiently on a cloud computing platform in order to provide a continuously updated bathymetric database. Our prototype implementation uses the FACE-IT Galaxy workflow engine to manage network communication and exploits the computational power of GPGPUs in a virtualized cloud environment, working with a CUDA-parallel algorithm, for efficient data processing. We report on an initial evaluation involving data from a sailing vessel in Italian coastal waters.

show abstract

“…The application of this technique to the measurement of weather and sea state parameters has previously been limited to ferries, freight carriers, professional vessels, and cruise ships. In a previous work, we developed FairWind, a smart, cloud-enabled, multi-functional navigation system for leisure and professional vessels [22,25]. In this paper, we introduce DYNAMO, an infrastructure for collecting marine environmental data from a distributed sensor network carried by leisure vessels [24,21].…”

Section: Introductionmentioning

confidence: 99%

Security and Storage Issues in Internet of Floating Things Edge-Cloud Data Movement

Montella

Luccio

Kosta

et al. 2020

Parallel Processing and Applied Mathematics

Self Cite

View full text Add to dashboard Cite

Sensors and actuators became first class citizens in technologically pervasive urban environments. However, the full potential of data crowdsourcing is still unexploited in marine coastal areas, due to the challenging operational conditions, extremely unstable network connectivity and security issues in data movement. In this paper, we present the latest specification of our DYNAMO Transfer Protocol (DTP), a platform-independent data mover framework specifically designed for the Internet of Floating Things applications, where data collected on board of professional or leisure vessels are stored locally and then moved from the edge to the cloud. We evaluate the performance achieved by the DTP in data movement in a controlled environment.

show abstract

Processing of crowd-sourced data from an internet of floating things

Cited by 8 publications

References 42 publications

Evaluation of a crowd sourced bathymetric approach

Evaluation of a crowd sourced bathymetric approach

Workflow-based automatic processing for Internet of Floating Things crowdsourced data

Security and Storage Issues in Internet of Floating Things Edge-Cloud Data Movement

Contact Info

Product

Resources

About