Marine depth mapping algorithm based on the edge computing in Internet of things

Yang, Jiachen; Wen, Jiabao; Jiang, Bin; Lv, Zhihan; Sangaiah, Arun Kumar

doi:10.1016/j.jpdc.2017.12.016

Cited by 16 publications

(5 citation statements)

References 29 publications

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“…These issues have been the focus of research efforts worldwide. Yang et al [41] suggested a technique or method for rapidly determining the form of data gathered via the Internet of Things (IoT). It is extremely quick to compute the distribution of contour lines properly.…”

Section: Wave and Ocean Environment Monitoringmentioning

confidence: 99%

Research advancements in ocean environmental monitoring systems using wireless sensor networks: a review

2023

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The ocean environment monitoring system is of great significance to the researchers because the ocean is the storehouse of natural resources. It is critical to comprehend and assess the ocean's environmental conditions. Several studies have been conducted over the last several decades that use sophisticated information and communication techniques to ensure the ocean ecosystem. Wireless sensor networks (WSNs) are a promising technology to monitor the ocean environment, which delivers significant benefits such as enhanced accuracy and real-time observations. The advancements in sensor technology such as micro electromechanical systems (MEMS), integrated systems, distributed processing, wireless communications, and wireless sensor applications have contributed to the development of WSNs. This paper describes the utilization of WSN and analyzes the previous and existing project works and technologies used for ocean environment monitoring through WSNs, and also includes the MEMS sensor technology used for monitoring various ocean parameters such as ocean wave monitoring, water conductivity, temperature, and depth of ocean.

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Section: Wave and Ocean Environment Monitoringmentioning

confidence: 99%

Research advancements in ocean environmental monitoring systems using wireless sensor networks: a review

2023

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“…It integrates network, computing, storage, and application to provide edge intelligence service nearby. It can satisfy the key requirements of industry digitalization in agile connection, real-time business, data optimization, application intelligence, and security and privacy protection [25][26][27]. Cognitive computing on the edge for healthcare service robots can be processed by the robot without frequent communications with data centers [28].…”

Section: Edge Service Compositionmentioning

confidence: 99%

Research on Edge Service Composition Method Based on BAS Algorithm

Miao

2021

Computational Intelligence and Neuroscience

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Edge services are transferred data processing, application running, and implementation of some functional services from cloud central server to network edge server to provide services. Combined edge service can effectively reduce task computation in the cloud, shorten transmission distance of processing data, quickly decompose task of service request, and select the optimal edge service combination to provide service for users. BAS is an efficient intelligent optimization algorithm, which can achieve efficient optimization and neither need to know the specific form of function nor need gradient information. This paper designs an edge service composition model based on edge computing and proposes a method about edge service composition by BAS optimization algorithm. Our proposed method has obvious advantages in service composition efficiency compared with service composition method based on PSO or WPA heuristic algorithm. Compared with cloud service composition method, our proposed method has advantages of shorter service response time, low cost, and high quality of user experience.

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“…ere are various problems such as inconsistency with user needs and predefined definitions. Not only the sampling information but also the blank sample information and parallel sample information collected on-site need to be recorded, [26,27]. Considering the data itself, data mining usually requires 8 steps such as data cleaning, data transformation, data mining implementation process, pattern evaluation, and knowledge representation.…”

Section: Marine Environment Monitoring Systemmentioning

confidence: 99%

Marine Environment Monitoring Based on Virtual Reality and Fuzzy C-Means Clustering Algorithm

Zhu

Han

2021

Mobile Information Systems

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In modern society, with the rapid increase of population and the serious shortage of resources, the marine environment has been destroyed; there are also many people who go out to sea without permission, regardless of the legal constraints, fishing. This kind of behavior leads the marine environment to get worse and worse, so the real-time monitoring of the marine environment is very necessary. The main article marine environment monitoring, virtual reality technology, and fuzzy C-means clustering algorithm combine to improve the efficiency of monitoring and processing power of the data information. Through the application of virtual reality technology in the marine environment monitoring base and real-time simulation of the dynamics of the ocean, the monitoring personnel can understand the emergencies on the sea in time; the fuzzy C-means clustering algorithm is applied to the server receiving the data to classify the data. It is found in the experiment that when virtual reality technology and fuzzy C-means clustering algorithm are not used, the data of marine environment monitoring takes more than 1.3 s to return to the server, but, after applying two advanced technologies, the return efficiency is greatly improved, and the time consumed is less than 0.82 s. The results show that virtual reality technology and fuzzy C-means clustering algorithm can improve the efficiency of environmental monitoring, and through virtual reality technology, real-time monitoring of the marine environment can be achieved; in the absence of people out to sea, the actual situation on the sea can be clearly understood; and fuzzy C-means clustering algorithm can improve the speed of data processing, so that the monitoring personnel can solve the problem faster.

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Marine depth mapping algorithm based on the edge computing in Internet of things

Cited by 16 publications

References 29 publications

Research advancements in ocean environmental monitoring systems using wireless sensor networks: a review

Research advancements in ocean environmental monitoring systems using wireless sensor networks: a review

Research on Edge Service Composition Method Based on BAS Algorithm

Marine Environment Monitoring Based on Virtual Reality and Fuzzy C-Means Clustering Algorithm

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