Secure and Efficient Data Collection and Storage of IoT in Smart Ocean

Hu, Chunqiang; Pu, Yuwen; Yang, Feihong; Zhao, Ruifeng; Alrawais, Arwa; Xiang, Tao

doi:10.1109/jiot.2020.2988733

Cited by 61 publications

(20 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are problems in the costs of submerged systems, and the sea is still a very complex environment for accurate control. [210][211][212][213] Biodiversity Forests and natural territories can be improved with technology and non-invasive surveillance.…”

Section: Oceansmentioning

confidence: 99%

Application of IoT in Healthcare: Keys to Implementation of the Sustainable Development Goals

Verdejo-Espinosa

Ruiz

Mata

et al. 2021

Sensors

View full text Add to dashboard Cite

We live in complex times in the health, social, political, and energy spheres, and we must be aware of and implement new trends in intelligent social health systems powered by the Internet of Things (IoT). Sustainable development, energy efficiency, and public health are interrelated parameters that can transform a system or an environment for the benefit of people and the planet. The integration of sensors and smart devices should promote energy efficiency and ensure that sustainable development goals are met. This work is carried out according to a mixed approach, with a literature review and an analysis of the impact of the Sustainable Development Goals on the applications of the Internet of Things and smart systems. In the analysis of results, the following questions are answered about these systems and applications: a) Are IoT applications key to the improvement of people’s health and the environment? b) Are there research and case studies implemented in cities or territories that demonstrate the effectiveness of IoT applications and their benefits to public health? c) What sustainable development indicators and objectives can be assessed in the applications and projects analyzed?

show abstract

Section: Oceansmentioning

confidence: 99%

Application of IoT in Healthcare: Keys to Implementation of the Sustainable Development Goals

Verdejo-Espinosa

Ruiz

Mata

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…The real-time reporting for any irregularity to the concerned authority in educational environment, will help to improve the educational environment on global standards. The recent developments and utilization of IoT devices, mobile internet, Technologies like IoT; Fog Computing; and Cloud computing (IFC), Deep Learning and AI has changed the scenario of data perception, data transmission and information storage in many areas of life, including education sector [14]. In the present scenario by the use of IoT devices, it has become possible to sense and transmit various types of data in real-time.…”

Section: A Requirement and Contributionsmentioning

confidence: 99%

IoT Inspired Intelligent Monitoring and Reporting Framework for Education 4.0

et al. 2021

View full text Add to dashboard Cite

Education 4.0 contemplates the involvement of emerging technologies like IoT (Internet of Things), Fog and cloud computing. Ubiquitous real-time monitoring under the challenging environment of an educational institution is the key requirement for proper implementation of Education 4.0 around the world. Conspicuously, this research presents a novel monitoring and irregularity detection framework for educational institutions. In this research, acquisition of data while deploying IoT is being suggested in the comprehensive environs of the educational institutions. Pre-processing of acquired data for feature extraction is implemented using the Fog-Cloud nodes. Subsequently, the Temporal Chunk (TC)which is articulated with Temporal Data mining, is further employed to detect irregularities based on SoTL (Set of threshold limits)and HAA (Historical Adversity Approximation). Successively, Multi-Layered Bi-Directional Long Short Term Memory (M-Bi-LSTM) oriented irregularity prediction model is deployed. Furthermore, a fog-inspired alert generation and reporting module are employed for real-time reporting to notify the concerned stakeholder for in-time preventive action corresponding to predicted irregularity. To authenticate the proposed framework and to avoid the experimental implementation cost, the experimental simulations are performed. The experimental results verify that the proposed framework is capable to perform better in comparison to other contemporary decision-making methods for Delay Efficiency, Data Classification, Irregularity Prediction and System Stability. Moreover, the proposed framework can successfully estimate most of the irregularities in an educational environment and provide support for the proper implementation of Education 4.0 in a proficient and realistic manner.

show abstract

“…The computations are computationally intensive. However, as noted in Equation ( 6), the computationally intensive part which is the computation of Equation (7), is performed only once for each pixel. Then this computed value can be applied on any image to compute the image moments.…”

Section: Phft Computationmentioning

confidence: 99%

“…With growing speed of internet accessibility and ever increasing internet speed, the amount of data transfer has increased [1,2]. The transfer of data involved in many fields including medical, satellite data and internet of things applications [3][4][5][6][7]. Medical images are frequently transferred, uploaded and downloaded over the internet in telemedicine.…”

Section: Introductionmentioning

confidence: 99%

Application of a novel image moment computation in X‐ray and MRI image watermarking

Singh

Kumar

Ali

et al. 2020

IET Image Processing

View full text Add to dashboard Cite

Orthogonal polar image moments which are defined over a unit disk, are used often in watermarking applications. One such image moment is polar harmonic Fourier transformation (PHFT). The quality of the extracted watermark depends on the accuracy of the computed image moments. Various methods have already been used for the computation of the moments with varying degrees of accuracy. This study proposes application of a novel image moments computation method which is a synergy of analytic, and numerical techniques, to image watermarking. The computed moment results in a robust watermark extraction. The PHFT have rotation, and scaling invariance property, which allows the watermark to resist various geometric attacks. In addition to the geometric attacks the watermark has the capability to resist various signal processing attacks. The performance of the proposed watermarking scheme is performed with the methods used in recently published articles. The experimental results show that the proposed method has the better performance compared to other techniques, and has better capability to resist various attacks.

show abstract

Secure and Efficient Data Collection and Storage of IoT in Smart Ocean

Cited by 61 publications

References 42 publications

Application of IoT in Healthcare: Keys to Implementation of the Sustainable Development Goals

Application of IoT in Healthcare: Keys to Implementation of the Sustainable Development Goals

IoT Inspired Intelligent Monitoring and Reporting Framework for Education 4.0

Application of a novel image moment computation in X‐ray and MRI image watermarking

Contact Info

Product

Resources

About