CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

A Review on Various IOT Analytics Techniques for Bridge Failure Detection in Fog Computing

by Suneha Amar, Pankaj Deep Kaur
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 169 - Number 1
Year of Publication: 2017
Authors: Suneha Amar, Pankaj Deep Kaur
10.5120/ijca2017914586

Suneha Amar, Pankaj Deep Kaur . A Review on Various IOT Analytics Techniques for Bridge Failure Detection in Fog Computing. International Journal of Computer Applications. 169, 1 ( Jul 2017), 38-43. DOI=10.5120/ijca2017914586

@article{ 10.5120/ijca2017914586,
author = { Suneha Amar, Pankaj Deep Kaur },
title = { A Review on Various IOT Analytics Techniques for Bridge Failure Detection in Fog Computing },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2017 },
volume = { 169 },
number = { 1 },
month = { Jul },
year = { 2017 },
issn = { 0975-8887 },
pages = { 38-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume169/number1/27952-2017914586/ },
doi = { 10.5120/ijca2017914586 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:16:13.442624+05:30
%A Suneha Amar
%A Pankaj Deep Kaur
%T A Review on Various IOT Analytics Techniques for Bridge Failure Detection in Fog Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 169
%N 1
%P 38-43
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

IoT analytics is the alteration of enormous quantities of information in significant styles and rules. To expect describing the previous in addition to calculating the long term via data analysis. IoT analytics is a multi-disciplinary area which mixes, machine learning, research, data source technologies and artificial intelligence. IOT analytics is usually achieved in several stages of development: Business enterprise knowing, Information knowing, Information preparing, Acting, Review, and Deployment. There are various IOT analytics methods when Affiliation, Distinction, Clustering, Sensation problems System and Regression. This research work presents different IOT analytics algorithms intended for effectively mining the particular health-related facts set. IOT analytics algorithms have grown to be favorite every day live apps including breach prognosis procedure, diabetes mellitus exploration, e-mail spam distinction etc. In this paper we discuss about the various techniques of IOT and also IOT analytics techniques for bridge failure detection IOTs. The overall objective of this paper is to bridge failure detection in IOT

References
  1. Díaz, Manuel, Cristian Martín, and Bartolomé Rubio. "State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing." Journal of Network and Computer Applications 67 (2016): 99-117.
  2. Gia, Tuan Nguyen, et al. "Fog computing in healthcare internet of things: A case study on ecg feature extraction." Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM), 2015 IEEE International Conference on. IEEE, 2015.
  3. Abdelwahab, Sherif, et al. "Enabling smart cloud services through remote sensing: An internet of everything enabler." IEEE Internet of Things Journal 1.3 (2014): 276-288.
  4. Bonomi, Flavio, et al. "Fog computing: A platform for internet of things and analytics." Big Data and Internet of Things: A Roadmap for Smart Environments. Springer International Publishing, 2014. 169-186.
  5. Vaquero, Luis M., and Luis Rodero-Merino. "Finding your way in the fog: Towards a comprehensive definition of fog computing." ACM SIGCOMM Computer Communication Review 44.5 (2014): 27-32.
  6. Stojmenovic, Ivan, and Sheng Wen. "The fog computing paradigm: Scenarios and security issues." Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on. IEEE, 2014.
  7. Madsen, Henrik, et al. "Reliability in the utility computing era: Towards reliable fog computing." Systems, Signals and Image Processing (IWSSIP), 2013 20th International Conference on. IEEE, 2013.
  8. Hong, Kirak, et al. "Mobile fog: A programming model for large-scale applications on the internet of things." Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing. ACM, 2013.
  9. Zhu, Jiang, et al. "Improving web sites performance using edge servers in fog computing architecture." Service Oriented System Engineering (SOSE), 2013 IEEE 7th International Symposium on. IEEE, 2013.
  10. Wang, Wenye, and Zhuo Lu. "Cyber security in the Smart Grid: Survey and challenges." Computer Networks 57.5 (2013): 1344-1371.
  11. Luan, Tom H., et al. "Fog computing: Focusing on mobile users at the edge." arXiv preprint arXiv:1502.01815 (2015).
  12. Stolfo, Salvatore J., Malek Ben Salem, and Angelos D. Keromytis. "Fog computing: Mitigating insider data theft attacks in the cloud." Security and Privacy Workshops (SPW), 2012 IEEE Symposium on. IEEE, 2012.
  13. F. Bonomi, “Connected vehicles, the internet of things, and fog computing,” in The Eighth ACM International Workshop on Vehicular Inter- Networking (VANET), Las Vegas, USA, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Fog computing bridge failure detection Internet Of Things (IOT).

Powered by PhDFocusTM