Browse > Article
http://dx.doi.org/10.3837/tiis.2021.07.007

Automation Monitoring With Sensors For Detecting Covid Using Backpropagation Algorithm  

Kshirsagar, Pravin R. (Department of Electronics and Communication Engineering, AVNIET)
Manoharan, Hariprasath (Department of Electronics and Communication Engineering, Audisankara College of Engineering and Technology)
Tirth, Vineet (Department of Mechanical Engineering, College of Engineering, King Khalid University)
Naved, Mohd (Department of Business Analytics, Jagannath University)
Siddiqui, Ahmad Tasnim (Department of Computer Applications, Sherwood College of Professional Management)
Sharma, Arvind K. (Department of Computer Science, University of Kota)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.7, 2021 , pp. 2414-2433 More about this Journal
Abstract
This article focuses on providing remedial solutions for COVID disease through the data collection process. Recently, In India, sudden human losses are happening due to the spread of infectious viruses. All people are not able to differentiate the number of affected people and their locations. Therefore, the proposed method integrates robotic technology for monitoring the health condition of different people. If any individual is affected by infectious disease, then data will be collected and within a short span of time, it will be reported to the control center. Once, the information is collected, then all individuals can access the same using an application platform. The application platform will be developed based on certain parametric values, where the location of each individual will be retained. For precise application development, the parametric values related to the identification process such as sub-interval points and intensity of detection should be established. Therefore, to check the effectiveness of the proposed robotic technology, an online monitoring system is employed where the output is realized using MATLAB. From simulated values, it is observed that the proposed method outperforms the existing method in terms of data quality with an observed percentage of 82.
Keywords
Data quality; Intensity of detection; Robotic technology; Wireless sensors;
Citations & Related Records
연도 인용수 순위
  • Reference
1 J. Khan, J.P. Li, B. Ahamad, S. Praveen, A.U. Haq, G. Ahmad Khan and A.K. Sangaiah, "SMSH: Secure surveillance mechanism on smart healthcare IoT system with probabilistic image encryption," IEEE Access, vol. 8, pp. 15747-15767, 2020.   DOI
2 Binh NTM, Binh HTT, Van Linh N, Yu S, "Efficient meta-heuristic approaches in solving minimal exposure path problem for heterogeneous wireless multimedia sensor networks in internet of things," Appl Intell, 50, 1889-1907, 2020.   DOI
3 Khatoon A, "A blockchain-based smart contract system for healthcare management," Electron, 9, 2020.
4 Gupta A, Shreevastava M, "Medical Diagnosis using Back propagation Algorithm," Int J Emerg Technol Adv Eng, 1, 55-58, 2011
5 Misganaw B, Vidyasagar M, "Exploiting Ordinal Class Structure in Multiclass Classification: Application to Ovarian Cancer," IEEE Life Sci Lett, 1, 15-18, 2015.   DOI
6 A. Kharrat, M. Halima Ben, M. Ben Ayed, "MRI brain tumor classification using Support Vector Machines and meta-heuristic method," in Proc. of International Conference on Intelligent Systems and Design Applications (ISDA), pp. 446-451, 2016.
7 Pokhrel P, Hu C, Mao H, "Detecting the coronavirus (CoVID-19)," ACS Sensors, 5, 2283-2297, 2020.   DOI
8 T. Ozturk, M. Talo, E.A. Yildirim, U.B. Baloglu, O. Yildirim and U. Rajendra Acharya, "Automated detection of COVID-19 cases using deep neural networks with X-ray images," Computers in Biology and Medicine, vol. 121, pp. 103792, 2020.   DOI
9 Y. Shen, D. Guo, F. Long, L.A. Mateos, H. Ding, Z. Xiu, R.B. Hellman, Adam King, S. Chen, C. Zhang and H. Tan, "Robots under COVID-19 Pandemic: A Comprehensive Survey," IEEE Access, vol. 9, pp. 1590-1615, 2020.
10 Nag P, Sadani K, Mukherji S, "Optical Fiber Sensors for Rapid Screening of COVID-19," Trans Indian Natl Acad Eng, 5, 233-236, 2020.   DOI
11 Zhang W, Wang R, Luo F, et al, "Miniaturized electrochemical sensors and their point-of-care applications," Chinese Chem Lett, 31, 589-600, 2020.   DOI
12 Li X, Zhu L, Chu X, Fu H., "Edge Computing-Enabled Wireless Sensor Networks for Multiple Data Collection Tasks in Smart Agriculture," J Sensors, 2020.
13 Mohammed MN, Hazairin NA, Syamsudin H, et al., "2019 novel coronavirus disease (Covid-19): Detection and diagnosis system using iot based smart glasses," Int J Adv Sci Technol, 29, 954-960, 2020.
14 Chandra P., "Miniaturized label-free smartphone assisted electrochemical sensing approach for personalized COVID-19 diagnosis," Sensors Int, 1, 100019, 2020.   DOI
15 Zhou C, Su F, Pei T, et al., "COVID-19: Challenges to GIS with Big Data," Geogr Sustain, 1, 77-87, 2020.
16 Seshadri DR, Davies E V., Harlow ER, et al., "Wearable Sensors for COVID-19: A Call to Action to Harness Our Digital Infrastructure for Remote Patient Monitoring and Virtual Assessments," Front Digit Heal, 2, 1-11, 2020.   DOI
17 Seo G, Lee G, Kim MJ, et al., "Rapid Detection of COVID-19 Causative Virus (SARS-CoV-2) in Human Nasopharyngeal Swab Specimens Using Field-Effect Transistor-Based Biosensor," ACS Nano, 14, 5135-5142, 2020.   DOI
18 Kumar R, Nagpal S, Kaushik S, Mendiratta S., "COVID-19 diagnostic approaches: different roads to the same destination," VirusDisease, 31, 97-105, 2020.   DOI
19 Al-Turjman F, Lemayian JP, "Intelligence, security, and vehicular sensor networks in internet of things (IoT)-enabled smart-cities: An overview," Comput Electr Eng, 87, 106776, 2020.   DOI
20 M.Z. Islam, M.M. Islam and A. Asraf, "A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images," Informatics in Medicine Unlocked, vol. 20, pp. 100412, 2020..   DOI
21 Yu Y, Bu F, Zhou H, et al, "Biosafety materials: An emerging new research direction of materials science from the COVID-19 outbreak," Mater Chem Front, 4, 1930-1953, 2020.   DOI
22 M.K. Pandit, S.A. Banday, R. Naaz, M.A. Chishti, "Automatic detection of COVID-19 from chest radiographs using deep learning," Radiography, vol. 27, pp. 483-489, 2021.   DOI
23 Ibrahim A, Alfa A, "Optimization techniques for design problems in selected areas in WSNs: A tutorial," Sensors (Switzerland), 17, 1-63, 2017.   DOI