Root Depth Prediction Using Machine Learning for Effective Root Zone Injection Irrigation through IoT Automation

  • V. Vivekanandhan Assistant Professor, Department of Computer Science and Engineering, Adhiyamaan College of Engineering, Tamil Nadu, India
  • Christopher M. UG Scholar, Department of Computer Science and Engineering, Adhiyamaan College of Engineering, Tamil Nadu, India
  • Dilipkumar M UG Scholar, Department of Computer Science and Engineering, Adhiyamaan College of Engineering, Tamil Nadu, India
  • Gopal G. UG Scholar, Department of Computer Science and Engineering, Adhiyamaan College of Engineering, Tamil Nadu, India
Keywords: Agriculture, Irrigation, Machine Learning, Linear Regression, IoT devices, Wireless Neural Network of sensors, Root Zone Injection method

Abstract

Agriculture plays an important role in producing food supply for survival. The agriculture practice is performed by multiple factors such as soil type, fertilisers, plant samplings, irrigation practice, etc. On these factors on which agriculture depends, irrigation is one of the major factors for the better yield of crops, just like any other factor. Therefore, efficient irrigation practice has to be performed to increase cultivation production and preserve available water resources for optimal usage. Traditional methods of irrigation practice are well suited for situations with surplus water resources but not very efficient when it comes to scarce places. So, we propose a new IoT-driven root zone injection method of irrigation which is estimated to perform required irrigation practices in places of high water scarcity. This method is performed with the help of machine learning, IoT devices, wireless neural networking of sensors, and root zone injection equipment for automation. The mechanism starts with collecting real-time data from the agricultural field for specified crop types by using a wireless neural network of sensors and forming the dataset. Once the dataset is formed, it will be processed and cleaned to feed into machine learning algorithms. The machine learning algorithm (here, it is linear regression) will make the required prediction for the water content needed for the irrigation process for that particular day. The dynamic estimation is made as the water content required will vary from the growing phases of plants where it is minimum at the initial phase, peak at middle and reduce or increase depending on the plant species at later phase of growth. This estimated water content is then delivered to the plants through the irrigation process, governed by the IoT devices, which have the procedures encoded for irrigation. ML prediction guides the IoT system on how much water to deliver to the plants. Finally, the injection setup of the root zone passes the water directly to the underground root zones. Thus, completely preventing evaporation wastage and accurate water content estimation and supply, achieving optimal irrigation practice.

References

1. S.R. Barkunan, V. Bhanumathi, J. Sethuram, “Smart sensor for automatic drip irrigation system for paddy cultivation” Received 30 January 2017, Revised 13 June 2018, Accepted 13 November 2018.
2. Avşar, E., Buluş, K., Saridaş, M.A. and Kapur, B., 2018, May. Development of a cloud-based automatic irrigation system: A case study on strawberry cultivation. In 2018 7th International Conference on Modern Circuits and Systems Technologies (MOCAST) (pp. 1-4). IEEE.
3. Kodali, R.K. and Sarjerao, B.S., 2017, July. A low-cost smart irrigation system using MQTT protocol. In 2017 IEEE Region 10 Symposium (TENSYMP) (pp. 1-5). IEEE.
4. Jaafar, MFM, Hussin, H., Rosman, R., Kheng, TY and Hussin, MJA, 2019, October. Smart Cocoa Nursery Monitoring System Using IRT for Automatic Drip Irrigation. In 2019 IEEE 13th International Conference on Telecommunication Systems, Services, and Applications (TSSA) (pp. 108-113). IEEE.
5. H. Jochen Schenk And Robert B. Jackson, “Blackwell Science, Ltd Rooting depths, lateral root spreads and below-ground/ above-ground allometries of plants in water-limited ecosystems” Department of Biology and Nicholas School of the Environment and Earth Sciences, Duke University, Durham, North Carolina 27708, USA.
6. Yan-Ping Wang, Lin-Sen Zhang, Yan Mu, Wei-Hong Liu, Fu-Xing Guo1 And Tian-Ran Chang, “Effect of a Root-Zone Injection Irrigation method on water productivity and Apple production in a semi-arid region in north-western china” DOI: 10.1002.
7. Chiyurl Yoon, Miyoung Huh, Shin-Gak Kang, Juyoung Park, Changkyu Lee, “Implement Smart Farm with IoT Technology” International Conference on Advanced Communications Technology (ICACT).
8. K. A. Patil, N. R. Kale, “A Model for Smart Agriculture Using IoT”, 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication.
9. Rajinder Kumar, Nagaraj V Dharwadkar, “A Wireless Sensor Network Based Low Cost and Energy Efficient Frame Work for Precision Agriculture”, 2017 International Conference on Nascent Technologies in the Engineering Field (ICNTE-2017).
10. Harmantoa, V.M. Salokhea, M.S. Babelb, H.J. Tantauc, “Water requirement of drip irrigated tomatoes grown in greenhouse in tropical environment”,71 (2005) 225–242.
11. Bright Keswani, Ambarish G. Mohapatra, Amarjeet Mohanty, Ashish Khanna, Joel J. P. C. Rodrigues, Deepak Gupta, Victor Hugo C. de Albuquerque, “Adapting weather conditions based IoT enabled smart irrigation technique in precision agriculture mechanisms”, The Natural Computing Applications Forum 2018.
12. Weiwei Fang, Feng Liu, Fangnan Yang, Lei Shu, Nishio, S. (2010), “Energy-efficient cooperative communication for data transmission in wireless sensor networks”, 56(4), 0–2192. doi:10.1109/tce.2010.5681089.
13. Huang Lu, Jie Li, Guizani, Mohsen (2014),” Secure and Efficient Data Transmission for Cluster-Based Wireless Sensor Networks”, IEEE Transactions on Parallel and Distributed Systems, 25(3), 750–761. doi:10.1109.
14. M. Nesa Sudha; M.L. Valarmathi; Anni Susan Babu (2011), “Energy efficient data transmission in automatic irrigation system using wireless sensor networks”, 78(2), 215–221. doi:10.1016.
15. Hsu, T.-H.; Yen, P.-Y. (2011),” Adaptive time division multiple access-based medium access control protocol for energy conserving and data transmission in wireless sensor networks”, 5(18), 1–. doi:10.1049/iet-com.2011.0088.
16. Liu, Xuesong; Wu, Jie (2019), “A Method for Energy Balance and Data Transmission Optimal Routing in Wireless Sensor Networks. Sensors”, 19(13), 3017.
17. Chikankar, Pravina B.; Mehetre, Deepak; Das, Soumitra (2015), International Conference on Pervasive Computing (ICPC), “An automatic irrigation system using ZigBee in wireless sensor network”, doi:10.1109/PERVASIVE.2015.7086997.
18. Benaddy, M.; Habil, B. El; Ouali, M. El; Meslouhi, O. El; Krit, S. (2017), International Conference on Engineering & MIS (ICEMIS), “A mutlipath routing algorithm for wireless sensor networks under distance and energy consumption constraints for reliable data transmission”, doi:10.1109/ICEMIS.2017.8273076.
19. Ma, Ruiping; Xing, Liudong; Michel, Howard E. (2007), “A New Mechanism for Achieving Secure and Reliable Data Transmission in Wireless Sensor Networks”, 274–279. doi:10.1109/THS.2007.370058.
20. Kaewmard, Nattapol, Saiyod, Saiyan (2014). [IEEE 2014 IEEE Conference on Wireless Sensors (ICWiSe) - Subang, Selangor, Malaysia (2014.10.26-2014.10.28)] 2014 IEEE Conference on Wireless Sensors (ICWiSE), “Sensor data collection and irrigation control on vegetable crop using smart phone and wireless sensor networks for smart farm”, doi:10.1109/icwise.2014.7042670.
21. Dr. S. Velmurugan, V. Balaji, T. Manoj Bharathi, K. Saravanan, “An IOT based Smart Irrigation System using Soil Moisture and Weather Prediction”, International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181.
22. George Kokkoni, Sotirios Kontogiannis, Dimitrios Tomtsis,” A Smart IoT Fuzzy Irrigation System”, IOSR Journal of Engineering, ISSN (e): 2250-3021, ISSN (p): 2278-8719.
23. Aashika Premkumar, Thenmozhi K, P Monishaa, Padmapriya Praveenkumar, “IoT Assisted Automatic Irrigation System using Wireless Sensor Nodes”, 2018 International Conference on Computer Communication and Informatics (ICCCI -2018).
24. Revanth Kondaveti, Akash Reddy, Supreet Palabtla, “Smart Irrigation System Using Machine Learning and IOT”,doi:10.1109/ViTECoN.2019.8899433.
25. A. Mahesh Reddy, K. Raghava Rao, “An Android based Automatic Irrigation System using a WSN and GPRS Module”, Indian Journal of Science and Technology, Vol 9(29), DOI: 10.17485, August 2016.
26. Shiraz Pasha B.R., Dr. B Yogesha, “Microcontroller Based Automated Irrigation System”, The International Journal of Engineering and Science (IJES), ISSN (e): 2319 – 1813 ISSN (p): 2319 – 1805.
27. Getie Dereje Derib, “Cooperative Automatic Irrigation System using Arduino”, International Journal of Science and Research (IJSR), ISSN: 2319-7064.
28. John R. Dela Cruz, Renann G. Baldovino, Argel A. Bandala, Elmer P. Dadios, “Water Usage Optimization of Smart Farm Automated Irrigation System Using Artificial Neural Network”, 2017 Fifth International Conference on Information and Communication Technology (ICoICT).
29. D.S. Hooda, Keerti Upadhyay and D.K. Sharma, “On Parametric Generalization of ‘Useful’ R- norm Information Measure” British Journal of Mathematics & Computer Science, Vol. 8(1), pp. 1-15, 2015.
30. D.S. Hooda, Keerti Upadhyay and D.K. Sharma, “A Generalized Measure of ‘Useful R-norm Information”, International Journal of Engineering Mathematics and Computer Sciences, Vol 3(5), pp.1-11, 2014.
31. D.S. Hooda, Keerti Upadhyay and D.K. Sharma, “Bounds on Cost Measures in terms of ‘Useful’ R-norm Information Measures” Direct Research Journal of Engineering and Information Technology, Vol.2 (2), pp.11-17, 2014.
32. D.S. Hooda and D.K. Sharma, “Lower and Upper Bounds Inequality of a Generalized ‘Useful’ Mean Code Length” GAMS Journal of Mathematics and Mathematical Biosciences, Vol. 4(1), pp.62-69, 2013.
33. D.S. Hooda, Keerti Upadhyay and D.K. Sharma, ‘Useful’ R-Norm Information Measure and its Properties” IOSR Journal of Electronics and Communication Engineering, Vol. 8, pp. 52-57, 2013.
34. D.S. Hooda, Sonali Saxena and D.K. Sharma, “A Generalized R-Norm Entropy and Coding Theorem” International Journal of Mathematical Sciences and Engineering Applications, Vol.5(2), pp.385-393, 2011.
35. D.S. Hooda and D.K. Sharma, “Bounds on Two Generalized Cost Measures” Journal of Combinatorics, Information & System Sciences, Vol. 35(3-4), pp. 513-530, 2010.
36. D.K. Sharma and D.S. Hooda, “Generalized Measures of ‘Useful’ Relative Information and Inequalities” Journal of Engineering, Management & Pharmaceutical Sciences, Vol.1(1), pp.15-21, 2010.
37. D.S. Hooda and D.K. Sharma (2010) “Exponential Survival Entropies and Their Properties” Advances in Mathematical Sciences and Applications, Vol. 20, pp. 265-279, 2010.
38. D.S. Hooda and D.K. Sharma, “Generalized ‘Useful’ Information Generating Functions” Journal of Appl. Math. and Informatics, Vol. 27( 3-4), pp. 591-601, 2009.
39. D.S. Hooda and D.K. Sharma, “Non-additive Generalized Measures of ‘Useful’ Inaccuracy” Journal of Rajasthan Academy of Physical Sciences, Vol. 7(3), pp.359-368, 2008.
40. D.S. Hooda and D.K. Sharma, Generalized R-Norm information Measures-Journal of Appl. Math, Statistics & informatics (JAMSI), Vol. 4 No.2 , 153-168, 2008.
41. Dilip Kumar Sharma, “Some Generalized Information Measures: Their characterization and Applications”, Lambert Academic Publishing, Germany, 2010. ISBN: 978-3838386041.
42. D. K. Sharma, B. Singh, R. Regin, R. Steffi and M. K. Chakravarthi, "Efficient Classification for Neural Machines Interpretations based on Mathematical models," 2021 7th International Conference on Advanced Computing and Communication Systems, 2021, pp. 2015-2020.
43. F. Arslan, B. Singh, D. K. Sharma, R. Regin, R. Steffi and S. Suman Rajest, "Optimization Technique Approach to Resolve Food Sustainability Problems," 2021 International Conference on Computational Intelligence and Knowledge Economy, 2021, pp. 25-30.
44. G. A. Ogunmola, B. Singh, D. K. Sharma, R. Regin, S. S. Rajest and N. Singh, "Involvement of Distance Measure in Assessing and Resolving Efficiency Environmental Obstacles," 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021, pp. 13-18.
45. D. K. Sharma, B. Singh, M. Raja, R. Regin and S. S. Rajest, "An Efficient Python Approach for Simulation of Poisson Distribution," 2021 7th International Conference on Advanced Computing and Communication Systems, 2021, pp. 2011-2014.
46. D. K. Sharma, B. Singh, E. Herman, R. Regine, S. S. Rajest and V. P. Mishra, "Maximum Information Measure Policies in Reinforcement Learning with Deep Energy-Based Model," 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021, pp. 19-24.
47. D. K. Sharma, N. A. Jalil, R. Regin, S. S. Rajest, R. K. Tummala and T. N, "Predicting Network Congestion with Machine Learning," 2021 2nd International Conference on Smart Electronics and Communication, 2021, pp. 1574-1579.
48. Rupapara, V., Narra, M., Gonda, N. K., Thipparthy, K., & Gandhi, S. (2020). Auto-Encoders for Content-based Image Retrieval with its Implementation Using Handwritten Dataset. 2020 5th International Conference on Communication and Electronics Systems (ICCES), 289–294.
49. Rupapara, V., Thipparthy, K. R., Gunda, N. K., Narra, M., & Gandhi, S. (2020). Improving video ranking on social video platforms. 2020 7th International Conference on Smart Structures and Systems (ICSSS), 1–5.
50. Rupapara, V., Narra, M., Gonda, N. K., & Thipparthy, K. (2020). Relevant Data Node Extraction: A Web Data Extraction Method for Non Contagious Data. 2020 5th International Conference on Communication and Electronics Systems (ICCES), 500–505.
51. Ishaq, A., Sadiq, S., Umer, M., Ullah, S., Mirjalili, S., Rupapara, V., & Nappi, M. (2021). Improving the Prediction of Heart Failure Patients’ Survival Using SMOTE and Effective Data Mining Techniques. IEEE Access, 9, 39707–39716.
52. Rustam, F., Khalid, M., Aslam, W., Rupapara, V., Mehmood, A., & Choi, G. S. (2021). A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis. PLOS ONE, 16(2), e0245909.
53. Yousaf, A., Umer, M., Sadiq, S., Ullah, S., Mirjalili, S., Rupapara, V., & Nappi, M. (2021b). Emotion Recognition by Textual Tweets Classification Using Voting Classifier (LR-SGD). IEEE Access, 9, 6286–6295.
54. Sadiq, S., Umer, M., Ullah, S., Mirjalili, S., Rupapara, V., & NAPPI, M. (2021). Discrepancy detection between actual user reviews and numeric ratings of Google App store using deep learning. Expert Systems with Applications, 115111.
55. Rupapara, V., Narra, M., Gonda, N. K., Thipparthy, K., & Gandhi, S. (2020). Auto-Encoders for Content-based Image Retrieval with its Implementation Using Handwritten Dataset. 2020 5th International Conference on Communication and Electronics Systems (ICCES), 289–294.
56. Rupapara, V., Thipparthy, K. R., Gunda, N. K., Narra, M., & Gandhi, S. (2020). Improving video ranking on social video platforms. 2020 7th International Conference on Smart Structures and Systems (ICSSS), 1–5.
57. Rupapara, V., Narra, M., Gonda, N. K., & Thipparthy, K. (2020). Relevant Data Node Extraction:A Web Data Extraction Method for Non Contagious Data. 2020 5th International Conference on Communication and Electronics Systems (ICCES), 500–505.
58. U. Zulfiqar, S. Mohy-Ul-Din, A. Abu-Rumman, A. E. M. Al-Shraah, And I. Ahmed, “Insurance-Growth Nexus: Aggregation and Disaggregation,” The Journal of Asian Finance, Economics and Business, vol. 7, no. 12, pp. 665–675, Dec. 2020.
59. Al-Shqairat, Z. I., Al Shraah, A. E. M., Abu-Rumman, A., “The role of critical success factors of knowledge stations in the development of local communities in Jordan: A managerial perspective,” Journal of management Information and Decision Sciences, vol. 23, no.5, pp. 510-526, Dec. 2020. DOI: 1532-5806-23-5-218
60. Abu-Rumman, Ayman. "Transformational leadership and human capital within the disruptive business environment of academia." World Journal on Educational Technology: Current Issues 13, no. 2 (2021): 178-187.
61. Almomani, Reham Zuhier Qasim, Lina Hamdan Mahmoud Al-Abbadi, Amani Rajab Abed Alhaleem Abu Rumman, Ayman Abu-Rumman, and Khaled Banyhamdan. "Organizational Memory, Knowledge Management, Marketing Innovation and Cost of Quality: Empirical Effects from Construction Industry in Jordan." Academy of Entrepreneurship Journal 25, no. 3 (2019): 1528-2686.
62. Alshawabkeh, Rawan, Amani Abu Rumman, Lina Al-Abbadi, and Ayman Abu-Rumman. "The intervening role of ambidexterity in the knowledge management project success connection." Problems and Perspectives in Management 18, no. 3 (2020): 56.
63. Abu-Rumman, Ayman. "Gaining competitive advantage through intellectual capital and knowledge management: an exploration of inhibitors and enablers in Jordanian Universities." Problems and Perspectives in Management 16, no. 3 (2018): 259-268.
64. Abu-Rumman, A. Al Shraah, F. Al-Madi, T. Alfalah, “Entrepreneurial networks, entrepreneurial orientation, and performance of small and medium enterprises: are dynamic capabilities the missing link?” Journal of Innovation and Entrepreneurship. Vol 10 Issue 29, pp 1-16. Jul 2021.
65. A.Al Shraah, A. Abu-Rumman, F. Al Madi, F.A. Alhammad, A.A. AlJboor, “The impact of quality management practices on knowledge management processes: a study of a social security corporation in Jordan” The TQM Journal. Vol. ahead-of-print No. Issue ahead-of- print. Apr 2021.
66. Abu-Rumman, A. Al Shraah, F. Al-Madi, T. Alfalah, "The impact of quality framework application on patients’ satisfaction", International Journal of Human Rights in Healthcare, Vol. ahead-of-print No. Issue ahead-of- print. Jun2021.
67. Zafar, S.Z., Zhilin, Q., Malik, H., Abu-Rumman, A., Al Shraah, A., Al-Madi, F. and Alfalah, T.F. (2021), "Spatial spillover effects of technological innovation on total factor energy efficiency: taking government environment regulations into account for three continents", Business Process Management Journal, Vol. 27 No. 6, pp. 1874-1891.
68. A.K. Gupta, Y. K. Chauhan, and T Maity, “Experimental investigations and comparison of various MPPT techniques for photovoltaic system,” Sādhanā, Vol. 43, no. 8, pp.1-15, 2018.
69. A.K. Gupta, “Sun Irradiance Trappers for Solar PV Module to Operate on Maximum Power: An Experimental Study,” Turkish Journal of Computer and Mathematics Education, Vol. 12, no.5, pp.1112-1121, 2021.
70. A.K. Gupta, Y.K Chauhan, and T Maity and R Nanda, “Study of Solar PV Panel Under Partial Vacuum Conditions: A Step Towards Performance Improvement,” IETE Journal of Research, pp.1-8, 2020.
71. A.K. Gupta, Y.K Chauhan, and T Maity, “A new gamma scaling maximum power point tracking method for solar photovoltaic panel Feeding energy storage system,” IETE Journal of Research, vol.67, no.1, pp.1-21, 2018.
72. A. K. Gupta et al., "Effect of Various Incremental Conductance MPPT Methods on the Charging of Battery Load Feed by Solar Panel," in IEEE Access, vol. 9, pp. 90977-90988, 2021.
73. Aakanksha Singhal and D.K. Sharma, “Seven Divergence Measures by CDF of fitting in Exponential and Normal Distributions of COVID-19 Data”, Turkish Journal of Physiotherapy and Rehabilitation, Vol.32(3), pp. 1212 - 1222, 2021.
74. D.K. Sharma and Haldhar Sharma, “A Study of Trend Growth Rate of Confirmed cases, Death cases and Recovery cases in view of Covid-19 of Top Five States of India”, Solid State Technology, Vol.64(2), pp. 4526-4541, 2021.
75. D.K. Sharma, “Information Measure Computation and its Impact in MI COCO Dataset”, IEEE Conference Proceedings, 7th International Conference on Advanced Computing and Communication Systems (ICACCS), Vol.1, pp. 2011-2014, 2021.
76. Aakanksha Singhal and D.K. Sharma, “Keyword extraction using Renyi entropy: a statistical and domain independent method”, IEEE Conference Proceedings, 7th International Conference on Advanced Computing and Communication Systems (ICACCS), Vol.1, pp. 1970-1975, 2021.
77. Aakanksha Singhal and D.K. Sharma, “Generalization of F-Divergence Measures for Probability Distributions with Associated Utilities”, Solid State Technology, Vol.64(2), pp. 5525-5531, 2021.
78. Aakanksha Singhal and D.K. Sharma, “A Study of before and after Lockdown Situation of 10 Countries through Visualization of Data along With Entropy Analysis of Top Three Countries”, International Journal of Future Generation Communication and Networking, Vol.14(1), pp. 496-525, 2021.
79. Aakanksha Singhal and D.K. Sharma, “Generalized ‘Useful’ Rényi & Tsallis Information Measures, Some Discussions with Application to Rainfall Data", International Journal of Grid and Distributed Computing, Vol. 13(2), pp. 681-688, 2020.
80. Reetu Kumari and D. K. Sharma, “Generalized `Useful non-symmetric divergence measures and Inequalities", Journal of Mathematical Inequalities, Vol. 13(2), pp. 451-466, 2019.
81. D.S. Hooda and D.K. Sharma, “On Characterization of Joint and Conditional Exponential Survival Entropies", International Journal of Statistics and Reliability Engineering, Vol. 6(1), pp. 29-36, 2019.
82. Reetu Kumari and D. K. Sharma, “Generalized `Useful' AG and `Useful' JS-Divergence Measures and their Bounds", International Journal of Engineering, Science and Mathematics, Vol. 7 (1), pp. 441-450, 2018.
83. D.S. Hooda, Reetu Kumari and D. K. Sharma, “Intuitionistic Fuzzy Soft Set Theory and Its Application in Medical Diagnosis”, International Journal of Statistics in Medical Research, Vol. 7, pp. 70-76, 2018.
84. D.K. Sharma and Sonali Saxena, “Generalized Coding Theorem with Different Source Coding Schemes”, International Journal on Recent and Innovation Trends in Computing and Communication, Vol. 5(6), pp. 253 – 257, 2017.
85. S. Sudhakar and S.Chenthur Pandian “Secure Packet Encryption and Key Exchange System in Mobile Ad hoc Nerwork”, Journal of Computer Science, Vol.8, No. 6, pp : 908-912, 2012, DOI:10.3844/jcssp.2012.908.912.
86. S. Sudhakar and S. Chenthur Pandian, “Hybrid Cluster-based Geographical Routing Protocol to Mitigate Malicious Nodes in Mobile Ad Hoc Network”, International Journal of Ad Hoc and Ubiquitous Computing, 2016 Vol.21 No.4, pp.224-236.
87. N. Keerthana, Viji Vinod and S. Sudhakar, “A Novel Method for Multi-Dimensional Cluster to Identify the Malicious Users on Online Social Networks”, Journal of Engineering Science and Technology Vol. 15, No. 6, pp: 4107-4122, 2020.
88. A. U. Priyadarshni and S. Sudhakar, “Cluster Based Certificate Revocation by Cluster Head in Mobile Ad-Hoc Network”, International Journal of Applied Engineering Research, Vol. 10, No. 20, pp. 16014-16018, 2015.
89. S. Sudhakar and S. Chenthur Pandian, “Investigation of Attribute Aided Data Aggregation Over Dynamic Routing in Wireless Sensor,” Journal of Engineering Science and Technology Vol.10, No.11, pp:1465–1476, 2015.
90. S. Sudhakar and S. Chenthur Pandian, “Trustworthy Position Based Routing to Mitigate against the Malicious Attacks to Signifies Secured Data Packet using Geographic Routing Protocol in MANET”, WSEAS Transactions on Communications, Vol. 12, No. 11, pp:584- 603, 2013,
91. S. Sudhakar and S. Chenthur Pandian, “A Trust and Co-Operative Nodes with Affects of Malicious Attacks and Measure the Performance Degradation on Geographic Aided Routing in Mobile Ad Hoc Network”, Life Science Journal, Vol. 10, No. (4s), pp:158-163, 2013.
92. S. Sudhakar and S. Chenthur Pandian, “An Efficient Agent-Based Intrusion Detection System for Detecting Malicious Nodes in MANET Routing”, International Review on Computers and Software, Vol.7, No.6, pp.3037-304,2012.
93. S. Sudhakar and S. Chenthur Pandian, “Authorized Node Detection and Accuracy in Position-Based Information for MANET”, European Journal of Scientific Research, Vol.70, No.2, pp.253-265,2012.
94. K. Ganesh Kumar and S. Sudhakar, Improved Network Traffic by Attacking Denial of Service to Protect Resource Using Z-Test Based 4-Tier Geomark Traceback (Z4TGT),Wireless Personal Communications, Vol.114, No. 4, pp:3541–3575, 2020.
95. Akther, T. and Xu, F. (2021), "An investigation of the credibility of and confidence in audit value: evidence from a developing country", Accounting Research Journal, Vol. 34 No. 5, pp. 488-510.
96. Xu, F., & Akther, T. (2019). A partial least-squares structural equation modeling approach to investigate the audit expectation gap and its impact on investor confidence: perspectives from a developing country. Sustainability, 11(20), 5798.
97. Akther, T., & Xu, F. (2020). Existence of the audit expectation gap and its impact on stakeholders’ confidence: The moderating role of the financial reporting council. International Journal of Financial Studies, 8(1), 4.
98. Akther, T. Corporate Environmental Reporting and Profitability: A Study on Listed Companies in Bangladesh; Jagannath University Journal of Business Studies; Vol. 5, No. 1 &2 June 2017(99-104).
99. F. J. John Joseph, “IoT Based Weather Monitoring System for Effective Analytics,” Int. J. Eng. Adv. Technol., vol. 8, no. 4, pp. 311–315, 2019.
100. F. J. J. John Joseph, “Twitter Based Outcome Predictions of 2019 Indian General Elections Using Decision Tree,” in Proceedings of 2019 4th International Conference on Information Technology, 2019, no. October, pp. 50–53.
101. F. J. John Joseph, “Empirical Dominance of Features for Predictive Analytics of Particulate Matter Pollution in Thailand,” in 5th Thai-Nichi Institute of Technology Academic Conference TNIAC 2019, 2019, no. May, pp. 385–388.
102. V. Pattana-anake, P. Danphitsanuparn, and F. J. J. John Joseph, “BettaNet : A Deep Learning Architecture for Classification of Wild Siamese Betta Species,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1055, 2021.
103. F. J. John Joseph and S. Nonsiri, “Region-Specific Opinion Mining from Tweets in a Mixed Political Scenario,” in International Conference on Intelligent and Smart Computing in Data Analytics, 2021, pp. 189–195.
104. F. J. John Joseph, S. Nonsiri, and A. Monsakul, “Keras and Tensorflow - A Hands on Experience,” in Advanced Deep Learning for Engineers And Scientists: A Practical Approach, Switzerland: Springer Nature Switzerland AG, 2020.
105. F. J. John Joseph and P. Anantaprayoon, “Offline Handwritten Thai Character Recognition Using Single Tier Classifier and Local Features,” in 2018 International Conference on Information Technology (InCIT), 2018, pp. 1–4.
106. F. J. John Joseph and S. Auwatanamongkol, “A crowding multi-objective genetic algorithm for image parsing,” Neural Comput. Appl., vol. 27, no. 8, pp. 2217–2227, 2016, doi: 10.1007/s00521-015-2000-2.
107. J. F. Joe, T. Ravi, A. Natarajan and S. P. Kumar, "Object recognition of Leukemia affected cells using DCC and IFS," 2010 Second International conference on Computing, Communication and Networking Technologies, 2010, pp. 1-6.
108. J. F. Joe, "Enhanced sensitivity of motion detection in satellite videos using instant learning algorithms," IET Chennai 3rd International on Sustainable Energy and Intelligent Systems (SEISCON 2012), 2012, pp. 1-6, doi: 10.1049/cp.2012.2250.
109. Thowfeek MH, Samsudeen, SN, Sanjeetha, MBF. Drivers of Artificial Intelligence in Banking Service Sectors, Solid State Technology, (2020); 63(5): 6400 – 6411.
110. Samsudeen SN, Thowfeek MH, Rashida, MF. School Teachers’ Intention to Use E-Learning Systems in Sri Lanka: A Modified TAM Approach, International Journal of Information and Knowledge Management, (2015); 5(4), 55-59.
111. Samsudeen, SN, Thowfeek, MH. Small Medium Entrepreneurs’ Intension to Use Cloud Computing: Reference to Eastern Province of Sri Lanka, Journal of Management, (2014);11(1), 1-10.
112. Thowfeek, MH. Salam, MNA. Students’ Assessment on the Usability of E-learning Websites. Procedia-Social and Behavioral Sciences, (2014);141; 916-922.
113. Samsudeen, S. N. Acceptance of cloud of things by small and medium enterprises in Sri Lanka, Journal of Advanced Research in Dynamical and Control Systems, (2020);12(2), 2276-2285.
114. Thowfeek, MH, Samsudeen SN. Readiness of Resources for Flipped Classroom. In Proceedings of the 2019 8th International Conference on Educational and Information Technology. (2019); (pp. 92-96).
115. Rjoub, H., Iloka, C. B., & Venugopal, V. (2022). Changes in the Marketing Orientation Within the Business Model of an International Retailer: IKEA in Malaysia for Over 20 Years. In Handbook of Research on Current Trends in Asian Economics, Business, and Administration (pp. 170-190). IGI Global.
116. Li, M., Hamawandy, N. M., Wahid, F., Rjoub, H., & Bao, Z. (2021). Renewable energy resources investment and green finance: Evidence from China. Resources Policy, 74, 102402.
117. Li, H. S., Geng, Y. C., Shinwari, R., Yangjie, W., & Rjoub, H. (2021). Does renewable energy electricity and economic complexity index help to achieve carbon neutrality target of top exporting countries?. Journal of Environmental Management, 299, 113386.
118. Ahmed, Z., Ahmad, M., Rjoub, H., Kalugina, O. A., & Hussain, N. (2021). Economic growth, renewable energy consumption, and ecological footprint: Exploring the role of environmental regulations and democracy in sustainable development. Sustainable Development.
119. Safi, A., Chen, Y., Wahab, S., Zheng, L., & Rjoub, H. (2021). Does environmental taxes achieve the carbon neutrality target of G7 economies? Evaluating the importance of environmental R&D. Journal of Environmental Management, 293, 112908.
120. Odugbesan, J. A., Rjoub, H., Ifediora, C. U., & Iloka, C. B. (2021). Do financial regulations matters for sustainable green economy: evidence from Turkey. Environmental Science and Pollution Research, 1-16.
121. Demir, M., Rjoub, H., & Yesiltas, M. (2021). Environmental awareness and guests’ intention to visit green hotels: The mediation role of consumption values. Plos one, 16(5), e0248815.
122. Moguluwa, S. C., Odugbesan, J. A., Rjoub, H., & Iloka, C. B. (2021). Cost and competitiveness of agricultural produce in Nigeria: impact on exportation. Custos E Agronegocio On Line, 17(2), 64-86.
123. Yıldız, B. F., Hesami, S., Rjoub, H., & Wong, W. K. (2021). Interpretation Of Oil Price Shocks On Macroeconomic Aggregates Of South Africa: Evidence From SVAR. Journal of Contemporary Issues in Business and Government, 27(1), 279-287.
124. Al-Baghdadi, E. N., Alrub, A. A., & Rjoub, H. (2021). Sustainable Business Model and Corporate Performance: The Mediating Role of Sustainable Orientation and Management Accounting Control in the United Arab Emirates. Sustainability, 13(16), 8947.
125. Rjoub, H., Ifediora, C. U., Odugbesan, J. A., Iloka, B. C., Xavier Rita, J., Dantas, R. M., ... & Martins, J. M. (2021). Implications of Governance, Natural Resources, and Security Threats on Economic Development: Evidence from Sub-Saharan Africa. International Journal of Environmental Research and Public Health, 18(12), 6236.
126. Panait, M., Ionescu, R., Radulescu, I. G., & Rjoub, H. (2021). The Corporate Social Responsibility on Capital Market: Myth or Reality?. In Financial Management and Risk Analysis Strategies for Business Sustainability (pp. 219-253). IGI Global.
127. Ayodeji, Y., & Rjoub, H. (2021). Investigation into waiting time, self‐service technology, and customer loyalty: The mediating role of waiting time in satisfaction. Human Factors and Ergonomics in Manufacturing & Service Industries, 31(1), 27-41.
128. Alwreikat, A. A., & Rjoub, H. (2020). Impact of mobile advertising wearout on consumer irritation, perceived intrusiveness, engagement and loyalty: A partial least squares structural equation modelling analysis. South African Journal of Business Management, 51(1), 11.
129. Ilkhanizadeh, S., Golabi, M., Hesami, S., & Rjoub, H. (2020). The Potential Use of Drones for Tourism in Crises: A Facility Location Analysis Perspective. Journal of Risk and Financial Management, 13(10), 246.
130. Alhmoud, A., & Rjoub, H. (2020). Does Generation Moderate the Effect of Total Rewards on Employee Retention? Evidence From Jordan. SAGE Open, 10(3), 2158244020957039.
131. Fofack, A. D., Aker, A., & Rjoub, H. (2020). Assessing the post-quantitative easing surge in financial flows to developing and emerging market economies. Journal of Applied Economics, 23(1), 89-105.
132. Rjoub, H., Aga, M., Oppong, C., Sunju, N., & Fofack, A. (2017). The Impact of FDI Inflows on Economic Growth: Evidence from Landlocked Countries in Sub-Saharan Africa. Bilig-Turk DunyasI Sosyal Bilimler Dergisi, 10(1), 153-168.
133. Odugbesan, J. A., & Rjoub, H. HIV/AIDS Prevalence as A Challenge for Sustainable Development: The Sub-Saharan Africa Experience.
134. Peterka, H., & Rjoub, H. Facility Management Based–Integrated Substantiated Portfolio Management Of The University Of Vienna.
135. Geno Peter, Anli Sherine, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, Histogram Shifting based Quick Response Steganography method for Secure Communication” Wireless Communications and Mobile Computing. vol. 2022, 10 pages, 2022.
136. Geno Peter, Anli Sherine, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, Design of Automated Deep Learning-based Fusion Model for Copy-Move Image Forgery Detection” Computational Intelligence and Neuroscience. vol. 2022, 9 pages, 2022.
137. Hariprasath Manoharan, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, K Venkatachalam, Acclimatization Of Nano Robots In Medical Applications Using Artificial Intelligence System With Data Transfer Approach” Wireless Communications And Mobile Computing. vol. 2022, 9 pages, 2022.
138. Ashok Kumar L, Ramya Kuppusamy, Yuvaraja Teekaraman, Indragandhi V, Arun Radhakrishnan, Design and Implementation of Automatic Water Spraying System for Solar Photovoltaic Module” Mathematical Problems In Engineering. vol. 2022, 9 pages, 2022.
139. K Veena, K Meena, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, Cybercrime Detection using C SVM and KNN Techniques” Wireless Communications and Mobile Computing. vol. 2022, 8 pages, 2022.
140. Yuvaraja Teekaraman, KA Ramesh Kumar, Ramya Kuppusamy, Amruth Ramesh Thelkar, SSNN Based Energy Management Strategy in Grid-Connected System for Load Scheduling and Load Sharing” Mathematical Problems In Engineering. vol. 2022, Article ID 2447299, 9 pages, 2022.
141. M. Bharathidasan, V. Indragandhi, Ramya Kuppusamy, Yuvaraja Teekaraman, Shabana Urooj4,*, Norah Alwadi, ‘Intelligent Fuzzy Based High Gain Non-Isolated Converter for DC Micro-Grids” CMC-Computers, Materials & Continua. Vol 71, No.2, 2022.
142. Hariprasath Manoharan, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, A Novel Optimal Robotized Parking System Using Advanced Wireless Sensor Network” Journal of Sensors. Volume 2021, Page 1-8, 2021.
143. Kamaleshwar T, Lakshminarayanan R, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, A Self-Adaptive framework for Rectification and Detection of Blackhole and Wormhole attacks in 6LoWPAN” Wireless Communications And Mobile Computing. Volume 2021, 2021. Page 1-8.
144. Pavan Babu Bandla, Indragandhi Vairavasundaram, Yuvaraja Teekaraman, Srete Nikolovski, “Real Time Sustainable Power Quality Analysis of Non-Linear Load under Symmetrical Conditions” Energies 2022, 15(01).
145. Hariprasath Manoharan, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, A Prognostic Three-Axis Coordination Model for Supply Chain Regulation Using Machine Learning Algorithm” Scientific Programming. Volume 2021, 2021. Page 1-9.
146. Hariprasath Manoharan, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, An Intellectual Energy Device for Household Appliances Using Artificial Neural Network” Mathematical Problems In Engineering. Volume 2021, 2021. Page 1-9.
147. Nagarajan Manikandan, Rajappa Muthaiah, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, A Novel Random Error Approximate Adder-Based Lightweight Image Encryption Scheme for Secure Remote Monitoring of Reliable Data” Security and Communication Networks. Vol 2021, 2021. Page 1-14.
148. Senthilselvan Natarajan, Subramaniyaswamy Vairavasundaram, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan, Schema-Based Mapping Approach for Data Transformation toEnrich Semantic Web” Wireless Communications and Mobile Computing. Vol 2021, 2021. Page 1-15.
149. Yuvaraja Teekaraman, Hariprasath Manoharan, Ramya Kuppusamy, Fadwa Alrowais, Shabana Urooj, Energy Efficient Multi-Hop Routing Protocol for Smart Vehicle Monitoring Using Intelligent Sensor Networks” International Journal Of Distributed Sensor Networks. Vol 17, Issue 12. 2021. Page 1-11.
150. Yuvaraja Teekaraman, Ramya Kuppusamy, V. Indragandhi, ‘Modeling and Analysis of PV System with Fuzzy Logic MPPT Technique for a DC Microgrid under Variable Atmospheric Conditions” Electronics. (20) 2541, 2021.
151. Yuvaraja Teekaraman, Ramya Kuppusamy, V. Indragandhi, ‘Investigations on the effect of micro-grid using improved NFIS-PID with hybrid algorithms” Computing. Springer 2021. DOI: 10.1007/s00607-021-01006-9.
152. Yuvaraja Teekaraman, Jasmin Pamela, V. Indragandhi, R. Saranya, Shabana Urooj, V. Subramaniyaswamy, Norah Alwadi ‘’2D Finite Element Analysis of Asynchronous Machine Influenced under Power Quality Perturbations” CMC-Computers, Materials & Continua. Volume 70. Number 03, pp. 5745-5763, 2021.
153. Ratnam Kamala Sarojini, Palanisamy Kaliannan, Yuvaraja Teekaraman, Srete Nikolovski, Hamid Reza Baghaee, ''An Enhanced Emulated Inertia Control for Grid-Connected PV Systems with HESS in a Weak Grid''Energies 2021, 14(06), 1455 (1-21);
154. Subramanian Vasantharaj, Indragandhi Vairavasundaram, Subramaniyaswamy Vairavasundaram, Yuvaraja Teekaraman, Ramya Kuppusamy, Nikolovski Srete, Efficient Control of DC Microgrid with Hybrid PV—Fuel Cell and Energy Storage Systems” Energies 2021, 14(06), 3234 (1-18);
155. Yuvaraja Teekaraman, Hariprasath Manoharan, "Implementation of Cognitive Radio Model for Agricultural Applications using Hybrid Algorithms". Wireless Personal Communications, Accepted. 2021.
156. Rahul Gopi, Soundarya S, Kavitha P, Yuvaraja Teekaraman, Ramya Kuppusamy, Shabana Urooj “Enhanced Model Reference Adaptive Control Scheme for Tracking Control of Magnetic Levitation System” Energies 2021, 14(05), 1455 (1-13).
157. Shabana Urooj, Fadwa Alrowais, Yuvaraja Teekaraman, Hariprasath Manoharan, Ramya Kuppusamy, “IoT Based Electric Vehicle Application Using Boosting Algorithm for Smart Cities” Energies 2021, 14(04), 1072 (1-15).
158. Shabana Urooj, Fadwa Alrowais, Ramya Kuppusamy, Yuvaraja Teekaraman, Hariprasath Manoharan, “New Gen Controlling Variable using Dragonfly Algorithm in PV Panel” Energies 2021, 14(04), 790 (1-14).
159. Hariprasath Manoharan, Yuvaraja Teekaraman, Pravin R Kshirsagar, Shanmugam Sundaramurthy, Abirami Manoharan, Examining the effect of Aquaculture using Sensor based Technology with Machine Learning Algorithm. Aquaculture Research, 13(15), pp.1-16. 2020.
160. Hariprasath Manoharan, Yuvaraja Teekaraman, Irina Kirpichnikova, Ramya Kuppusamy, Srete Nikolovski, Hamid Reza Baghaee., Smart Grid Monitoring by Wireless Sensors Using Binary Logistic Regression. Energies, 13(15), pp.1-16. 2020.
161. Yuvaraja Teekaraman, Hariprasath Manoharan., Adam Raja Basha, Abirami Manoharan., Hybrid Optimization Algorithms for Resource Allocation in Heterogeneous Cognitive Radio Networks. Neural Processing Letters. http://link.springer.com/article/10.1007/s11063-020- 10255-2. 2020.
162. Yuvaraja.T, KA Ramesh Kumar, “Enhanced Frequency Shift Carrier Modulation for H Bridge Multilevel Converter to Conquer the Impact of Instability in Deputize Condenser Voltage” International Journal Of Electrical Engineering Education, Volume 57 Issue 2, April 2020.
163. Yuvaraja Teekaraman, K Ramya, Srete Nikolovski, “Current Compensation in Grid Connected VSCs using Advanced Fuzzy Logic Based Fluffy Built SVPWM Switching” Energies 2020, 13(05), 1259.
164. Yuvaraja Teekaraman, Pranesh Sthapit, Miheung Choe, Kiseon Kim, “Energy Analysis on Localization Free Routing Protocols in UWSNs” International Journal of Computational Intelligence System, Atlantis Press, Vol.12, Issue 2, pp. 1526-1536, 2019.
165. W. Vinu, “ Analysis of percent body fat among all India inter university hand ball players. International Journal of Advanced Educational Research, Vol.1, no.1, p.36-38, 2016.
166. Jothi, K.R., W. Vinu, & Eleckuvan, R.M., “Effect of Concurrent Strength and Plyometric Training on Selected Biomotor Abilities. Recent Research in Science and Technology, Vol. 2, no.5, p.124-126, 2010.
167. Mozhi, A. A., & W. Vinu , “ A comparative study of aggression between men and women kabaddi and kho-kho players. International Journal of Physiology, Nutrition and Physical Education, Vol. 4, no.1, p.380-382, 2019.
168. Mozhi, A. A., & W. Vinu , “ A comparative study of competition anxiety between men and women boxers and fencers. International Journal of Yogic, Human Movement and Sports Sciences, Vol.4, no.1, p.203-205, 2019.
169. Ravi, R. A., & W. Vinu , “ Effects of adapted physical exercise on development of reaction time among children with autism. International Journal of Yogic, Human Movement and Sports Sciences, Vol.4, no.1, p.1307-1309, 2019.
170. Ravi, R. A., & W. Vinu , “ Outcome of physical exercises on development of motor skill in children with autism. International Journal of Physiology, Nutrition and Physical Education, Vol.4, no.1, p.2030-2032, 2019.
171. Vinu.W. , “ Anthropometric aspects of South Indian volleyball players in relation to their skill performance ‘Service’. Annals of the Romanian Society for Cell Biology, Vol. 25, no.4, p.20187–20192, 2021.
172. W Vinu. ( 2012). The effect of circuit training and circuit weight training with and with out protein suplementary on thigh girth. Pharma Innovation, Vol.1, no.10, p.73-78, 2012.
173. C. Virmani, A. Pillai, and D. Juneja. "Study and analysis of Social network Aggregator.", International Conference on Reliability Optimization and Information Technology, pp. 145-148. IEEE, 2014.
174. C. Virmani, A. Pillai, and D. Juneja., "Clustering in aggregated user profiles across multiple social networks." International Journal of Electrical and Computer Engineering, vol 7. No 6, pp, 3692-3699, 2017.
175. C. Virmani, A. Pillai, and D. Juneja., "Extracting information from social network using nlp." International Journal of Computational Intelligence Research , vol. 13, No.4, pp: 621-630, 2017.
176. T. Choudhary, C. Virmani, and D. Juneja. "Convergence of Blockchain and IoT: An Edge Over Technologies." Toward Social Internet of Things (SIoT): Enabling Technologies, Architectures and Applications. Springer, Cham, pp: 299-316, 2020.
177. C. Virmani, D. Juneja , and A. Pillai, "Design of query processing system to retrieve information from social network using NLP.", KSII Transactions on Internet and Information Systems (TIIS), vol. 12, No.3, pp: 1168-1188, 2018.
178. W. Vinu (2016). Effect of intensive and extensive circuit weight training and detraining on mean arterial pressure, Vol.1, no.1, p.70-74. 2016
179. W. Vinu , Implication of yogic practice and Swiss ball training on hormone triiodothyronine (T3) in physical education students. International Journal of Academic Research and Development, Vol.3, no.2, p.711-1713, 2018.
180. W. Vinu , “ Assessment of Sports, Yoga with Mind Training and Sports, Yoga Training on Students with Cigarette Addiction. Indian Journal of Public Health Research & Development., Vol. 10, no.5, p339-343, 2019.
181. W. Vinu , “ Comparative study of speed variables between Private School and Government School football players. International Journal of Advance Research, Ideas and Innovations in Technology, Vol. 5, no.3, p.979-982, 2019.
182. W. Vinu , “ Disparities in Sportspersons’ Sleep Behaviour due to COVID-19 Pandemic Lockdown in India. Asian Journal of Aplied Science and Technology (AJAST), Vol.5, no.2, p.134-139, 2021.
183. W. Vinu , “ Effect of yogic practice on the attitude among school students. International Journal of Multidisciplinary Research and Development, Vol.2, no.10. p.731-733, 2015.
184. W. Vinu , “ Effect of yogic practices on selected cardio respiratory endurance of men students. International Journal of Physical Education, Sports and Health, Vol.1, no.6, p.109-111, 2015.
185. W. Vinu , “ Efficacy of extensive interval training on Vo2 max of untrained college students. International Journal of Physiology, Nutrition and Physical Education, Vol.4, no.1, p. 1570-1571, 2019.
186. J. Żywiołek and F. Schiavone, “Perception of the Quality of Smart City Solutions as a Sense of Residents’ Safety,” Energies, vol. 14, no. 17, p. 5511, 2021.
187. Żywiołek, J., Schiavone, F., The value of data sets in information and knowledge management as a threat to information security [in:] Proceedings of the European Conference on Knowledge Management, ECKM, 2021.
188. Shakir Khan and Hela Alghulaiakh, “ARIMA Model for Accurate Time Series Stocks Forecasting”, International Journal of Advanced Computer Science and Applications, 11(7), 2020.
189. Shakir Khan and Amani Alfaifi, “Modeling of Coronavirus Behavior to Predict It’s Spread”, International Journal of Advanced Computer Science and Applications, 11(5), 2020.
190. Shakir Khan, “Artificial Intelligence Virtual Assistants (Chatbots) are Innovative Investigators”, International Journal of Computer Science and Network Security Vol. 20 No. 2 pp. 93-98, 2020.
191. Shakir Khan and Alshara M, “Development of Arabic evaluations in information retrieval. International Journal of Advanced and Applied Sciences, 6(12): 92-98, 2019.
192. Shakir Khan and Mohamed F. AlAjmi, “A Review on Security Concerns in Cloud Computing and their Solutions. International Journal of Computer Science and Network Security, Vol. 19 No. 2, pp. 9-15, 2019.
193. C. Virmani, and A. Pillai. "Internet of Things and Cyber Physical Systems: An Insight." Recent Advances in Intelligent Systems and Smart Applications. Springer, Cham, pp: 379-401, 2021.
Published
2022-04-09
How to Cite
Vivekanandhan, V., M., C., M, D., & G., G. (2022). Root Depth Prediction Using Machine Learning for Effective Root Zone Injection Irrigation through IoT Automation. International Journal of Human Computing Studies, 4(4), 35-65. https://doi.org/10.31149/ijhcs.v4i4.2937