Internet of Things (IoT)-Based Smart Water Irrigation Systems: A Sustainable Approach to Water Management in Agriculture

References

[1] G. Rajeswarappa and S. Vasundra, “Red Deer and Simulation Annealing Optimization Algorithm-Based Energy Efficient Clustering Protocol for Improved Lifetime Expectancy in Wireless Sensor Networks,” Wireless Personal Communications, Aug. 2021, doi: https://doi.org/10.1007/s11277-021-08808-2. [Crossref]

[2] G. Rajeswarappa and S. Vasundra, “Self-Adaptive Cuckoo Search-Based Cluster Head Selection for Maximizing Network Lifetime in Wireless Sensor Networks,” Lecture notes in networks and systems, pp. 599–611, Jan. 2022, doi: https://doi.org/10.1007/978-981-16-7118-0_52.

[3] S. Sirisala, G. Rajeswarappa, and S. Lakumarapu, “Node Cooperation Enforcement Scheme for Enhancing Quality of Service in MANETs Using Machine Learning Approach,” Lecture Notes in Computer Science, pp. 348–355, 2023, doi: https://doi.org/10.1007/978-3-031-36402-0_32. [Crossref]

[4] G Rajeswarappa, Sivakumar Depuru, and Srinivasulu Sirisala, “Crop Pests Identification based on Fusion CNN Model: A Deep Learning,” 2022 7th International Conference on Communication and Electronics Systems (ICCES), pp. 968–974, Jun. 2023, doi: https://doi.org/10.1109/icces57224.2023.10192693.

[5] R. Govardanagiri and V. Sanjeevulu, “Hybrid Grasshopper and Improved Bat Optimization Algorithms-based clustering scheme for maximizing lifetime of Wireless Sensor Networks (WSNs),” International Journal of Intelligent Engineering and Systems, vol. 15, no. 3, p. 2022, doi: https://doi.org/10.22266/ijies2022.0630.45. [Crossref]

[6] V. Durga Prasad Jasti, Guttikonda Kranthi Kumar, M. Sandeep Kumar, V. Maheshwari, Prabhu Jayagopal, Bhaskar Pant, Alagar Karthick, M. Muhibbullah, "Relevant-Based Feature Ranking (RBFR) Method for Text Classification Based on Machine Learning Algorithm", Journal of Nanomaterials, vol. 2022, Article ID 9238968, 12 pages, 2022. https://doi.org/10.1155/2022/9238968 [Crossref]

[7] S. K. Yashwant, P. V. Krishna, B. N. V. S. B. Kumar, G. Chandan, and J. V. D. Prasad, “iLock: State-of-the-art Sophisticated Door Lock for Wireless Devices,” 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Mar. 2020, doi: https://doi.org/10.1109/icimia48430.2020.9074972. [Crossref]

[8] Bindhu, M.L.H., Potluri, T., Korra, C.B., Prasad, J.V.D. (2023). Detection and Counting of Trees in Aerial Images Using Image Processing Techniques. In: Bhateja, V., Mohanty, J.R., Flores Fuentes, W., Maharatna, K. (eds) Communication, Software and Networks. Lecture Notes in Networks and Systems, vol 493. Springer, Singapore. https://doi.org/10.1007/978-981-19-4990-6_17 [Crossref]

[9] J. V. D. Prasad, M. Sreelatha, and K. SuvarnaVani, “V-BANet: Land cover change detection using effective deep learning technique,” Ecological Informatics, vol. 75, p. 102019, Jul. 2023, doi: https://doi.org/10.1016/j.ecoinf.2023.102019. [Crossref]

[10] Meruga, S.R., Jasti, P. (2022). Land Cover Change Detection on Sentinel-2 Using GDAL and NDVI. In: Saini, H.S., Sayal, R., Govardhan, A., Buyya, R. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 385. Springer, Singapore. https://doi.org/10.1007/978-981-16-8987-1_57 [Crossref]

[11] “Iceberg Detection in Satellite Images using Deep Learning Techniques,” International Journal of Recent Technology and Engineering, vol. 8, no. 6, pp. 4701–4704, Mar. 2020, doi:https://doi.org/10.35940/ijrte.f9736.038620.

[12] V. Durga Prasad Jasti, Abu Sarwar Zamani, K. Arumugam, Mohd Naved, Harikumar Pallathadka, F. Sammy, Abhishek Raghuvanshi, Karthikeyan Kaliyaperumal, "Computational Technique Based on Machine Learning and Image Processing for Medical Image Analysis of Breast Cancer Diagnosis", Security and Communication Networks, vol. 2022, Article ID 1918379, 7 pages, 2022. https://doi.org/10.1155/2022/1918379 [Crossref]

[13] Pallavi S. Bangare, Kishor P. Patil, “Enhancing MQTT security for internet of things: Lightweight two-way authorization and authentication with advanced security measures”, Measurement: Sensors, ISSN:2665-9174, Publisher: Elsevier, Vol. 33 (2024), Article no 101212, pp.1-9. https://doi.org/10.1016/j.measen.2024.101212

[14] Pallavi S. Bangare, Kishor P. Patil, “Study and analysis of various authentication and authorization for IoT devices: A challenging overview”, International Journal of Safety and Security Engineering (IJSSE), ISSN: 2041-9031, Publisher: International Information and Engineering Technology Association (IIETA), Vol. 12, No. 2, April, 2022, pp. 209-216, https://doi.org/10.18280/ijsse.120209

[15] Pallavi S. Bangare, Kishor P. Patil, “IoT based secured data transmission protocol for Agriculture Application”, Ingénierie des Systèmes d’Information (ISI), ISSN:1633-1311, Publisher: Lavoisier, IIETA, Vol. 28 Iss.2, April 2023, 419-424. DOI: https://doi.org/10.18280/isi.280217

[16] Pallavi S. Bangare, Kishor P. Patil, “Security issues and challenges in Internet of things (IoT) system”, IEEE 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, pp.91-94, 28-29 April 2022. https://doi.org/10.1109/ICACITE53722.2022.9823709

[17] Pallavi S. Bangare, Kishor P. Patil, “A Systematic Review on the Future of Internet of Things Applications in Healthcare”, Chapter No.17, Book Title: Deep Learning in Internet of Things for Next Generation Healthcare, Edition 1st Published June 2024, Chapman and Hall/CRC, Pages 16, eBook ISBN9781003451846, DOI https://doi.org/10.1201/9781003451846

[18] P. S. Bangare, S. L. Bangare, R. U. Yawle and S. T. Patil, "Detection of human feature in abandoned object with modern security alert system using Android Application," 2017 International Conference on Emerging Trends & Innovation in ICT (ICEI), Pune, India, 2017, pp. 139-144, doi:10.1109/ETIICT.2017.7977025 https://ieeexplore.ieee.org/document/7977025

[19] Priya A. Kotwal, Kapil G. Julwani, Sunil L. Bangare, Pallavi S. Bangare, “A Location Tracer with Social Networking Services”, International Journal of Engineering and Technology (IJET), ISSN: 0975-4024, Volume 4, Issue No 1, Feb-Mar 2012, pp.19-23, Publisher: Engg. Journals Publications. https://www.enggjournals.com/ijet/docs/IJET12-04-01-017.pdf

[20] S. L. Bangare, A. D. Kadam, P. S. Bangare, P. V. Katariya, C. A. Khot, N. R. Kankure, “Solutions Concerning Information Systems for Real Time Bus Arrival”, International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249-8958 (Online), Volume-2 Issue-3, pp.316-319, February 2013. https://www.ijeat.org/wp-content/uploads/papers/v2i3/C1117022313.pdf

[21] Mutkule Prasad Raghunath, Shyam Deshmukh, Poonam Chaudhari, Sunil L. Bangare, Kishori Kasat, Mohan Awasthy, Batyrkhan Omarov, Rajesh R. Waghulde, “PCA and PSO based optimized support vector machine for efficient intrusion detection in internet of things”, Measurement: Sensors, E-ISSN:2665-9174, Publisher: Elsevier, Volume 37 (2025), 101806, pp.1-7. https://doi.org/10.1016/j.measen.2024.101806

[22] P. Nancy, P. Mutkule, K. Thakre, A. Ladkat, S. Babu, S. L. Bangare, & M. Naved, “Machine Learning and Feature Selection-Enabled Optimized Technique for Heart Disease Classification and Prediction”, Computer Assisted Methods in Engineering and Science, ISSN:2299-3649, E-ISSN:2956-5839, Volume 31(4), pp.419–429, Publisher: Institute of Fundamental Technological Research, Polish Academy of Sciences, 2024. DOI: http://dx.doi.org/10.24423/cames.2024.602

[23] Kavita A. Sultanpure, Jayashri Bagade, Sunil L. Bangare, Manoj L. Bangare, Kalyan D. Bamane, Abhijit J. Patankar, “Internet of things and deep learning based digital twins for diagnosis of brain tumor by analyzing MRI images”, Measurement: Sensors, ISSN 2665-9174, Publisher: Elseviere: ScienceDirect, Volume 33, 2024, 101220, , https://doi.org/10.1016/j.measen.2024.101220 [Crossref]

[24] J. Surve, M. L. Bangare, S. L. Bangare, U. R. Pol, M. Mali, M. Meenakshi, A. Alsalmani & S. A. Morsi, “Development of internet of vehicles and recurrent neural network enabled intelligent transportation system for smart cities”, International Journal of Reconfigurable and Embedded Systems (IJRES), Publisher: Institute of Advanced Engineering and Science (IAES), ISSN:2089-4864 E-ISSN:2722-2608, Volume 14, Issue 1, pp.291-300, March 2025. https://doi.org/10.11591/ijres.v14.i1.pp291-300

[25] Devata Anekar, Yogesh Deshpande, Sanjesh Pawale, Sunil L. Bangare, “Comprehensive Survey of Computer-Based Programs Impact on Adolescent Mental Health: Focusing on Depression and Anxiety”, Panamerican Mathematical Journal, ISSN: 1064-9735, Vol 34 No. 1 (2024), pp.141-154. https://doi.org/10.52783/pmj.v34.i1.912

[26] Mrunal Pathak, Sunil L. Bangare, Kavita Moholkar, Pranjal Pandit, R. B. Kakkeri, Pushpa M. Bangare, “Mathematical Modelling for Brain Tumor Segmentation and Classification Using Machine Learning”, Panamerican Mathematical Journal, ISSN: 1064-9735, Vol. 34, Issue No. 4 (2024), pp.211-229, https://doi.org/10.52783/pmj.v34.i4.1879

[27] Nilesh Shelke, Sushovan Chaudhury, Sudakshina Chakrabarti, Sunil L. Bangare, G. Yogapriya, Pratibha Pandey, “An efficient way of text-based emotion analysis from social media using LRA-DNN”, Neuroscience Informatics, E-ISSN:2772-5286, Volume 2, Issue 3, September 2022, 100048, pp.1-10, Publisher: Elsevier, https://doi.org/10.1016/j.neuri.2022.100048

[28] Sunil L. Bangare, “Classification of optimal brain tissue using dynamic region growing and fuzzy min-max neural network in brain magnetic resonance images”, Neuroscience Informatics, E-ISSN:2772-5286, Volume 2, Issue 3, September 2022, 100019, Publisher: Elsevier, https://doi.org/10.1016/j.neuri.2021.100019

[29] M. D. Kokate, S. N. Gujar, S. L. Bangare, D. Dhabliya, P. Sharma & M. Patil, “Securing the Future: Technological Innovations for Social Medical Public Healthcare Security”, South Eastern European Journal of Public Health, ISSN: 2197-5248, Special Volume XXIII No.1 2024 (Health Security and Informatics), pp.12–23, 2024, Publisher: Jacobs Verlag. https://doi.org/10.70135/seejph.vi.484

[30] K. P. Kamble, Sunil L. Bangare, Leena A Deshpande, Pallavi Ahire, Deepali Sanjay Chavan, Rajesh B Raut, “Use of Internet of Things (IoT) in Irrigation Management”, International Water and Irrigation, Volume 44, Issue 1 (2025), ISSN: 0334-5807, pp.245-249, Publisher: SNER Communications Ltd. https://www.intwater.com/index.php/journal/article/view/134/108

[31] Megha Dhotay, Abhijit Mitra, Amol S. Suryawanshi, Sunil L. Bangare, Ankita Tiwari, “Securing Cloud Infrastructures: A Multi-Layered Approach to Data Protection”, Computer Fraud and Security, ISSN (online): 1873-7056, Volume 2024, Issue 7, pp.126-133, Publisher: MA Healthcare Ltd. https://www.computerfraudsecurity.com/index.php/journal/article/view/69/54

[32] Sukhvinder Singh Dari, Bipin Sule, Ansh Anand Bhanushali, Sunil L. Bangare, “The Role of Artificial Intelligence in Combating Cyber Fraud”, Computer Fraud and Security, ISSN (online): 1873-7056, Volume 2024, Issue 7, pp.168-175, Publisher: MA Healthcare Ltd. https://www.computerfraudsecurity.com/index.php/journal/article/view/74/59 [Crossref]

[33] G. K. Kumar, M. L. Bangare, P. M. Bangare, C. R. Kumar, R. Raj, J. L. Arias-Gonzáles, B. Omarov, B., & M. S. Mia, “Internet of Things Sensors and Support Vector machine integrated intelligent irrigation system for agriculture industry”, Discover Sustainability, E-ISSN: 2662-9984, Volume 5, article number 6, (2024), Publisher: Springer Nature. https://doi.org/10.1007/s43621-024-00179-5

[34] M. Ritonga, M. L. Bangare, P. M. Bangare, S. L. Bangare, S. S. Vanjire, K. Moholkar, K. Kasat & P. Rozak, “Optimized convolutional neural network deep learning for Arabian handwritten text recognition”, Bulletin of Electrical Engineering and Informatics, Vol. 14, No. 2, April 2025, pp.1497-1506, ISSN: 2302-9285, Publisher: Institute of Advanced Engineering and Science (IAES). https://doi.org/10.11591/eei.v14i2.7696

[35] N. S. More, R. R. Borhade, R. S. Apare, M. L. Bangare & P. M. Bangare, “Hybrid Optimal Load Balancing with Modified Fuzzy Clustering-based Virtual Machine Categorization”, International Journal of Modeling, Simulation, and Scientific Computing, ISSN:1793-9615, Publisher: World Scientific, 2025. https://doi.org/10.1142/s1793962325500230

[36] Praveen Kumar Kollu, Manoj L. Bangare, P. Venkata Hari Prasad, Pushpa M. Bangare, Kantilal Pitambar Rane, José Luis Arias-Gonzáles, Sachin Lalar, Mohammad Shabaz, “Internet of things driven multilinear regression technique for fertilizer recommendation for precision agriculture”, SN Applied Sciences, E-ISSN:2523-3971, Volume 5, Issue 10, article number 264, pp.1-9, Publisher: Springer Nature, 2023. https://doi.org/10.1007/s42452-023-05484-8

[37] Manoj L. Bangare, Pushpa M. Bangare, Elia Ramirez-Asis, Robert Jamanca-Anaya, Chirasak Phoemchalard, Dada Ab Rouf Bhat, “Role of machine learning in improving tourism and education sector”, Materials Today: Proceedings, Volume 51, Part 8, ISSN: 2214-7853 pp.2457-2461, 2022, Publisher: Elsevier, https://doi.org/10.1016/j.matpr.2021.11.615

[38] Manoj L. Bangare, Pushpa M. Bangare, Ravindra S. Apare, Sunil L. Bangare, “Fog computing-based security of IoT application”, Design Engineering (Toronto), ISSN: 0011-9342, Issue 7, pp.7542-7549, Publisher: Rogers Media Publishing, http://www.thedesignengineering.com/index.php/DE/article/view/3262

[39] Ravindra S. Apare, Manoj L. Bangare, Pushpa M. Bangare, “Blockchain Based Privacy Preservation in Modern IoT Devices”, Design Engineering (Toronto), ISSN: 0011-9342, Issue 7, pp.7567-7575, Publisher: Rogers Media Publishing, http://www.thedesignengineering.com/index.php/DE/article/view/3265 [Crossref]

[40] Rathish Mohan, Srikanth Gangarapu, Vishnu Vardhan Reddy Chilukoori, Abhishek Vajpayee, The Evolution of Virtual Care: Impact of Advanced Features in AI-Powered Healthcare Chatbots, International Journal of Engineering and Technical Research (IJETR), Volume 9, Issue 2, pp. 78-89, September 2024. DOI: 10.5281/zenodo.13683336.

[41] Abhishek Vajpayee, Rathish Mohan, Vishnu Vardhan Reddy Chilukoori, Srikanth Gangarapu, REAL-TIME DATA PROCESSING IN PREDICTIVE MAINTENANCE: ENHANCING INDUSTRIAL EFFICIENCY AND EQUIPMENT LONGEVITY, International Journal of Remote Sensing and Earth Sciences (IJReSES), September 2024. DOI: 10.5281/zenodo.13627980

[42] Rathish Mohan, Abhishek Vajpayee, Srikanth Gangarapu, Vishnu Vardhan Reddy Chilukoori, Mitigating Complex Cyber Threats: An Integrated Multimodal Deep Learning Framework for Enhanced Security, International Journal for Research in Applied Science and Engineering Technology, Volume 12, Issue 9, pp. 1108-1117, September 2024. DOI: 10.22214/ijraset.2024.64150

[43] Abhishek Vajpayee, Rathish Mohan, Vishnu Vardhan Reddy Chilukoori, BUILDING SCALABLE DATA ARCHITECTURES FOR MACHINE LEARNING, INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY, Volume 14, Issue 4, pp. 308-320, August 2024. DOI: 10.5281/zenodo.13234031

[44] Abhishek Vajpayee, Rathish Mohan, Srikanth Gangarapu, Evolution of Data Engineering: Trends and Technologies Shaping the Future, International Journal of Innovative Research in Science Engineering and Technology, Volume 13, Issue 8, August 2024. DOI: 10.15680/IJIRSET.2024.1308009

[45] M. Sharma Vadigicherla, “Digital Twins in Supply Chain Management: Applications and Future Directions,” vol. 9001, p. 16032, 2008, doi: https://doi.org/10.15680/IJIRSET.2024.1309015|.

[46] M. S. Vadigicherla, “Enhancing Supply Chain Resilience through Emerging Technologies: A Holistic Approach to Digital Transformation,” International Journal for Research in Applied Science and Engineering Technology, vol. 12, no. 9, pp. 1319–1329, Sep. 2024, doi: https://doi.org/10.22214/ijraset.2024.64326. [Crossref]

[47] M. Sharma Vadigicherla, “The Role of Artificial Intelligence in Enhancing Supply Chain Resilience,” International Journal of Computer Engineering and Technology (IJCET), vol. 15, no. 5, pp. 45–55, 2024, doi: https://doi.org/10.5281/zenodo.13709767.

[48] M. Sharma Vadigicherla, “Article ID: IJETR_09_02_030 of Supply Chain Resilience in Industry Partnerships,” International Journal of Engineering and Technology Research (IJETR), vol. 9, no. 2, p. 2024, 2024, doi: https://doi.org/10.5281/zenodo.13838753. [Crossref]

[49] P. Borra, “Snowflake: A Comprehensive Review of a Modern Data Warehousing Platform,” SSRN Electronic Journal, 2024, doi: https://doi.org/10.2139/ssrn.4914191.

[50] None Praveen Borra, “Exploring Microsoft Azure’s Cloud Computing: A Comprehensive Assessment,” International Journal of Advanced Research in Science Communication and Technology, pp. 897–906, May 2022, doi: https://doi.org/10.48175/ijarsct-5807c.

[51] B. Praveen, Advancing Data Science and AI with Azure Machine Learning: A Comprehensive Review, International Journal of Research Publication and Reviews, Volume 5, Issue 6, June 2024, pp.1825-1831.

[52] None Praveen Borra, “Maximizing Efficiency and Collaboration with Microsoft Azure DevOps,” International Journal of Advanced Research in Science Communication and Technology, pp. 556–562, Jun. 2024, doi: https://doi.org/10.48175/ijarsct-18864.

[53] None Praveen Borra, “Securing Cloud Infrastructure: An In-Depth Analysis of Microsoft Azure Security,” International Journal of Advanced Research in Science, Communication and Technology, pp. 549–555, Jun. 2024, doi: https://doi.org/10.48175/ijarsct-18863.

[54] P. Borra, M. Mullapudi, H. Nerella, and L. K. Prakashchand, “Analyzing AWS Edge Computing Solutions to Enhance IoT Deployments,” International Journal of Engineering and Advanced Technology, vol. 13, no. 6, pp. 8–12, Aug. 2024, doi: https://doi.org/10.35940/ijeat.f4519.13060824.

[55] P. Borra, “The Transformative Role of Microsoft Azure AI in Healthcare,” International Journal of Emerging Trends in Engineering Research, vol. 12, no. 7, pp. 108–113, Jul. 2024, doi: https://doi.org/10.30534/ijeter/2024/021272024.

[56] B. Praveen, Advancing Artificial Intelligence with AWS Machine Learning: A Comprehensive Overview, International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), Volume 4, Issue 2, June 2024, pp.71-78.

[57] P. Borra, “Impact and Innovations of Azure IoT: Current Applications, Services, and Future Directions,” International Journal of Recent Technology and Engineering (IJRTE), vol. 13, no. 2, pp. 21–26, Jul. 2024, doi: https://doi.org/10.35940/ijrte.b8111.13020724

[58] None Praveen Borra, “The Evolution and Impact of Google Cloud Platform in Machine Learning and AI,” International Journal of Advanced Research in Science Communication and Technology, vol. 4, no. 3, pp. 72–77, Jun. 2024, doi: https://doi.org/10.48175/ijarsct-18908.

[59] None Praveen Borra, “A Survey of Google Cloud Platform (GCP): Features, Services, and Applications,” International Journal of Advanced Research in Science, Communication and Technology, vol. 4, no. 3, pp. 191–199, Jun. 2024, doi: https://doi.org/10.48175/ijarsct-18922.

[60] None Praveen Borra, “Microsoft Azure Networking: Empowering Cloud Connectivity and Security,” International Journal of Advanced Research in Science, Communication and Technology, pp. 469–475, Jun. 2024, doi: https://doi.org/10.48175/ijarsct-18949.

[61] B. Praveen, Comprehensive Survey of Amazon Web Services (AWS): Techniques, Tools, and Best Practices for Cloud Solutions, INTERNATIONAL RESEARCH JOURNAL OF ADVANCED ENGINEERING AND SCIENCE, Volume 9, Issue 3, 2024, pp.24-29.

[62] M. Saraswat and R. C. Tripathi, “Cloud Computing: Comparison and Analysis of Cloud Service Providers-AWs, Microsoft and Google,” 2020 9th International Conference System Modeling and Advancement in Research Trends (SMART), pp. 281–285, Dec. 2020, doi: https://doi.org/10.1109/smart50582.2020.9337100.

[63] P. Borra, “EVALUATION OF TOP CLOUD SERVICE PROVIDERS’ BI TOOLS: A COMPARISON OF AMAZON QUICKSIGHT, MICROSOFT POWER BI, AND GOOGLE LOOKER,” INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY (IJCET), vol. 15, no. 3, pp. 150–156, Jun. 2024, Accessed: Feb. 20, 2025. [Online]. Available: https://iaeme.com/Home/article_id/IJCET_15_03_014

[64] M. Bairoja, M. Mohamedaskhan, B. Bharathivijay, and P. Tamilselvan, “Security Information and Event Management (SIEM) Tool.” Accessed: Feb. 20, 2025. [Online]. Available: https://www.espjeta.org/ICEAIST-24/ICEAIST-M138.pdf

[65] P. Borra, “Impact and Innovations of Azure IoT: Current Applications, Services, and Future Directions,” International Journal of Recent Technology and Engineering (IJRTE), vol. 13, no. 2, pp. 21–26, Jul. 2024, doi: https://doi.org/10.35940/ijrte.b8111.13020724

[66] P. Borra, “COMPARATIVE REVIEW: TOP CLOUD SERVICE PROVIDERS ETL TOOLS - AWS VS. AZURE VS. GCP,” INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY (IJCET), vol. 15, no. 3, pp. 203–208, Jun. 2024, Accessed: Feb. 20, 2025. [Online]. Available: https://iaeme.com/Home/article_id/IJCET_15_03_019

[67] B. Praveen, Nerella, Harshavardhan, AI Revolution in Healthcare: AWS Innovations and Future Directions, ESP Journal of Engineering & Technology Advancements, Volume 4, Issue 3, July 2024, pp.23-27.

[68] B. Praveen, An Overview of Cloud Computing and Leading Cloud Service Providers, International Journal of Computer Engineering and Technology, Volume 15, Issue 3, May 2024, pp.122-133.

[69] U. Ramanathan, S. Rajendran, Devi Thiyagarajan, and E. Rajendran, “A Hybrid Modified Artificial Bee Colony (ABC)-Based Artificial Neural Network Model for Power Management Controller and Hybrid Energy System for Energy Source Integration,” pp. 35–35, Dec. 2023, doi: https://doi.org/10.3390/engproc2023059035. [Crossref]

[70] U. Ramanathan and S. Rajendran, “Weighted Particle Swarm Optimization Algorithms and Power Management Strategies for Grid Hybrid Energy Systems,” pp. 123–123, Dec. 2023, doi: https://doi.org/10.3390/engproc2023059123. [Crossref]

[71] P. Panwar, M. Shabaz, S. Nazir, I. Keshta, A. Rizwan, and R. Sugumar, “Generic Edge Computing System for Optimization and Computation Offloading of Unmanned Aerial Vehicle,” Computers and Electrical Engineering, vol. 109, p. 108779, Jul. 2023, doi: https://doi.org/10.1016/j.compeleceng.2023.108779.

[72] U. Dr.R., Dr. P. B. K. Chowdary, D. Dr.T., and S. Dr.R., “Integrated SVM-FFNN for Fraud Detection in Banking Financial Transactions,” Journal of Internet Services and Information Security, vol. 13, no. 4, pp. 12–25, Dec. 2023, doi: https://doi.org/10.58346/jisis.2023.i4.002. [Crossref]

[73] A. and, “Real-time Migration Risk Analysis Model for Improved Immigrant Development Using Psychological Factors,” Migration Letters, vol. 20, no. 4, pp. 33–42, 2023, doi: https://doi.org/10.59670/ml.v20i4.2979. [Crossref]

[74] R. Udayakumar, A. Joshi, S.S. Boomiga, R. Sugumar, Deep Fraud Net: A Deep Learning Approach for Cyber Security and Financial Fraud Detection and Classification, Journal of Internet Services and Information Security (JISIS), Volume 13, Issue 4, November 2023, pp. 138-157.

[75] R. Udayakumar, R.Elankavi, V.R.Vimal, R. Sugumar, Improved Particle Swarm Optimization With Deep Learning-Based Municipal Solid Waste Management In Smart Cities, Revista de Gestao Social e Ambiental, Volume 17, Issue 4, July 2023

[76] R.Udayakumar, Suvarna Yogesh, Yogesh Manohar, V.R.Vimal, R.Sugumar, User Activity Analysis Via Network Traffic Using DNN and Optimized Federated Learning based Privacy Preserving Method in Mobile Wireless Networks, Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 14(2), pp. 66–81, June 2023.

[77] R. Udayakumar, Muhammad Abul Kalam, R. Sugumar, R. Elankavi, Assessing Learning Behaviors Using Gaussian Hybrid Fuzzy Clustering (GHFC) in Special Education Classrooms, Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA), Volume 14, Number 1, March 2023, pp. 118-125.

[78] Arul Raj.A.M and Sugumar R., “Estimating social distance in public places for COVID-19 protocol using region CNN” Published in Indonesian journal of Electrical Engineering and computer science (IJEECS) , Vol. 30, No. 1, April2023,pp.414-421,ISSN:2502-4752, Indonesia., DOI: 10.11591/ijeecs.v30.i1.pp414-421. Impact Factor: 1.94.

[79] Arul Raj.A.M and Sugumar R., “ Enhanced convolutional neural network enabled optimized diagnostic model for COVID-19 detection” published in Bulletin of Electrical Engineering and Informatics (BEEI) , Vol. 13, No. 3, June 2024, pp. 1935~1942,ISSN: 2302-9285, DOI: 10.11591/eei.v13i3.6393, Impact Factor: 1.96.

[80] Arul Raj A.M.,Sugumar R.,Padmkala .S., “Detection of Covid-19 based on convolutional neural networks using pre-processed chest X-ray images”, AIP Advances, Volume 14, issue 3, 035150-March(2024),AIP-Publishing, ISSN/eISSN:2158-3226. https://doi.org/10.1063/5.0188957 Impact Factor: 1.6.

[81] Yahya Alqahtani, Umakant Mandawkar, Aditi Sharma, Mohammad Najmus Saquib Hasan, Mrunalini Harish Kulkarni, R. Sugumar, Breast Cancer Pathological Image Classification Based on the Multiscale CNN Squeeze Model, Journal of Computational Intelligence and Neuroscience, September 2022. (IF: 3.12). [Scopus Indexed]

[82] Arul Raj .A.M and Sugumar R., "Estimation of Social Distance for COVID19 Prevention using K-Nearest Neighbor Algorithm through deep learning," 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), Mysuru, India, 2022, pp. 1-6. March 2023, , ISBN:978-166549790-9. DOI:10.1109/MysuruCon55714.2022.9972422

[83] Arul Raj .A.M and Sugumar R.,” Monitoring of the social Distance between Passengers in Real-time through video Analytics and Deep learning in Railway stations for Developing highest Efficiency” , March 2023 International Conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2022, ISBN 979-835033384-8, March 2023, Chennai , India ., DOI 10.1109/ICDSAAI55433.2022.10028930.

[84] Arul Raj .A.M and Sugumar R., “A Deep Learning-Based Preventive Measures of COVID-19 in a crowd using Reinforcement Model over GAN for Enhanced efficiency”, 2023 3rd International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2023 Bhilai., India., 5 January 2023through 6 January 2023Code 188686, Publisher by Institute of Electrical and Electronics Engineers Inc, ISBN:978-166549400-7 DOI 10.1109/ICAECT57570.2023.10118327.

[85] Arul Raj .A.M and Sugumar R., “Multi-Modal Fusion of Deep Learning with CNN based COVID-19 Detection and Classification Combining Chest X-ray Images,” 7th International Conference on Intelligent Computing and Control Systems, Madurai., India., ICICCS 2023, Code 189354, Pages 569 – 5752023, 17 May 2023 through 19 May 2023,ISBN:979-835039725-3, DOI : 10.1109/ICICCS56967.2023.10142910.

[86] Arul Raj .A.M and Sugumar R., “ Enhancing COVID-19 Diagnosis with Automated Reporting using Preprocessed Chest X-Ray Image Analysis based on CNN,” 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023, Salem.,India., Code 189334, Pages 35 - 402023 , 4 May 2023 through 6 May 2023, ISBN:978-166545630-2, DOI: 10.1109/ICAAIC56838.2023.10141515

[87] Arul Raj .A.M and Sugumar R., “A Deep Learning Framework for COVID-19 Detection in X-Ray Images with Global Thresholding ,” 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Institute of Electrical and Electronics Engineers Inc, ViTECoN 2023, Vellore.,India., Code-190031, Aug 2023, ISBN-979-835034798-2, DOI-10.1109/ViTECoN58111.2023.10157404.

[88] Arul Raj .A.M and Sugumar R., “Early Detection of COVID-19 with Impact on Cardiovascular Complications using CNN Utilising Pre-Processed Chest X-Ray Images”, (ICAISC-2023) August 2023, ISBN:979-8-3503-2380-1, https://doi.org/10.1109/ICAISC58445.2023.10199456 , 1st IEEE International Conference on Applied Intelligence and Sustainable Computing, ICAISC 2023 Hybrid, Dharwad., India.,

[89] B Yamini, K Sudha, M Nalini, G Kavitha, R Siva Subramanian, R Sugumar, Predictive Modelling for Lung Cancer Detection using Machine Learning Techniques, 2023 8th International Conference on Communication and Electronics Systems (ICCES), pp.1220-1226. [Crossref]

[90] Vivek Balaji, K., Sugumar, R., Harnessing the Power of Machine Learning for Diabetes Risk Assessment: A Promising Approach, 2023 International Conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2023, 2023

[91] Zekrifa, D. M. S., Saravanakumar, R., Nair, S., Pachiappan, K., Vetrithangam, D., Kalavathi Devi, T., ... & Rukmani Devi, S. Securing energy horizons: Cloud-driven based machine learning methods for battery management systems. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-15.

[92] Praveenchandar, J., Vetrithangam, D., Kaliappan, S., Karthick, M., Pegada, N. K., Patil, P. P., ... & Umar, S. (2022). IoT-Based harmful toxic gases monitoring and fault detection on the sensor dataset using deep learning techniques. Scientific Programming, 2022.

[93] Brahma Reddy Katam (2024), AI-Driven Mood Analysis for Employee Wellbeing: A Proactive Approach to Enhancing Workplace Productivity. International Journal of Innovative Science and Research Technology (IJISRT) IJISRT24SEP1264, 2833-2836. DOI: 10.38124/ijisrt/IJISRT24SEP1264. https://www.ijisrt.com/aidriven-mood-analysis-for-employee-wellbeing-a-proactive-approach-to-enhancing-workplace-productivity [Crossref]

[94] Brahma Reddy Katam. "Improving the Performance of Autonomous Vehicles through Data Engineering, Machine Learning, AI, and Integrated Hardware-Software Solutions.” Volume. 9 Issue.8, August - 2024 International Journal of Innovative Science and Research Technology (IJISRT), www.ijisrt.com. ISSN - 2456-2165, PP:- 180-182, https://doi.org/10.38124/ijisrt/IJISRT24AUG085 [Crossref]

[95] Katam, B.R. (2024). Data + AI Driven Solutions for Enhancing Employee Wellbeing and Work-Life Balance.INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT.https://doi.org/10.55041/ijsrem36975 [Crossref]

[96] Brahma Reddy Katam, “Case Study: Leveraging Databricks to Process Health Care Claims Data and Detect Risks,” International Journal of Scientific Research in Engineering and Management (, vol. 08, no. 07, pp. 1–5, Feb. 2025.

[97] Brahma Reddy Katam, “Optimizing Data Pipeline Efficiency with Machine Learning Techniques,” International Journal of Scientific Research in Engineering and Management, vol. 8, no. 7.

[98] Das, P., Vetrithangam, D., Krishnan, G. H., Kumar, A., & Reddy, R. V. K. (2023). Deep Learning Techniques Revolutionizing Biomedical Applications: Arrhythmia Detection, Cardiac Sensed Signals, and Cell-Free Synthetic Biology. In Applications of Synthetic Biology in Health, Energy, and Environment (pp. 68-91). IGI Global.

[99] Vetrithangam, D., SATVE, P. P., KUMAR, J. R. R., Anitha, P., Vidhya, S., & SAINI, A. K. (2023). prediction of pneumonia disease from x-ray images using a modified resnet152v2 deep learning model. Journal of Theoretical and Applied Information Technology, 101(17).

[100] Vetrithangam, D., Pegada, N. K., Himabindu, R., & Arunadevi, B. (2023). State-of-the-Art Review on the Models, Techniques, and Datasets to Diagnose COVID-19 Disease. Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence, 208-233.

[101] VETRITHANGAM, D., SHRUTI, P., ARUNADEVI, B., HIMABINDU, R., KUMAR, P. N., KUMAR, A. R., ... & ARNET ZITHA, D. R. (2023). OPTIMUM FEATURE SELECTION BASED BREAST CANCER PREDICTION USING MODIFIED LOGISTIC REGRESSION MODEL. Journal of Theoretical and Applied Information Technology, 101(8).

[102] Vetrithangam, D., Ebin, P. M., Nareshkumar, P., Arunadevi, B., Fathima, A., & Kumar, A. R. (2023, September). Enhanced Vgg-19 Model for Accurate Brain Tumor Prediction. In 2023 International Conference on Network, Multimedia and Information Technology (NMITCON) (pp. 1-6). IEEE

[103] Raj, A., & Vetrithangam, D. (2023, April). Machine Learning and Deep Learning technique used in Customer Churn Prediction:-A Review. In 2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) (pp. 139-144). IEEE.

[104] Aleza, M. E., & Vetrithangam, D. (2023, April). Use of Artificial Intelligence to Avoid Errors in Referring a Football Match. In 2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1) (pp. 1-6). IEEE.

[105] Raj, A., & Vetrithangam, D. (2023, April). Prediction of customer churn using resampling and ensemble classification algorithms on telecom dataset. In 2023 11th International Conference on Emerging Trends in Engineering & Technology-Signal and Information Processing (ICETET-SIP) (pp. 1-7). IEEE.

[106] Chakraborty, A., & Vetrithangam, D. (2023, April). ExRAN: Deep Ensemble Majority Voting using Transfer Learning for Brain tumor Identification from Magnetic Resonance Imaging. In 2023 International Conference on Inventive Computation Technologies (ICICT) (pp. 130-134). IEEE

[107] VETRITHANGAM, D., SENTHILKUMAR, V., NEHA, A., NARESH, P., & KUMAR, M. S. (2022). CORONARY ARTERY DISEASE PREDICTION BASED ON OPTIMAL FEATURE SELECTION USING IMPROVED ARTIFICIAL NEURAL NETWORK WITH META-HEURISTIC ALGORITHM. Journal of Theoretical and Applied Information Technology, 100(24).

[108] Pegada, N. K., Vetrithangam, V., Fathima, A., & Arunadevi, A. (2022, October). A survey on various image analysis techniques. In AIP Conference Proceedings (Vol. 2555, No. 1). AIP Publishing.

[109] Vetrithangam, V., Devi, A., & Aggarwal, S. (2022, October). Multi disease prediction based on combined deep reinforcement Boltzmann machines. In AIP Conference Proceedings (Vol. 2555, No. 1). AIP Publishing.

[110] Praveenchandar, J., Vetrithangam, D., Kaliappan, S., Karthick, M., Pegada, N. K., Patil, P. P., ... & Umar, S. (2022). IoT-Based harmful toxic gases monitoring and fault detection on the sensor dataset using deep learning techniques. Scientific Programming, 2022.

[111] Aggarwal, S., Suchithra, M., Chandramouli, N., Sarada, M., Verma, A., Vetrithangam, D., ... & Ambachew Adugna, B. (2022). Rice disease detection using artificial intelligence and machine learning techniques to improvise agro-business. Scientific Programming, 2022.

[112] Indira, V., Umar, S., Pant, B., & Goyal, M. K. (2022). Discriminating the Pneumonia-Positive Images from COVID-19-Positive Images Using an Integrated Convolutional Neural Network. Mathematical Problems in Engineering, 2022.

[113] VETRITHANGAM, D., ARUNADEVI, B., KUMAR, A. K., & NALINI, S. (2023). OLGV3 NET: OPTIMIZED LIGHTGBM WITH INCEPTIONV3 FOR ACCURATE MULTI-CLASS BREAST CANCER IMAGE CLASSIFICATION. Journal of Theoretical and Applied Information Technology, 101(24).

[114] KANTAMANENI, P., VETRITHANGAM, D., SAISREE, M. M., SHARGUNAM, S., KUMAR, S. S., & BEKKANTI, A. (2023). OPTIMIZED FUZZY C-MEANS (FCM) CLUSTERING FOR HIGH-PRECISION BRAIN IMAGE SEGMENTATION AND DIAGNOSIS USING DENSENET FEATURES. Journal of Theoretical and Applied Information Technology, 101(24).

[115] Paul, S. P., & Vetrithangam, D. (2023). Design and Analysis of an Efficient and Load-Balanced Multipath Routing Algorithm for Energy-Effective Wireless Sensor Networks. International Journal of Intelligent Systems and Applications in Engineering, 11(10s), 601-617.

[116] PAUL, S. P., & VETRITHANGAM, D. (2023). A FULL-SCALE ANALYSIS ON CHALLENGES AND ISSUES OF NEXT GENERATION (5G) COMMUNICATION IN HETEROGENEOUS WIRELESS NETWORK BASED ENTERPRISE APPLICATIONS. Journal of Theoretical and Applied Information Technology, 101(11).

[117] Paul, S. P., & Vetrithangam, D. (2023, March). A Scientometric Study of Research Development on Cloud Computing-Based Data Management Technique. In Doctoral Symposium on Computational Intelligence (pp. 617-625). Singapore: Springer Nature Singapore.

[118] Paul, S. P., & Vetrithangam, D. (2023, June). A Thorough Assessment on Orthogonal Frequency Division Multiplexing (OFDM) based Wireless Communication: Challenges and Interpretation. In 2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) (pp. 1145-1151). IEEE.

[119] Nancy, Raghuvanshi, A. (2023). Detection of brain tumour using machine learning based framework by classifying MRI images. International Journal of Nanotechnology,Inderscience Publication. 20(5/6/7/8/9/10), 880–896. doi:10.1504/ijnt.2023.134040

[120] Sharma, P., Raghuvanshi, A., & Pachori, R. (2019). Artificial intelligence and soft computing: Soft computing techniques: Artificial intelligence, neural networks, fuzzy logic and genetic algorithm. Chhattisgarh, India: Educreation Publishing.

[121] Mutyalaiah Paricherla, Mahyudin Ritonga, S. R. Shinde, S. M. Chaudhari, Rahmat Linur, and Abhishek Raghuvanshi, “Machine learning techniques for accurate classification and detection of intrusions in computer network,” Bulletin of Electrical Engineering and Informatics, vol. 12, no. 4, pp. 2340–2347, Aug. 2023, doi: https://doi.org/10.11591/eei.v12i4.4708. [Crossref]

[122] D. Teja Santosh et al., “Development of IoT based intelligent irrigation system using particle swarm optimization and XGBoost techniques,” Bulletin of Electrical Engineering and Informatics, vol. 13, no. 3, pp. 1927–1934, Jun. 2024, doi: https://doi.org/10.11591/eei.v13i3.6332. [Crossref]

[123] S. Dave and Abhishek Raghuvanshi, “Performance improvement in Distributed Systems through Replication and Checkpointing,” International Journal of Computer Applications, vol. 42, no. 19, pp. 17–21, Mar. 2012, doi: https://doi.org/10.5120/5800-8039. [Crossref]

[124] Ankit Jain, Abhishek Raghuvanshi, “Analysis Of Query Based Text Classification Approach”, International Journal of Advanced Research in Computer Science, 2012, Vol. 2, Pp.2, Pp.62, 2277128x

[125] M. Jawarneh, M. Alshar’e, D. A. Dewi, M. Al Nasar, R. Almajed, and A. Ibrahim, “The Impact of Virtual Reality Technology on Jordan’s Learning Environment and Medical Informatics among Physicians,” International Journal of Computer Games Technology, vol. 2023, p. e1678226, Feb. 2023, doi: https://doi.org/10.1155/2023/1678226.

[126] Mustafa, M., Alzubi, S., Alshare, M. (2020). The Moderating Effect of Demographic Factors Acceptance Virtual Reality Learning in Developing Countries in the Middle East. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T., Valentino, G. (eds) Advances in Computing and Data Sciences. ICACDS 2020. Communications in Computer and Information Science, vol 1244. Springer, Singapore. https://doi.org/10.1007/978-981-15-6634-9_2 [Crossref]

[127] Alshar’e, M. (2023). CYBER SECURITY FRAMEWORK SELECTION: COMPARISION OF NIST AND ISO27001. Applied Computing Journal, 3(1), 245-255. https://doi.org/10.52098/acj.202364 [Crossref]

[128] Alshar’e, “A USER PROTECTION MODEL FOR THE TRUSTED COMPUTING ENVIRONMENT,” Journal of Computer Science, vol. 10, no. 9, pp. 1692–1702, Sep. 2014, doi: https://doi.org/10.3844/jcssp.2014.1692.1702.

[129] M. Alshar& et al., “Usability Evaluation of Educational Games: An Analysis of Culture as a Factor Affecting Children’s Educational Attainment.,” Advances in Human-Computer Interaction, vol. 2022, Aug. 2022, doi: https://doi.org/10.1155/2022/9427405. [Crossref]

[130] F. Najar et al., "Efficient Statistical Learning Framework with Applications to Human Activity and Facial Expression Recognition," 2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), Sousse, Tunisia, 2020, pp. 1-6, doi: 10.1109/ATSIP49331.2020.9231759.

[131] Marwan Ibrahim Alshar’e, R. Sulaiman, M. R. Mokhtar, and Abdullah MohdZin, “DESIGN AND IMPLEMENTATION OF THE TPM USER AUTHENTICATION MODEL,” Journal of Computer Science, vol. 10, no. 11, pp. 2299–2314, Nov. 2014, doi: https://doi.org/10.3844/jcssp.2014.2299.2314.

[132] Hussein Albazar, A. Abdel-Wahab, Marwan Alshar'e, and A. M. Abualkishik, “An Adaptive Two-Factor Authentication Scheme Based on the Usage of Schnorr Signcryption Algorithm,” Informatica, vol. 47, no. 5, May 2023, doi: https://doi.org/10.31449/inf.v47i5.4627.

[133] M. Alshar’e, A. Albadi, M. Mustafa, N. Tahir, and M. Al Amri, “A Framework of the Training Module for Untrained Observers in Usability Evaluation Motivated by COVID-19: Enhancing the Validity of Usability Evaluation for Children’s Educational Games,” Advances in Human-Computer Interaction, vol. 2022, pp. 1–11, Mar. 2022, doi: https://doi.org/10.1155/2022/7527457.

[134] M. Alshar'e, M. R. Al Nasar, R. Kumar, M. Sharma, Dharamvir and V. Tripathi, "A Face Recognition Method In Machine Learning (ML) For Enhancing Security In Smart Home," 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2022, pp. 1081-1086, doi: 10.1109/ICACITE53722.2022.9823833.

[135] F. Y. H. Ahmed, J. H. Yousif, Marwan Alshar’e, Maram El Sheikh, Ehsan Al-Ajmi, and Mahmood Al-Bahri, “Smart In-Cabin Air Monitoring System using IoT Technologies,” Qubahan Academic Journal, vol. 4, no. 1, pp. 78–90, Jan. 2024, doi: https://doi.org/10.58429/qaj.v4n1a275.

[136] M. Al-Bahri, W. Alkishri, F. Y. H. Ahmed, M. Alshar’e, and S. A. Maskari, “Enhancing IoT Network Security Through Digital Object Architecture-Based Approaches,” Qubahan Academic Journal, vol. 4, no. 1, pp. 224–239, Mar. 2024, doi: https://doi.org/10.48161/qaj.v4n1a413.

[137] R. S. Cordova, L. R. Maata, M. Jawarneh, M. I. Alshar’e, and O. C. Agustin, “Accurate prediction of chronic diseases using deep learning algorithms,” IAES International Journal of Artificial Intelligence, vol. 14, no. 1, pp. 570–570, Nov. 2024, doi: https://doi.org/10.11591/ijai.v14.i1.pp570-583.

[138] “Enhancing Data Protection in Digital Communication: A Novel Method of Combining Steganography and Encryption,” KSII Transactions on Internet and Information Systems, vol. 18, no. 6, Jun. 2024, doi: https://doi.org/10.3837/tiis.2024.06.011. [Crossref]

@article{1707348,
      author = {Dr. Abhishek Raghuvanshi},
      title = {Internet of Things (IoT)-Based Smart Water Irrigation Systems: A Sustainable Approach to Water Management in Agriculture},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {9},
      pages = {127-140},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1707348.pdf},
      abstract = {Water scarcity is one of the most significant challenges facing the global agricultural sector, particularly in regions with arid climates and limited water resources. The need for efficient water management practices is essential to ensure food security while minimizing environmental impact. Internet of Things (IoT)-based smart water irrigation systems have emerged as a solution to optimize water usage by integrating real-time data collection, processing, and automation in agricultural practices. This paper explores the potential of IoT-based irrigation systems, their components, benefits, challenges, and future developments in the context of sustainable water management for agriculture.},
      month = {March},
  }