Micro Irrigation by Integrating AI to Predict Crop Water Needs and Automate Valves and Boost Yield
Abstract
This study suggests combining artificial intelligence (AI) with micro irrigation technologies to improve how farmers manage water for their crops. Micro irrigation systems give water to crops very accurately, but they have trouble adjusting to changes in the weather and the water needs of the crops. This project wants to use AI algorithms to figure out how much water crops will require and to automatically open and close valves based on weather forecasts. The predictive modelling part is about making AI algorithms that can use information like the type of crop, the amount of moisture in the soil, and the weather to guess how much water the crops will need. The model will be trained using machine learning approaches including regression analysis and neural networks. The model's accuracy will keep getting better as it gets more historical and real-time data. To make the micro irrigation system automatic, smart valves, sensors, and actuators will be added. The AI algorithm and real-time weather data will tell these valves when to open and close. The goal of this dynamic adjustment is to make water delivery as efficient as possible while wasting as little as possible. Some of the main benefits are that it can respond to weather events before they happen, it can grow, and it works with current farming methods. User-friendly interfaces will make it possible to monitor and control things from afar. In conclusion, combining AI with micro irrigation systems is a promising way to make farming more environmentally friendly, use water more efficiently, and grow more crops.
References
N. H. M. Shamsuddin, N. A. Ali, and R. Alwee, “An overview on crime prediction methods,” in 2017 6th ICT International Student Project Conference (ICT-ISPC), Johor, Malaysia, 2017.
D. Ganesan, V. J. Francina, and V. P. Rameshkumaar, "Effectiveness of Corporate Responsibility Advertising Messages of Automobile Companies among Audience Perception," International Journal of Mechanical Engineering and Technology (IJMET), vol. 10, no. 2, pp. 934–941, 2019.
K. Priya, R. V, S. A. Krishnan, V. P. Rameshkumaar, B. Premkumar and P. Jyothi, "Exploring Effective Leadership Strategies to Drive Organisational Success & Foster Sustainable Growth," 2024 Second International Conference on Advances in Information Technology (ICAIT), Chikkamagaluru, Karnataka, India, 2024, pp. 1-6.
K. Priya, V. Rohini, S. A. Krishnan, V. P. Rameshkumaar, B. Premkumar, and P. Jyothi, "Exploring Effective Leadership Strategies to Drive Organisational Success & Foster Sustainable Growth," in Proc. 2024 Second International Conference on Advances in Information Technology (ICAIT), vol. 1, pp. 1–6, Jul. 24, 2024. IEEE.
K. Selvavinayagam, V. J. Francina, and V. P. Rameshkumaar, "Evaluation of Logistic Performance Index of India in the Indian Postal Services," International Journal of Engineering and Management Research (IJEMR), vol. 8, no. 5, pp. 80–87, 2018.
D. Thankachan, S. S. Ranganathan, P. D. Pachamuthu, V. Ravi, G. Manickam, and M. Alagarsamy, "Deep Learning-Enabled Holistic Control and Prediction System for Building Energy Consumption and Distribution Optimization," Electric Power Components and Systems, pp. 1-15, Apr. 1, 2024, Taylor & Francis.
J. Krithika, K. R. Sowmya, and P. Prabadevi, "Behavioural Based Safety Practices at Small Manufacturing Units at Chennai," International Journal of Recent Technology and Engineering (IJRTE), vol. 8, no. 6, pp. 1501-1506, 2020.
M. S. Kamalaveni, K. Parthiban, K. Sivasubramani, and P. P. Devi, "An evaluation of public health and healthcare policies in India," AIP Conf. Proc., vol. 3306, p. 030017, 2025.
S. Y. Malathi and R. B. Geeta, “Classification of knee X-ray images by severity of osteoarthritis using skip connection based ResNet101,” Int. J. Intell. Eng. Syst., vol. 16, no. 5, p. 738, 2023.
S. Y. Malathi and R. B. Geeta, “A novel method on CNN-LSTM to characterize knee osteoarthritis from radiography,” Proc. Natl. Acad. Sci., India, Sect. B: Biol. Sci., 2023.
K. S. Sharada, R. B. Geeta, K. K. Manohara, and S. Y. Malathi, “Insight analysis of deep learning and a conventional standardized evaluation system for assessing rice crop's susceptibility to salt stress during the seedling stage,” SN Comput. Sci., 2023.
S. Y. Malathi, R. B. Geeta, and K. S. Sharada, “Diagnosing and grading knee osteoarthritis from X-ray images using deep neural angular extreme learning machine,” Proc. Indian Natl. Sci. Acad., vol. 90, no. 2, 2024.
S. K. Shiragudikar, G. Bharamagoudar, K. K. Manohara, S. Y. Malathi, and G. S. Totad, “Predicting salinity resistance of rice at the seedling stage: An evaluation of transfer learning methods,” in Intelligent Systems in Computing and Communication (ISCComm 2023), CCIS, vol. 2231, Cham: Springer, 2025.
S. Malathi, G. Bharamagoudar, S. K. Shiragudikar, and G. S. Totad, “Predictive models for the early diagnosis and prognosis of knee osteoarthritis using deep learning techniques,” in Intelligent Systems in Computing and Communication (ISCComm 2023), CCIS, vol. 2231, Cham: Springer, 2025.
S. K. Shiragudikar and G. Bharamagoudar, “Enhancing rice crop resilience: Leveraging image processing techniques in deep learning models to predict salinity stress of rice during the seedling stage,” Int. J. Intell. Syst. Appl. Eng., vol. 12, no. 14s, pp. 116–124, 2024.
S. G. K. Peddireddy, “Advancing Threat Detection in Cybersecurity through Deep Learning Algorithms,” FMDB Transactions on Sustainable Intelligent Networks., vol.1, no. 4, pp. 190–200, 2024.
S. G. K. Peddireddy, “Integrating AI for Proactive Network Defense against Emerging Security Vulnerabilities,” FMDB Transactions on Sustainable Computer Letters., vol. 2, no. 4, pp. 232–241, 2024.
S. G. K. Peddireddy, “Optimizing Resource Allocation in Multi-Cloud Environments for Cost Efficiency and Scalability,” FMDB Transactions on Sustainable Computing Systems., vol. 2, no. 4, pp. 167–177, 2024.
R. Rai, “A brief assessment of kiwifruit cultivation status in Nepal,” J. Multidiscip. Sci., vol. 7, no. 1, pp. 46–55, 2025.
A. Nepal, C. Joshi, N. Khatiwada, P. B. Chhetri, R. S. Chhetri, P. Kathayat, B. Mahara, and R. Rai, “Evaluation of the conversion of farming systems and scaling up of agroecological approaches in Nepal,” J. Multidiscip. Sci., vol. 7, no. 1, pp. 11–25, 2025.
A. Badarch, R. Rai, and J.-H. Kim, “Estimation and analysis of the impact of habitats and chromosomes on trichome variation in Lilium amabile Palibian,” J. Multidiscip. Sci., vol. 7, no. 1, pp. 1–10, 2025.
A. Nepal, K. Koirala, S. Rai, and R. Rai, “Agrobiodiversity integration in farming systems for income generation and livelihood options of smallholder farmers in Nepal: A case study of Bhimphedi Municipality,” J. Exp. Biol. Agric. Sci., vol. 13, no. 1, pp. 29–49, 2025.
S. Rai, A. Nepal, S. Basi, T. Dhakal, and R. Rai, “Present status, practices, limitations, and future prospects of organic fruit production in Nepal,” J. Exp. Biol. Agric. Sci., vol. 13, no. 1, pp. 1–10, 2025.
R. Rai and J.-H. Kim, “Heterosis and combining ability among promising single cross hybrids in Lilium formolongi Hort. for major growth and flowering traits,” Academia Biology, vol. 2, no. 4, 2024.
R. Rai, A. Shrestha, S. Rai, S. Chaudhary, D. K. Acharya, and S. Subedi, “Conversion of farming systems into organic bio-intensive farming systems and the transition to sustainability in agroecology: Pathways towards sustainable agriculture and food systems,” J. Multidiscip. Sci., vol. 6, no. 2, pp. 25–34, 2024.
S. Rai and R. Rai, “Advancements and practices in budding techniques for kiwifruit propagation,” J. Multidiscip. Sci., vol. 6, no. 2, pp. 11–16, 2024.
S. Rai and R. Rai, “Monkey menace in Nepal: An analysis and proposed solutions,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 26–31, 2024.
A. K. Shrestha, S. Chaudhary, S. Subedi, S. Rai, D. K. Acharya, and R. Rai, “Farming systems research in Nepal: Concepts, design, and methodology for enhancing agricultural productivity and sustainability,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 17–25, 2024.
S. Rai and R. Rai, “Advancement of kiwifruit cultivation in Nepal: Top working techniques,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 11–16, 2024.
S. Chaudhary, A. K. Shrestha, S. Rai, D. K. Acharya, S. Subedi, and R. Rai, “Agroecology integrates science, practice, movement, and future food systems,” J. Multidiscip. Sci., vol. 5, no. 2, pp. 39–60, 2023.
R. Rai, V. Y. Nguyen, and J.-H. Kim, “Variability analysis and evaluation for major cut flower traits of F1 hybrids in Lilium brownie var. colchesteri,” J. Multidiscip. Sci., vol. 4, no. 2, pp. 35–41, 2022.
V. Y. Nguyen, J.-H. Kim, J.-Y. Kim, and K. N. Jong, “Ecogeographical variations of the vegetative and floral traits in Lilium amabile Palibian,” J. Plant Biotechnol., vol. 48, no. 4, pp. 236–245, 2021.
R. Rai and J.-H. Kim, “Performance evaluation and variability analysis for major growth and flowering traits of Lilium longiflorum Thunb.,” J. Exp. Biol. Agric. Sci., vol. 9, no. 4, pp. 439–444, 2021.
R. Rai, V. Y. Nguyen, and J.-H. Kim, “Estimation of variability analysis parameters for major growth and flowering traits of Lilium leichtlinii var. maximowiczii germplasm,” J. Exp. Biol. Agric. Sci., vol. 9, no. 4, pp. 457–463, 2021.
R. Rai and J.-H. Kim, “Effect of storage temperature and cultivars on seed germination of Lilium × formolongi Hort.,” J. Exp. Biol. Agric. Sci., vol. 8, no. 5, pp. 621–627, 2020.
R. Rai and J.-H. Kim, “Estimation of combining ability and gene action for growth and flowering traits in Lilium longiflorum,” Int. J. Adv. Sci. Technol., vol. 29, no. 8S, pp. 1356–1363, 2020.
R. Rai, A. Badarch, and J.-H. Kim, “Identification of superior three-way cross F1s, its Line × Tester hybrids, and donors for major quantitative traits in Lilium × formolongi,” J. Exp. Biol. Agric. Sci., vol. 8, no. 2, pp. 157–165, 2020.
R. Rai, J. Shrestha, and J.-H. Kim, “Line × Tester analysis in Lilium × formolongi: Identification of superior parents for growth and flowering traits,” SAARC J. Agric., vol. 17, no. 1, pp. 175–187, 2019.
R. Rai, J. Shrestha, and J.-H. Kim, “Combining ability and gene action analysis for quantitative traits in Lilium × formolongi,” J. Agric. Life Environ. Sci., vol. 30, no. 3, pp. 131–143, 2019.
T. X. Nguyen, S. I. Lee, R. Rai, N. S. Kim, and J.-H. Kim, “Ribosomal DNA locus variation and REMAP analysis of the diploid and triploid complexes of Lilium lancifolium,” Genome, vol. 59, pp. 1–14, 2016.
T. X. Nguyen, J.-Y. Kim, R. Rai, J.-H. Kim, N. S. Kim, and A. Wakana, “Karyotype analysis of Korean Lilium maximowiczii Regal populations,” J. Fac. Agric. Kyushu Univ., vol. 60, no. 2, pp. 315–322, 2015.
S. Kasthuri and A. N. Jebaseeli, “An artificial bee colony and pigeon inspired optimization hybrid feature selection algorithm for Twitter sentiment analysis,” J. Comput. Theor. Nanosci., vol. 17, no. 12, pp. 5378–5385, 2020.
S. Kasthuri and A. N. Jebaseeli, “Review analysis of Twitter sentimental data,” Biosci. Biotechnol. Res. Commun., vol. 13, no. 6 (Special Issue), pp. 209–214, 2020.
S. Kasthuri and A. N. Jebaseeli, “An efficient decision tree algorithm for analyzing the Twitter sentiment analysis,” J. Crit. Rev., vol. 7, no. 4, pp. 1010–1018, 2020.
S. Kasthuri and A. N. Jebaseeli, “Latent Dirichlet Allocation feature extraction with bio inspired pigeon feature selection technique for Twitter sentiment analysis,” Int. J. Adv. Trends Comput. Sci. Eng., vol. 9, no. 4, pp. 6406–6414, Jul.–Aug. 2020.
S. Kasthuri, L. Jayasimman, and A. N. Jebaseeli, “An opinion mining and sentiment analysis techniques: A survey,” Int. Res. J. Eng. Technol. (IRJET), vol. 3, no. 2, pp. 573–575, 2016.
S. Kasthuri and A. N. Jebaseeli, “A robust data classification in online social networks through automatically mining query facts,” Int. J. Sci. Res. Comput. Sci. Appl. Manage. Stud., vol. 7, no. 4, Jul. 2018.
S. Kasthuri and A. N. Jebaseeli, “Social network analysis in data processing,” Adalya J., vol. 9, no. 2, pp. 260–263, Feb. 2020.
S. Kasthuri and A. N. Jebaseeli, “Review on social network analysis in data mining,” Infokara Res., vol. 8, no. 12, pp. 1168–1172, Dec. 2019.
S. Kasthuri and A. N. Jebaseeli, “Study on social network analysis in data mining,” Int. J. Anal. Exp. Modal Anal., vol. 11, no. 8, pp. 111–116, Aug. 2019.
G. Rajarajeswari and S. Kasthuri, “Co-clustering interpretations for feature selection by using sparsity learning,” Int. J. Res. Instinct, vol. 4, no. 1, pp. 30–35, 2017.
T. Ganesh Kannan, S. Kasthuri, and T. Dineshkumar, “A reliable communication and rate control for mobile network through efficient routing protocol,” Int. J. Comput. Sci. Eng., vol. 6, Special Issue 2, pp. 354–357, 2018.
K. V. Deshpande and J. Singh, “Weighted transformer neural network for web attack detection using request URL,” Multimedia Tools and Applications, vol. 83, no. 15, pp. 43983–44007, Oct. 2023.
J. Singh, S. Rani, and V. Kumar, “Role-based access control (RBAC) enabled secure and efficient data processing framework for IoT networks,” Int. J. Commun. Netw. Inf. Secur. (IJCNIS), Aug. 2024.
J. Singh, S. Rani, and P. Kumar, “Blockchain and smart contracts: Evolution, challenges, and future directions,” in Proc. 2024 Int. Conf. Knowledge Eng. Commun. Syst. (ICKECS), Apr. 2024, pp. 1–5.
J. Singh, E. al., “Enhancing cloud data privacy with a scalable hybrid approach: HE-DP-SMC,” J. Electr. Syst., vol. 19, no. 4, pp. 350–375, Jan. 2024.
J. Singh, S. Rani, and G. Srilakshmi, “Towards explainable AI: Interpretable models for complex decision-making,” in Proc. 2024 Int. Conf. Knowledge Eng. Commun. Syst. (ICKECS), Apr. 2024, pp. 1–5.
P. Das, D. Datta, S. S. Rajest, L. M. M. Visuwasam, A. Thakare, and J. Cypto, "Application of multi-criteria decision-making approach using TOPSIS to identify the vulnerable time zone of earthquake time series signal," Int. J. Crit. Comput.-Based Syst., vol. 11, no. 1/2, pp. 30–47, 2024.
G. Kumaresan and L. M. Visuwasam, "Enhanced in-line data deduplication and secure authorization in hybrid cloud," Int. J. Innov. Res. Sci. Eng. Technol., vol. 4, no. 2, pp. 466–471, 2015.
S. Gomathy, K. Deepa, T. Revathi, and L. M. M. Visuwasam, "Genre specific classification for information search and multimodal semantic indexing for data retrieval," SIJ Trans. Comput. Sci. Eng. Appl. (CSEA), vol. 1, no. 1, pp. 10–15, 2013.
K. Kishore, D. Dhinakaran, N. J. Kumar, S. M. U. Sankar, K. Chandu, and L. M. M. Visuwasam, "Fish farm monitoring system using IoT," in Proc. 2021 Int. Conf. Syst., Comput., Autom. Netw. (ICSCAN), 2021, vol. 10, pp. 1–6.
L. M. V., A. Balakrishna, N. S. R., and K. V., "Level-6 automated IoT integrated with artificial intelligence based big data-driven dynamic vehicular traffic control system," EAI Endorsed Trans. Energy Web, p. 164176, 2018.
N. J. K., M. Shoba, D. Dhinakaran, L. M. M. V., and G. Elangovan, "Bio-inspired optimization to enhance the performance in 6G networks of reconfigurable intelligent surfaces," in Advances in Computational Intelligence and Robotics, pp. 409–444, 2025.
N. J. Kumar, R. Premkumar, L. M. M. Visuwasam, G. Arjunan, G. Yuyaraj, and C. T. Kumar, "Hybrid K-means and firefly algorithm-based load balancer for dynamic task scheduling in fog computing for postoperative healthcare systems," in Proc. 2025 Int. Conf. Adv. Comput. Technol. (ICoACT), Sivalasi, India, 2025, pp. 1–6.
N. J. Kumar, R. Premkumar, L. M. Michael Visuwasam, G. Arjunan, A. Shiny, and K. Dharani, "Adaptive optimization and resource allocation (AORA) model for IoT-edge computing using hybrid Newton-Raphson and dolphin echolocation algorithm (HNR-DEA) technique," in Proc. 2025 Int. Conf. Adv. Comput. Technol. (ICoACT), Sivalasi, India, 2025, pp. 1–6.
R. Premkumar, N. J. Kumar, L. M. Michael Visuwasam, G. Arjunan, A. Vinothini, and C. T. Kumar, "Hybrid gradient descent and sea lion optimization algorithm (H-GD-SLnO) to optimize task scheduling in fog computing environment," in Proc. 2025 Int. Conf. Adv. Comput. Technol. (ICoACT), Sivalasi, India, 2025, pp. 1–6.
K. Singh, L. M. M. Visuwasam, G. Rajasekaran, R. Regin, S. S. Rajest, and S. T., "Innovations in skeleton-based movement recognition bridging AI and human kinetics," in Advances in Computational Intelligence and Robotics, pp. 125–141, 2024.
V. S. A. Anala, A. R. Pothu, and S. Chintapalli, “Enhancing Preventive Healthcare with Wearable Health Technology for Early Intervention,” FMDB Transactions on Sustainable Health Science Letters., vol.2, no.4, pp. 211–220, 2024.
V. S. A. Anala and S. Chintapalli, “Scalable Data Partitioning Strategies for Efficient Query Optimization in Cloud Data Warehouses,” FMDB Transactions on Sustainable Computer Letters., vol. 2, no. 4, pp. 195–206, 2024.
Md H. Rahman, T. Islam, Md E. Hossen, Md E. Chowdhury, R. Hayat, Md S. S. Shovon, M. Alamgir, S. Akter, R. Chowdhury, and A. R. Sunny, "Machine Learning in Healthcare: From Diagnostics to Personalized Medicine and Predictive Analytics," J. Angiother., vol. 8, no. 12, pp. 1–8, 2024.
R. Chowdhury, Md A. H. Fahad, S. M. S. Alam, M. I. Tusher, Md N. U. Rana, E. Ahmed, S. S. Akhi, and Md R. H. Mahin, "Database Management in the Era of Big Data: Trends, Challenges, and Breakthroughs," Pathfinder Res., vol. 1, no. 1, p. 15, 2020.
Md R. H. Mahin, E. Ahmed, S. S. Akhi, Md A. H. Fahad, M. I. Tusher, R. Chowdhury, and Md N. U. Rana, "Advancements and Challenges in Software Engineering and Project Management: A 2021 Perspective," Pathfinder Res., vol. 2, no. 1, p. 15, 2021.
Md A. H. Fahad and R. Chowdhury, "Evolution and Future Trends in Web Development: A Comprehensive Review," Pathfinder Res., vol. 3, no. 1, p. 13, 2022.
A. R. M. T. Islam, Md. N. Uddin, Md. F. R. Joy, R. Proshad, T. Kormoker, A. H. Anik, M. S. Rahman, Md. A. B. Siddique, and M. A. Alshehri, "Tracing sources-oriented ecological risks of metal(loid)s in sediments of anthropogenically-affected coastal ecosystem from northeast bay of Bengal," Mar. Pollut. Bull., vol. 211, p. 117354, 2025.
A. R. M. T. Islam, M. Abdullah-Al Mamun, M. Hasan, M. N. Aktar, M. N. Uddin, M. A. B. Siddique, M. H. Chowdhury, M. S. Islam, A. B. M. M. Bari, and A. M. Idris, "Optimizing coastal groundwater quality predictions: A novel data mining framework with cross-validation, bootstrapping, and entropy analysis," J. Contam. Hydrol., p. 104480, 2024.
Md. A.-A. Mamun, A. R. M. T. Islam, Mst. N. Aktar, M. N. Uddin, Md. S. Islam, S. C. Pal, A. Islam, A. B. M. M. Bari, A. M. Idris, and V. Senapathi, "Predicting groundwater phosphate levels in coastal multi-aquifers: A geostatistical and data-driven approach," Sci. Total Environ., vol. 953, p. 176024, 2024.
M. N. Uddin, G. C. Saha, M. A. Hasanath, M. A. H. Badsha, M. H. Chowdhury, and A. R. M. T. Islam, "Hexavalent chromium removal from aqueous medium by ternary nanoadsorbent: A study of kinetics, equilibrium, and thermodynamic mechanism," PLoS ONE, vol. 18, no. 12, e0290234, 2023.
G. C. Saha, M. A. Hasanath, M. N. Uddin, and M. Hasan, "Sustainable Utilization of Textile Dyeing Sludge and Coal Fly Ash by Brick Production Through Traditional Kilns," Nature Environ. Pollut. Technol., vol. 21, no. 3, 2022.
M. N. Uddin, G. C. Saha, M. A. Hasanath, M. T. Rahman, and M. M. Rashid, "Development and Characterization of Novel Mn–Fe–Sn Ternary Nanoparticle by Sol–Gel Technique," in Advances in Civil Engineering, S. Arthur, M. Saitoh, and S. K. Pal, Eds. Singapore: Springer, 2022, vol. 184, Lecture Notes in Civil Engineering.
M. T. Rahman, G. C. Saha, M. A. Hasanath, and M. N. Uddin, "Potential Use of Dying Sludge, Pet Granules and Fly Ash in Light Weight Concrete Block," in Advances in Civil Engineering, S. Arthur, M. Saitoh, and S. K. Pal, Eds. Singapore: Springer, 2022, vol. 184, Lecture Notes in Civil Engineering.
M. N. Uddin, G. C. Saha, M. A. Hasanath, M. T. Rahman, and M. M. Rashid, "Development and Characterization of Novel Mn–Fe–Sn Ternary Nanoparticle by Sol–Gel Technique," in Proc. 5th Int. Conf. Adv. Civil Eng. (ICACE 2020), Chattogram: CUET, 2021, pp. EE 29–34.
M. A. Hasanath, M. N. Uddin, and M. Ashraf, "Fabrication of Eco-friendly Water Purifier by Pedaling Energy," in Proc. 5th Int. Conf. Adv. Civil Eng. (ICACE 2020), Chattogram: CUET, 2021, pp. EE 29–34.
M. A. Hasanath, M. N. Uddin, and G. C. Saha, "Assessment of beverage sludge as agricultural soil," in Proc. 5th Int. Conf. Adv. Civil Eng. (ICACE 2020), Chattogram: CUET, 2021, pp. EE 254–260.
M. T. Rahman, G. C. Saha, M. A. Hasanath, and M. N. Uddin, "Potential Use of Dying Sludge, Pet Granules and Fly Ash in Light Weight Concrete Block," in Proc. 5th Int. Conf. Adv. Civil Eng. (ICACE 2020), Chattogram: CUET, 2021, pp. EE 254–260.
V. Yadav, “Machine Learning in Managing Healthcare Workforce Shortage: Analyzing how Machine Learning can Optimize Workforce Allocation in Response to Fluctuating Healthcare Demands,” Progress In Medical Sciences, pp. 1–9, Aug. 2023.
V. Yadav, “Machine Learning for Predicting Healthcare Policy Outcomes: Utilizing Machine Learning to Forecast the Outcomes of Proposed Healthcare Policies on Population Health and Economic Indicators,” Journal of Artificial Intelligence & Cloud Computing, vol. 1, no. 2, pp. 1–10, Jun. 2022.
R. Aravindhan, R. Shanmugalakshmi, K. Ramya and Selvan C., "Certain investigation on web application security: Phishing detection and phishing target discovery," 2016 3rd International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2016, pp. 1-10.
R. Aravindhan and R. Shanmugalakshmi, "Comparative analysis of Web 3.0 search engines: A survey report," 2013 International Conference on Advanced Computing and Communication Systems, Coimbatore, India, 2013, pp. 1-6.
Aravindhan, R., Shanmugalakshmi, R. & Ramya, K. Circumvention of Nascent and Potential Wi-Fi Phishing Threat Using Association Rule Mining. Wireless Pers Commun 94(3), 2331–2361, 2017.
R. Aravindhan and R. Shanmugalakshmi, "Visual analytics for semantic based image retrieval (SBIR): semantic tool," International Journal of Latest Trends in Engineering and Technology, vol. 7, no. 2, pp. 300–312, 2016.
R. Aravindhan and R. Shanmugalakshmi, "Multistage fuzzy classifier based phishing detection using LDA and CRF features followed by impersonated entity discovery," International Journal of Control Theory and Applications, vol. 10, no. 29, pp. 33–42, 2017.
Selvan, C., Ragunathan, A., & Ashwinkumar, U. M. (2024). Mitigating phishing threats in unmanned aircraft systems (UAS) through multi-stage defense strategies. In Analyzing and Mitigating Security Risks in Cloud Computing (pp. 125–162). IGI Global.
V. Basavegowda Ramu and A. R. Yeruva, "Optimising AIOps system performance for e-commerce and online retail businesses with the ACF model," International Journal of Intellectual Property Management, vol. 13, no. 3–4, pp. 412–429, 2023.
V. Basavegowda Ramu and A. R. Yeruva, "The Capability of Observing Performance in Healthcare Systems," in EAI/Springer Innovations in Communication and Computing, Springer, Cham, Switzerland, pp. 541–548, 2023.
V. Basavegowda Ramu and A. R. Yeruva, "Unsupervised strategies in detecting log anomalies using AIOps monitoring to amplify performance by PCA and ANN systems," International Journal of Critical Infrastructures, vol. 20, no. 4, pp. 356–371, 2024.
V. Samudrala, A. Reddy Yeruva, N. Jayapal, T. Vijayakumar, M. Rajkumar, and S. Razia, "Smart Water Flow Monitoring and Theft Detection System using IoT," in Proceedings of the International Conference on Automation, Computing and Renewable Systems (ICACRS), Pudukkottai, India, 2022.
S. A. Milu, S. Akter, A. Fathima, T. Talukder, I. Islam, and M. I. S. Emon, "Design and Implementation of hand gesture detection system using HM model for sign language recognition development," J. Data Anal. Inf. Process., vol. 12, no. 2, pp. 139–150, 2024.
S. S. Mahtab, R. A. Anonto, T. Talukder, A. Raihan, and I. Islam, "Etching Technologies in Semiconductor Manufacturing: A Short Review," in Proc. Int. Conf. Emerg. Appl. Mater. Sci. Technol., Cham: Springer Nature Switzerland, 2024, pp. 319–324.
T. Talukder, "Scanning Magnetometry With a Low Cost NV Diamond Quantum Sensor Probe," M.S. thesis, Morgan State Univ., 2024.
