AI-Powered Real-Time Anomaly Detection in Edge Computing Systems for Smart Cities
Smart city technologies have become essential in today’s world as people experience the improvement of city infrastructure that increases effectiveness, contacts and ecological unfriendliness. However, the implementation of different technologies and developing data-intensive systems in smart cities creates various questions especially the system availability and security in real-time systems. This means that like in other complex systems, there are always different types of anomalous events including equipment malfunctions, inadequate data, or cyber security threats that hinder standard and expected operations that make the detection of such anomalies important.
This paper explores how AI can help in real-time anomalies detection in edge computing systems, designed for smart cities. Edge computing in which data is processed nearer to the origin curtails general latency and provides improved response time, making it an excellent model for smart city implementation. The deep learning, clustering algorithms and federated learning enabled edge systems require accuracies greater than 90% in real-time to detect these anomalies for critical systems to run.
Some of the problems and issues as presented in the paper include limited resources of edge devices, data privacy issues and reliability issues in deploying AI on edge systems. It also discusses the topic of energy-efficient frameworks for AI, the capability of utilizing next-gen AI for better interpretability known as Explainable AI (XAI), and the fusion of edge-to-cloud systems for addressing the dilemma of centralized as well as decentralized data processing.
Lastly, the paper establishes how intelligent systems applied within smart city environments such as smart traffic management, energy grid monitoring, public safety, and environmental management provide theoretical and practical pathways to implementing AI-powered anomaly detection. The results put emphasis on the synergy between artificial intelligence and edge computing and show how it could help cities become more sustainable, smart, safe, and resourceful. This research endeavors to present the existing prospects and issues to help plan the further advancement and development of the literature in this field.
JOSHI, D., SAYED, F., BERI, J., & PAL, R. (2021). An efficient supervised machine learning model approach for forecasting of renewable energy to tackle climate change. Int J Comp Sci Eng Inform Technol Res, 11, 25-32.
Alam, K., Al Imran, M., Mahmud, U., & Al Fathah, A. (2024). Cyber Attacks Detection And Mitigation Using Machine Learning In Smart Grid Systems. Journal of Science and Engineering Research, November, 12.
Ghosh, A., Suraiah, N., Dey, N. L., Al Imran, M., Alam, K., Yahia, A. K. M., ... & Alrafai, H. A. (2024). Achieving Over 30% Efficiency Employing a Novel Double Absorber Solar Cell Configuration Integrating Ca3NCl3 and Ca3SbI3 Perovskites. Journal of Physics and Chemistry of Solids, 112498.
Al Imran, M., Al Fathah, A., Al Baki, A., Alam, K., Mostakim, M. A., Mahmud, U., & Hossen, M. S. (2023). Integrating IoT and AI For Predictive Maintenance in Smart Power Grid Systems to Minimize Energy Loss and Carbon Footprint. Journal of Applied Optics, 44(1), 27-47.
Mahmud, U., Alam, K., Mostakim, M. A., & Khan, M. S. I. (2018). AI-driven micro solar power grid systems for remote communities: Enhancing renewable energy efficiency and reducing carbon emissions. Distributed Learning and Broad Applications in Scientific Research, 4.
Joshi, D., Sayed, F., Saraf, A., Sutaria, A., & Karamchandani, S. (2021). Elements of Nature Optimized into Smart Energy Grids using Machine Learning. Design Engineering, 1886-1892.
Alam, K., Mostakim, M. A., & Khan, M. S. I. (2017). Design and Optimization of MicroSolar Grid for Off-Grid Rural Communities. Distributed Learning and Broad Applications in Scientific Research, 3.
Integrating solar cells into building materials (Building-Integrated Photovoltaics-BIPV) to turn buildings into self-sustaining energy sources. Journal of Artificial Intelligence Research and Applications, 2(2).
Manoharan, A., & Nagar, G. MAXIMIZING LEARNING TRAJECTORIES: AN INVESTIGATION INTO AI-DRIVEN NATURAL LANGUAGE PROCESSING INTEGRATION IN ONLINE EDUCATIONAL PLATFORMS.
Joshi, D., Parikh, A., Mangla, R., Sayed, F., & Karamchandani, S. H. (2021). AI Based Nose for Trace of Churn in Assessment of Captive Customers. Turkish Online Journal of Qualitative Inquiry, 12(6).
Ferdinand, J. (2024). Marine Medical Response: Exploring the Training, Role and Scope of Paramedics.
Nagar, G. (2018). Leveraging Artificial Intelligence to Automate and Enhance Security Operations: Balancing Efficiency and Human Oversight. Valley International Journal Digital Library, 78-94.
Kumar, S., & Nagar, G. (2024, June). Threat Modeling for Cyber Warfare Against Less Cyber-Dependent Adversaries. In European Conference on Cyber Warfare and Security (Vol. 23, No. 1, pp. 257-264).
Arefin, S., & Simcox, M. (2024). AI-Driven Solutions for Safeguarding Healthcare Data: Innovations in Cybersecurity. International Business Research, 17(6), 1-74.
Khambati, A. (2021). Innovative Smart Water Management System Using Artificial Intelligence. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(3), 4726-4734.
Nagar, G. (2024). The evolution of ransomware: tactics, techniques, and mitigation strategies. International Journal of Scientific Research and Management (IJSRM), 12(06), 1282-1298.
Ferdinand, J. (2023). The Key to Academic Equity: A Detailed Review of EdChat’s Strategies.
Manoharan, A. UNDERSTANDING THE THREAT LANDSCAPE: A COMPREHENSIVE ANALYSIS OF CYBER-SECURITY RISKS IN 2024.
Khambaty, A., Joshi, D., Sayed, F., Pinto, K., & Karamchandani, S. (2022, January). Delve into the Realms with 3D Forms: Visualization System Aid Design in an IOT-Driven World. In Proceedings of International Conference on Wireless Communication: ICWiCom 2021 (pp. 335-343). Singapore: Springer Nature Singapore.
Nagar, G., & Manoharan, A. (2022). THE RISE OF QUANTUM CRYPTOGRAPHY: SECURING DATA BEYOND CLASSICAL MEANS. 04. 6329-6336. 10.56726. IRJMETS24238.
Ferdinand, J. (2023). Marine Medical Response: Exploring the Training, Role and Scope of Paramedics and Paramedicine (ETRSp). Qeios.
Nagar, G., & Manoharan, A. (2022). ZERO TRUST ARCHITECTURE: REDEFINING SECURITY PARADIGMS IN THE DIGITAL AGE. International Research Journal of Modernization in Engineering Technology and Science, 4, 2686-2693.
JALA, S., ADHIA, N., KOTHARI, M., JOSHI, D., & PAL, R. SUPPLY CHAIN DEMAND FORECASTING USING APPLIED MACHINE LEARNING AND FEATURE ENGINEERING.
Ferdinand, J. (2023). Emergence of Dive Paramedics: Advancing Prehospital Care Beyond DMTs.
Nagar, G., & Manoharan, A. (2022). THE RISE OF QUANTUM CRYPTOGRAPHY: SECURING DATA BEYOND CLASSICAL MEANS. 04. 6329-6336. 10.56726. IRJMETS24238.
Nagar, G., & Manoharan, A. (2022). Blockchain technology: reinventing trust and security in the digital world. International Research Journal of Modernization in Engineering Technology and Science, 4(5), 6337-6344.
Joshi, D., Sayed, F., Jain, H., Beri, J., Bandi, Y., & Karamchandani, S. A Cloud Native Machine Learning based Approach for Detection and Impact of Cyclone and Hurricanes on Coastal Areas of Pacific and Atlantic Ocean.
Mishra, M. (2022). Review of Experimental and FE Parametric Analysis of CFRP-Strengthened Steel-Concrete Composite Beams. Journal of Mechanical, Civil and Industrial Engineering, 3(3), 92-101.
Agarwal, A. V., & Kumar, S. (2017, November). Unsupervised data responsive based monitoring of fields. In 2017 International Conference on Inventive Computing and Informatics (ICICI) (pp. 184-188). IEEE.
Agarwal, A. V., Verma, N., Saha, S., & Kumar, S. (2018). Dynamic Detection and Prevention of Denial of Service and Peer Attacks with IPAddress Processing. Recent Findings in Intelligent Computing Techniques: Proceedings of the 5th ICACNI 2017, Volume 1, 707, 139.
Mishra, M. (2017). Reliability-based Life Cycle Management of Corroding Pipelines via Optimization under Uncertainty (Doctoral dissertation).
Agarwal, A. V., Verma, N., & Kumar, S. (2018). Intelligent Decision Making Real-Time Automated System for Toll Payments. In Proceedings of International Conference on Recent Advancement on Computer and Communication: ICRAC 2017 (pp. 223-232). Springer Singapore.
Agarwal, A. V., & Kumar, S. (2017, October). Intelligent multi-level mechanism of secure data handling of vehicular information for post-accident protocols. In 2017 2nd International Conference on Communication and Electronics Systems (ICCES) (pp. 902-906). IEEE.
Ramadugu, R., & Doddipatla, L. (2022). Emerging Trends in Fintech: How Technology Is Reshaping the Global Financial Landscape. Journal of Computational Innovation, 2(1).
Ramadugu, R., & Doddipatla, L. (2022). The Role of AI and Machine Learning in Strengthening Digital Wallet Security Against Fraud. Journal of Big Data and Smart Systems, 3(1).
Doddipatla, L., Ramadugu, R., Yerram, R. R., & Sharma, T. (2021). Exploring The Role of Biometric Authentication in Modern Payment Solutions. International Journal of Digital Innovation, 2(1).
Dash, S. (2024). Leveraging Machine Learning Algorithms in Enterprise CRM Architectures for Personalized Marketing Automation. Journal of Artificial Intelligence Research, 4(1), 482-518.
Dash, S. (2023). Designing Modular Enterprise Software Architectures for AI-Driven Sales Pipeline Optimization. Journal of Artificial Intelligence Research, 3(2), 292-334.
Dash, S. (2023). Architecting Intelligent Sales and Marketing Platforms: The Role of Enterprise Data Integration and AI for Enhanced Customer Insights. Journal of Artificial Intelligence Research, 3(2), 253-291.
Barach, J. (2024, December). Enhancing Intrusion Detection with CNN Attention Using NSL-KDD Dataset. In 2024 Artificial Intelligence for Business (AIxB) (pp. 15-20). IEEE.
Sanwal, M. (2024). Evaluating Large Language Models Using Contrast Sets: An Experimental Approach. arXiv preprint arXiv:2404.01569.
Manish, S., & Ishan, D. (2024). A Multi-Faceted Approach to Measuring Engineering Productivity. International Journal of Trend in Scientific Research and Development, 8(5), 516-521.
Manish, S. (2024). An Autonomous Multi-Agent LLM Framework for Agile Software Development. International Journal of Trend in Scientific Research and Development, 8(5), 892-898.
Ness, S., Boujoudar, Y., Aljarbouh, A., Elyssaoui, L., Azeroual, M., Bassine, F. Z., & Rele, M. (2024). Active balancing system in battery management system for Lithium-ion battery. International Journal of Electrical and Computer Engineering (IJECE), 14(4), 3640-3648.
Han, J., Yu, M., Bai, Y., Yu, J., Jin, F., Li, C., ... & Li, L. (2020). Elevated CXorf67 expression in PFA ependymomas suppresses DNA repair and sensitizes to PARP inhibitors. Cancer Cell, 38(6), 844-856.
Mullankandy, S., Ness, S., & Kazmi, I. (2024). Exploring the Impact of Artificial Intelligence on Mental Health Interventions. Journal of Science & Technology, 5(3), 34-48.
Ness, S. (2024). Navigating Compliance Realities: Exploring Determinants of Compliance Officer Effectiveness in Cypriot Organizations. Asian American Research Letters Journal, 1(3).
Volkivskyi, M., Islam, T., Ness, S., & Mustafa, B. (2024). The Impact of Machine Learning on the Proliferation of State-Sponsored Propaganda and Implications for International Relations. ESP International Journal of Advancements in Computational Technology (ESP-IJACT), 2(2), 17-24.
Raghuweanshi, P. (2024). DEEP LEARNING MODEL FOR DETECTING TERROR FINANCING PATTERNS IN FINANCIAL TRANSACTIONS. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 3(3), 288-296.
Zeng, J., Han, J., Liu, Z., Yu, M., Li, H., & Yu, J. (2022). Pentagalloylglucose disrupts the PALB2-BRCA2 interaction and potentiates tumor sensitivity to PARP inhibitor and radiotherapy. Cancer Letters, 546, 215851.
Raghuwanshi, P. (2024). AI-Driven Identity and Financial Fraud Detection for National Security. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 7(01), 38-51.
Raghuwanshi, P. (2024). Integrating generative ai into iot-based cloud computing: Opportunities and challenges in the united states. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 5(1), 451-460.
Han, J., Yu, J., Yu, M., Liu, Y., Song, X., Li, H., & Li, L. (2024). Synergistic effect of poly (ADP-ribose) polymerase (PARP) inhibitor with chemotherapy on CXorf67-elevated posterior fossa group A ependymoma. Chinese Medical Journal, 10-1097.
Singu, S. K. (2021). Real-Time Data Integration: Tools, Techniques, and Best Practices. ESP Journal of Engineering & Technology Advancements, 1(1), 158-172.
Singu, S. K. (2021). Designing Scalable Data Engineering Pipelines Using Azure and Databricks. ESP Journal of Engineering & Technology Advancements, 1(2), 176-187.
Yu, J., Han, J., Yu, M., Rui, H., Sun, A., & Li, H. (2024). EZH2 inhibition sensitizes MYC-high medulloblastoma cancers to PARP inhibition by regulating NUPR1-mediated DNA repair. Oncogene, 1-15.
Singu, S. K. (2022). ETL Process Automation: Tools and Techniques. ESP Journal of Engineering & Technology Advancements, 2(1), 74-85.
Malhotra, I., Gopinath, S., Janga, K. C., Greenberg, S., Sharma, S. K., & Tarkovsky, R. (2014). Unpredictable nature of tolvaptan in treatment of hypervolemic hyponatremia: case review on role of vaptans. Case reports in endocrinology, 2014(1), 807054.
Shakibaie-M, B. (2013). Comparison of the effectiveness of two different bone substitute materials for socket preservation after tooth extraction: a controlled clinical study. International Journal of Periodontics & Restorative Dentistry, 33(2).
Shakibaie, B., Blatz, M. B., Conejo, J., & Abdulqader, H. (2023). From Minimally Invasive Tooth Extraction to Final Chairside Fabricated Restoration: A Microscopically and Digitally Driven Full Workflow for Single-Implant Treatment. Compendium of Continuing Education in Dentistry (15488578), 44(10).
Shakibaie, B., Sabri, H., & Blatz, M. (2023). Modified 3-Dimensional Alveolar Ridge Augmentation in the Anterior Maxilla: A Prospective Clinical Feasibility Study. Journal of Oral Implantology, 49(5), 465-472.
Shakibaie, B., Blatz, M. B., & Barootch, S. (2023). Comparación clínica de split rolling flap vestibular (VSRF) frente a double door flap mucoperióstico (DDMF) en la exposición del implante: un estudio clínico prospectivo. Quintessence: Publicación internacional de odontología, 11(4), 232-246.
Gopinath, S., Ishak, A., Dhawan, N., Poudel, S., Shrestha, P. S., Singh, P., ... & Michel, G. (2022). Characteristics of COVID-19 breakthrough infections among vaccinated individuals and associated risk factors: A systematic review. Tropical medicine and infectious disease, 7(5), 81.
Phongkhun, K., Pothikamjorn, T., Srisurapanont, K., Manothummetha, K., Sanguankeo, A., Thongkam, A., ... & Permpalung, N. (2023). Prevalence of ocular candidiasis and Candida endophthalmitis in patients with candidemia: a systematic review and meta-analysis. Clinical Infectious Diseases, 76(10), 1738-1749.
Bazemore, K., Permpalung, N., Mathew, J., Lemma, M., Haile, B., Avery, R., ... & Shah, P. (2022). Elevated cell-free DNA in respiratory viral infection and associated lung allograft dysfunction. American Journal of Transplantation, 22(11), 2560-2570.
Chuleerarux, N., Manothummetha, K., Moonla, C., Sanguankeo, A., Kates, O. S., Hirankarn, N., ... & Permpalung, N. (2022). Immunogenicity of SARS-CoV-2 vaccines in patients with multiple myeloma: a systematic review and meta-analysis. Blood Advances, 6(24), 6198-6207.
Roh, Y. S., Khanna, R., Patel, S. P., Gopinath, S., Williams, K. A., Khanna, R., ... & Kwatra, S. G. (2021). Circulating blood eosinophils as a biomarker for variable clinical presentation and therapeutic response in patients with chronic pruritus of unknown origin. The Journal of Allergy and Clinical Immunology: In Practice, 9(6), 2513-2516.
Mukherjee, D., Roy, S., Singh, V., Gopinath, S., Pokhrel, N. B., & Jaiswal, V. (2022). Monkeypox as an emerging global health threat during the COVID-19 time. Annals of Medicine and Surgery, 79.
Gopinath, S., Janga, K. C., Greenberg, S., & Sharma, S. K. (2013). Tolvaptan in the treatment of acute hyponatremia associated with acute kidney injury. Case reports in nephrology, 2013(1), 801575.
Shilpa, Lalitha, Prakash, A., & Rao, S. (2009). BFHI in a tertiary care hospital: Does being Baby friendly affect lactation success?. The Indian Journal of Pediatrics, 76, 655-657.
Singh, V. K., Mishra, A., Gupta, K. K., Misra, R., & Patel, M. L. (2015). Reduction of microalbuminuria in type-2 diabetes mellitus with angiotensin-converting enzyme inhibitor alone and with cilnidipine. Indian Journal of Nephrology, 25(6), 334-339.
Gopinath, S., Giambarberi, L., Patil, S., & Chamberlain, R. S. (2016). Characteristics and survival of patients with eccrine carcinoma: a cohort study. Journal of the American Academy of Dermatology, 75(1), 215-217.
Lin, L. I., & Hao, L. I. (2024). The efficacy of niraparib in pediatric recurrent PFA⁃ type ependymoma. Chinese Journal of Contemporary Neurology & Neurosurgery, 24(9), 739.
Gopinath, S., Sutaria, N., Bordeaux, Z. A., Parthasarathy, V., Deng, J., Taylor, M. T., ... & Kwatra, S. G. (2023). Reduced serum pyridoxine and 25-hydroxyvitamin D levels in adults with chronic pruritic dermatoses. Archives of Dermatological Research, 315(6), 1771-1776.
Han, J., Song, X., Liu, Y., & Li, L. (2022). Research progress on the function and mechanism of CXorf67 in PFA ependymoma. Chin Sci Bull, 67, 1-8.
Permpalung, N., Liang, T., Gopinath, S., Bazemore, K., Mathew, J., Ostrander, D., ... & Shah, P. D. (2023). Invasive fungal infections after respiratory viral infections in lung transplant recipients are associated with lung allograft failure and chronic lung allograft dysfunction within 1 year. The Journal of Heart and Lung Transplantation, 42(7), 953-963.
Swarnagowri, B. N., & Gopinath, S. (2013). Ambiguity in diagnosing esthesioneuroblastoma--a case report. Journal of Evolution of Medical and Dental Sciences, 2(43), 8251-8255.
Swarnagowri, B. N., & Gopinath, S. (2013). Pelvic Actinomycosis Mimicking Malignancy: A Case Report. tuberculosis, 14, 15.
H. Rathore and R. Ratnawat, "A Robust and Efficient Machine Learning Approach for Identifying Fraud in Credit Card Transaction," 2024 5th International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India, 2024, pp. 1486-1491, doi: 10.1109/ICOSEC61587.2024.10722387.
Permpalung, N., Bazemore, K., Mathew, J., Barker, L., Horn, J., Miller, S., ... & Shah, P. D. (2022). Secondary Bacterial and Fungal Pneumonia Complicating SARS-CoV-2 and Influenza Infections in Lung Transplant Recipients. The Journal of Heart and Lung Transplantation, 41(4), S397.
Shilpa Gopinath, S. (2024). Breast Cancer in Native American Women: A Population Based Outcomes Study involving 863,958 Patients from the Surveillance Epidemiology and End Result (SEER) Database (1973-2010). Journal of Surgery and Research, 7(4), 525-532.
Alawad, A., Abdeen, M. M., Fadul, K. Y., Elgassim, M. A., Ahmed, S., & Elgassim, M. (2024). A Case of Necrotizing Pneumonia Complicated by Hydropneumothorax. Cureus, 16(4).
Elgassim, M., Abdelrahman, A., Saied, A. S. S., Ahmed, A. T., Osman, M., Hussain, M., ... & Salem, W. (2022). Salbutamol-Induced QT Interval Prolongation in a Two-Year-Old Patient. Cureus, 14(2).
Cardozo, K., Nehmer, L., Esmat, Z. A. R. E., Afsari, M., Jain, J., Parpelli, V., ... & Shahid, T. (2024). U.S. Patent No. 11,893,819. Washington, DC: U.S. Patent and Trademark Office.
Cardozo, K., Nehmer, L., Esmat, Z. A. R. E., Afsari, M., Jain, J., & Parpelli, V. & Shahid, T.(2024). US Patent Application, (18/429,247).
Khambaty, A., Joshi, D., Sayed, F., Pinto, K., & Karamchandani, S. (2022, January). Delve into the Realms with 3D Forms: Visualization System Aid Design in an IOT-Driven World. In Proceedings of International Conference on Wireless Communication: ICWiCom 2021 (pp. 335-343). Singapore: Springer Nature Singapore.
Cardozo, K., Nehmer, L., Esmat, Z. A. R. E., Afsari, M., Jain, J., Parpelli, V., ... & Shahid, T. (2024). U.S. Patent No. 11,893,819. Washington, DC: U.S. Patent and Trademark Office.
Patil, S., Dudhankar, V., & Shukla, P. (2024). Enhancing Digital Security: How Identity Verification Mitigates E-Commerce Fraud. Journal of Current Science and Research Review, 2(02), 69-81.
Jarvis, D. A., Pribble, J., & Patil, S. (2023). U.S. Patent No. 11,816,225. Washington, DC: U.S. Patent and Trademark Office.
Pribble, J., Jarvis, D. A., & Patil, S. (2023). U.S. Patent No. 11,763,590. Washington, DC: U.S. Patent and Trademark Office.
Aljrah, I., Alomari, G., Aljarrah, M., Aljarah, A., & Aljarah, B. (2024). Enhancing Chip Design Performance with Machine Learning and PyRTL. International Journal of Intelligent Systems and Applications in Engineering, 12(2), 467-472.
Aljarah, B., Alomari, G., & Aljarah, A. (2024). Leveraging AI and Statistical Linguistics for Market Insights and E-Commerce Innovations. AlgoVista: Journal of AI & Computer Science, 3(2).
Aljarah, B., Alomari, G., & Aljarah, A. (2024). Synthesizing AI for Mental Wellness and Computational Precision: A Dual Frontier in Depression Detection and Algorithmic Optimization. AlgoVista: Journal of AI & Computer Science, 3(2).
Maddireddy, B. R., & Maddireddy, B. R. (2020). Proactive Cyber Defense: Utilizing AI for Early Threat Detection and Risk Assessment. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 64-83.
Maddireddy, B. R., & Maddireddy, B. R. (2020). AI and Big Data: Synergizing to Create Robust Cybersecurity Ecosystems for Future Networks. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 40-63.
Maddireddy, B. R., & Maddireddy, B. R. (2021). Evolutionary Algorithms in AI-Driven Cybersecurity Solutions for Adaptive Threat Mitigation. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 17-43.
Maddireddy, B. R., & Maddireddy, B. R. (2022). Cybersecurity Threat Landscape: Predictive Modelling Using Advanced AI Algorithms. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 270-285.
Maddireddy, B. R., & Maddireddy, B. R. (2021). Cyber security Threat Landscape: Predictive Modelling Using Advanced AI Algorithms. Revista Espanola de Documentacion Cientifica, 15(4), 126-153.
Maddireddy, B. R., & Maddireddy, B. R. (2021). Enhancing Endpoint Security through Machine Learning and Artificial Intelligence Applications. Revista Espanola de Documentacion Cientifica, 15(4), 154-164.
Maddireddy, B. R., & Maddireddy, B. R. (2022). Real-Time Data Analytics with AI: Improving Security Event Monitoring and Management. Unique Endeavor in Business & Social Sciences, 1(2), 47-62.
Maddireddy, B. R., & Maddireddy, B. R. (2022). Blockchain and AI Integration: A Novel Approach to Strengthening Cybersecurity Frameworks. Unique Endeavor in Business & Social Sciences, 5(2), 46-65.
Maddireddy, B. R., & Maddireddy, B. R. (2022). AI-Based Phishing Detection Techniques: A Comparative Analysis of Model Performance. Unique Endeavor in Business & Social Sciences, 1(2), 63-77.
Maddireddy, B. R., & Maddireddy, B. R. (2023). Enhancing Network Security through AI-Powered Automated Incident Response Systems. International Journal of Advanced Engineering Technologies and Innovations, 1(02), 282-304.
Maddireddy, B. R., & Maddireddy, B. R. (2023). Automating Malware Detection: A Study on the Efficacy of AI-Driven Solutions. Journal Environmental Sciences And Technology, 2(2), 111-124.
Maddireddy, B. R., & Maddireddy, B. R. (2023). Adaptive Cyber Defense: Using Machine Learning to Counter Advanced Persistent Threats. International Journal of Advanced Engineering Technologies and Innovations, 1(03), 305-324.
Maddireddy, B. R., & Maddireddy, B. R. (2024). A Comprehensive Analysis of Machine Learning Algorithms in Intrusion Detection Systems. Journal Environmental Sciences And Technology, 3(1), 877-891.
Maddireddy, B. R., & Maddireddy, B. R. (2024). Neural Network Architectures in Cybersecurity: Optimizing Anomaly Detection and Prevention. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 238-266.
Maddireddy, B. R., & Maddireddy, B. R. (2024). The Role of Reinforcement Learning in Dynamic Cyber Defense Strategies. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 267-292.
Maddireddy, B. R., & Maddireddy, B. R. (2024). Advancing Threat Detection: Utilizing Deep Learning Models for Enhanced Cybersecurity Protocols. Revista Espanola de Documentacion Cientifica, 18(02), 325-355.
Damaraju, A. (2021). Mobile Cybersecurity Threats and Countermeasures: A Modern Approach. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 17-34.
Damaraju, A. (2021). Securing Critical Infrastructure: Advanced Strategies for Resilience and Threat Mitigation in the Digital Age. Revista de Inteligencia Artificial en Medicina, 12(1), 76-111.
Damaraju, A. (2022). Social Media Cybersecurity: Protecting Personal and Business Information. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 50-69.
Damaraju, A. (2023). Safeguarding Information and Data Privacy in the Digital Age. International Journal of Advanced Engineering Technologies and Innovations, 1(01), 213-241.
Damaraju, A. (2024). The Future of Cybersecurity: 5G and 6G Networks and Their Implications. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 359-386.
Damaraju, A. (2022). Securing the Internet of Things: Strategies for a Connected World. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 29-49.
Damaraju, A. (2020). Social Media as a Cyber Threat Vector: Trends and Preventive Measures. Revista Espanola de Documentacion Cientifica, 14(1), 95-112.
Damaraju, A. (2023). Enhancing Mobile Cybersecurity: Protecting Smartphones and Tablets. International Journal of Advanced Engineering Technologies and Innovations, 1(01), 193-212.
Damaraju, A. (2024). Implementing Zero Trust Architecture in Modern Cyber Defense Strategies. Unique Endeavor in Business & Social Sciences, 3(1), 173-188.
Chirra, D. R. (2022). Collaborative AI and Blockchain Models for Enhancing Data Privacy in IoMT Networks. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 13(1), 482-504.
Chirra, D. R. (2024). Quantum-Safe Cryptography: New Frontiers in Securing Post-Quantum Communication Networks. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 670-688.
Chirra, D. R. (2024). Advanced Threat Detection and Response Systems Using Federated Machine Learning in Critical Infrastructure. International Journal of Advanced Engineering Technologies and Innovations, 2(1), 61-81.
Chirra, D. R. (2024). AI-Augmented Zero Trust Architectures: Enhancing Cybersecurity in Dynamic Enterprise Environments. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 643-669.
Chirra, D. R. (2023). The Role of Homomorphic Encryption in Protecting Cloud-Based Financial Transactions. International Journal of Advanced Engineering Technologies and Innovations, 1(01), 452-472.
Chirra, D. R. (2024). AI-Augmented Zero Trust Architectures: Enhancing Cybersecurity in Dynamic Enterprise Environments. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 643-669.
Chirra, D. R. (2023). The Role of Homomorphic Encryption in Protecting Cloud-Based Financial Transactions. International Journal of Advanced Engineering Technologies and Innovations, 1(01), 452-472.
Chirra, D. R. (2023). Real-Time Forensic Analysis Using Machine Learning for Cybercrime Investigations in E-Government Systems. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 14(1), 618-649.
Chirra, D. R. (2023). AI-Based Threat Intelligence for Proactive Mitigation of Cyberattacks in Smart Grids. Revista de Inteligencia Artificial en Medicina, 14(1), 553-575.
Chirra, D. R. (2023). Deep Learning Techniques for Anomaly Detection in IoT Devices: Enhancing Security and Privacy. Revista de Inteligencia Artificial en Medicina, 14(1), 529-552.
Chirra, D. R. (2024). Blockchain-Integrated IAM Systems: Mitigating Identity Fraud in Decentralized Networks. International Journal of Advanced Engineering Technologies and Innovations, 2(1), 41-60.
Chirra, B. R. (2024). Enhancing Cloud Security through Quantum Cryptography for Robust Data Transmission. Revista de Inteligencia Artificial en Medicina, 15(1), 752-775.
Chirra, B. R. (2024). Predictive AI for Cyber Risk Assessment: Enhancing Proactive Security Measures. International Journal of Advanced Engineering Technologies and Innovations, 1(4), 505-527.
Chirra, B. R. (2021). AI-Driven Security Audits: Enhancing Continuous Compliance through Machine Learning. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 12(1), 410-433.
Chirra, B. R. (2021). Enhancing Cyber Incident Investigations with AI-Driven Forensic Tools. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 157-177.
Chirra, B. R. (2021). Intelligent Phishing Mitigation: Leveraging AI for Enhanced Email Security in Corporate Environments. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 178-200.
Chirra, B. R. (2021). Leveraging Blockchain for Secure Digital Identity Management: Mitigating Cybersecurity Vulnerabilities. Revista de Inteligencia Artificial en Medicina, 12(1), 462-482.
Chirra, B. R. (2020). Enhancing Cybersecurity Resilience: Federated Learning-Driven Threat Intelligence for Adaptive Defense. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 11(1), 260-280.
Chirra, B. R. (2020). Securing Operational Technology: AI-Driven Strategies for Overcoming Cybersecurity Challenges. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 11(1), 281-302.
Chirra, B. R. (2020). Advanced Encryption Techniques for Enhancing Security in Smart Grid Communication Systems. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 208-229.
Chirra, B. R. (2020). AI-Driven Fraud Detection: Safeguarding Financial Data in Real-Time. Revista de Inteligencia Artificial en Medicina, 11(1), 328-347.
Chirra, B. R. (2023). AI-Powered Identity and Access Management Solutions for Multi-Cloud Environments. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 14(1), 523-549.
Chirra, B. R. (2023). Advancing Cyber Defense: Machine Learning Techniques for NextGeneration Intrusion Detection. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 14(1), 550-573.'
Yanamala, A. K. Y. (2024). Revolutionizing Data Management: Next-Generation Enterprise Storage Technologies for Scalability and Resilience. Revista de Inteligencia Artificial en Medicina, 15(1), 1115-1150.
Mubeen, M. (2024). Zero-Trust Architecture for Cloud-Based AI Chat Applications: Encryption, Access Control and Continuous AI-Driven Verification.
Yanamala, A. K. Y., & Suryadevara, S. (2024). Emerging Frontiers: Data Protection Challenges and Innovations in Artificial Intelligence. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 74-102.
Yanamala, A. K. Y. (2024). Optimizing data storage in cloud computing: techniques and best practices. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 476-513.
Yanamala, A. K. Y., & Suryadevara, S. (2024). Navigating data protection challenges in the era of artificial intelligence: A comprehensive review. Revista de Inteligencia Artificial en Medicina, 15(1), 113-146.
Yanamala, A. K. Y. (2024). Emerging challenges in cloud computing security: A comprehensive review. International Journal of Advanced Engineering Technologies and Innovations, 1(4), 448-479.
Yanamala, A. K. Y., Suryadevara, S., & Kalli, V. D. R. (2024). Balancing innovation and privacy: The intersection of data protection and artificial intelligence. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 1-43.
Yanamala, A. K. Y. (2023). Secure and private AI: Implementing advanced data protection techniques in machine learning models. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 14(1), 105-132.
Yanamala, A. K. Y., Suryadevara, S., & Kalli, V. D. R. (2024). Balancing innovation and privacy: The intersection of data protection and artificial intelligence. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 1-43.
Yanamala, A. K. Y., & Suryadevara, S. (2023). Advances in Data Protection and Artificial Intelligence: Trends and Challenges. International Journal of Advanced Engineering Technologies and Innovations, 1(01), 294-319.
Yanamala, A. K. Y., & Suryadevara, S. (2022). Adaptive Middleware Framework for Context-Aware Pervasive Computing Environments. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 13(1), 35-57.
Yanamala, A. K. Y., & Suryadevara, S. (2022). Cost-Sensitive Deep Learning for Predicting Hospital Readmission: Enhancing Patient Care and Resource Allocation. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 56-81.
Gadde, H. (2024). AI-Powered Fault Detection and Recovery in High-Availability Databases. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 500-529. Gadde, H. (2024). AI-Powered Fault Detection and Recovery in High-Availability Databases. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 500-529.
Gadde, H. (2019). Integrating AI with Graph Databases for Complex Relationship Analysis. International
Gadde, H. (2023). Leveraging AI for Scalable Query Processing in Big Data Environments. International Journal of Advanced Engineering Technologies and Innovations, 1(02), 435-465.
Gadde, H. (2019). AI-Driven Schema Evolution and Management in Heterogeneous Databases. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 10(1), 332-356.
Gadde, H. (2023). Self-Healing Databases: AI Techniques for Automated System Recovery. International Journal of Advanced Engineering Technologies and Innovations, 1(02), 517-549.
Gadde, H. (2024). Optimizing Transactional Integrity with AI in Distributed Database Systems. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 621-649.
Gadde, H. (2024). Intelligent Query Optimization: AI Approaches in Distributed Databases. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 650-691.
Gadde, H. (2024). AI-Powered Fault Detection and Recovery in High-Availability Databases. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 500-529.
Gadde, H. (2021). AI-Driven Predictive Maintenance in Relational Database Systems. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 12(1), 386-409.
Gadde, H. (2019). Exploring AI-Based Methods for Efficient Database Index Compression. Revista de Inteligencia Artificial en Medicina, 10(1), 397-432.
Gadde, H. (2024). AI-Driven Data Indexing Techniques for Accelerated Retrieval in Cloud Databases. Revista de Inteligencia Artificial en Medicina, 15(1), 583-615.
Gadde, H. (2024). AI-Augmented Database Management Systems for Real-Time Data Analytics. Revista de Inteligencia Artificial en Medicina, 15(1), 616-649.
Gadde, H. (2023). AI-Driven Anomaly Detection in NoSQL Databases for Enhanced Security. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 14(1), 497-522.
Gadde, H. (2023). AI-Based Data Consistency Models for Distributed Ledger Technologies. Revista de Inteligencia Artificial en Medicina, 14(1), 514-545.
Gadde, H. (2022). AI-Enhanced Adaptive Resource Allocation in Cloud-Native Databases. Revista de Inteligencia Artificial en Medicina, 13(1), 443-470.
Gadde, H. (2022). Federated Learning with AI-Enabled Databases for Privacy-Preserving Analytics. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 220-248.
Goriparthi, R. G. (2020). AI-Driven Automation of Software Testing and Debugging in Agile Development. Revista de Inteligencia Artificial en Medicina, 11(1), 402-421.
Goriparthi, R. G. (2023). Federated Learning Models for Privacy-Preserving AI in Distributed Healthcare Systems. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 14(1), 650-673.
Goriparthi, R. G. (2021). Optimizing Supply Chain Logistics Using AI and Machine Learning Algorithms. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 279-298.
Goriparthi, R. G. (2021). AI and Machine Learning Approaches to Autonomous Vehicle Route Optimization. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 12(1), 455-479.
Goriparthi, R. G. (2024). Adaptive Neural Networks for Dynamic Data Stream Analysis in Real-Time Systems. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 689-709.
Goriparthi, R. G. (2020). Neural Network-Based Predictive Models for Climate Change Impact Assessment. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 11(1), 421-421.
Goriparthi, R. G. (2024). Reinforcement Learning in IoT: Enhancing Smart Device Autonomy through AI. computing, 2(01).
Goriparthi, R. G. (2024). Deep Learning Architectures for Real-Time Image Recognition: Innovations and Applications. Revista de Inteligencia Artificial en Medicina, 15(1), 880-907.
Goriparthi, R. G. (2024). Hybrid AI Frameworks for Edge Computing: Balancing Efficiency and Scalability. International Journal of Advanced Engineering Technologies and Innovations, 2(1), 110-130.
Goriparthi, R. G. (2024). AI-Driven Predictive Analytics for Autonomous Systems: A Machine Learning Approach. Revista de Inteligencia Artificial en Medicina, 15(1), 843-879.
Goriparthi, R. G. (2023). Leveraging AI for Energy Efficiency in Cloud and Edge Computing Infrastructures. International Journal of Advanced Engineering Technologies and Innovations, 1(01), 494-517.
Goriparthi, R. G. (2023). AI-Augmented Cybersecurity: Machine Learning for Real-Time Threat Detection. Revista de Inteligencia Artificial en Medicina, 14(1), 576-594.
Goriparthi, R. G. (2022). AI-Powered Decision Support Systems for Precision Agriculture: A Machine Learning Perspective. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 345-365.
Reddy, V. M., & Nalla, L. N. (2020). The Impact of Big Data on Supply Chain Optimization in Ecommerce. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 1-20.
Nalla, L. N., & Reddy, V. M. (2020). Comparative Analysis of Modern Database Technologies in Ecommerce Applications. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 21-39.
Nalla, L. N., & Reddy, V. M. (2021). Scalable Data Storage Solutions for High-Volume E-commerce Transactions. International Journal of Advanced Engineering Technologies and Innovations, 1(4), 1-16.
Reddy, V. M. (2021). Blockchain Technology in E-commerce: A New Paradigm for Data Integrity and Security. Revista Espanola de Documentacion Cientifica, 15(4), 88-107.
Reddy, V. M., & Nalla, L. N. (2021). Harnessing Big Data for Personalization in E-commerce Marketing Strategies. Revista Espanola de Documentacion Cientifica, 15(4), 108-125.
Reddy, V. M., & Nalla, L. N. (2022). Enhancing Search Functionality in E-commerce with Elasticsearch and Big Data. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 37-53.
Nalla, L. N., & Reddy, V. M. (2022). SQL vs. NoSQL: Choosing the Right Database for Your Ecommerce Platform. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 54-69.
Reddy, V. M. (2023). Data Privacy and Security in E-commerce: Modern Database Solutions. International Journal of Advanced Engineering Technologies and Innovations, 1(03), 248-263.
Reddy, V. M., & Nalla, L. N. (2023). The Future of E-commerce: How Big Data and AI are Shaping the Industry. International Journal of Advanced Engineering Technologies and Innovations, 1(03), 264-281.
Reddy, V. M., & Nalla, L. N. (2024). Real-time Data Processing in E-commerce: Challenges and Solutions. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 297-325.
Reddy, V. M., & Nalla, L. N. (2024). Leveraging Big Data Analytics to Enhance Customer Experience in E-commerce. Revista Espanola de Documentacion Cientifica, 18(02), 295-324.
Reddy, V. M. (2024). The Role of NoSQL Databases in Scaling E-commerce Platforms. International Journal of Advanced Engineering Technologies and Innovations, 1(3), 262-296.
Nalla, L. N., & Reddy, V. M. (2024). AI-driven big data analytics for enhanced customer journeys: A new paradigm in e-commerce. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 719-740.
Reddy, V. M., & Nalla, L. N. (2024). Optimizing E-Commerce Supply Chains Through Predictive Big Data Analytics: A Path to Agility and Efficiency. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 555-585.
Reddy, V. M., & Nalla, L. N. (2024). Personalization in E-Commerce Marketing: Leveraging Big Data for Tailored Consumer Engagement. Revista de Inteligencia Artificial en Medicina, 15(1), 691-725.
Nalla, L. N., & Reddy, V. M. Machine Learning and Predictive Analytics in E-commerce: A Data-driven Approach.
Reddy, V. M., & Nalla, L. N. Implementing Graph Databases to Improve Recommendation Systems in E-commerce.
Chatterjee, P. (2023). Optimizing Payment Gateways with AI: Reducing Latency and Enhancing Security. Baltic Journal of Engineering and Technology, 2(1), 1-10.
Chatterjee, P. (2022). Machine Learning Algorithms in Fraud Detection and Prevention. Eastern-European Journal of Engineering and Technology, 1(1), 15-27.
Chatterjee, P. (2022). AI-Powered Real-Time Analytics for Cross-Border Payment Systems. Eastern-European Journal of Engineering and Technology, 1(1), 1-14.
Mishra, M. (2022). Review of Experimental and FE Parametric Analysis of CFRP-Strengthened Steel-Concrete Composite Beams. Journal of Mechanical, Civil and Industrial Engineering, 3(3), 92-101.
Krishnan, S., Shah, K., Dhillon, G., & Presberg, K. (2016). 1995: FATAL PURPURA FULMINANS AND FULMINANT PSEUDOMONAL SEPSIS. Critical Care Medicine, 44(12), 574.
Krishnan, S. K., Khaira, H., & Ganipisetti, V. M. (2014, April). Cannabinoid hyperemesis syndrome-truly an oxymoron!. In JOURNAL OF GENERAL INTERNAL MEDICINE (Vol. 29, pp. S328-S328). 233 SPRING ST, NEW YORK, NY 10013 USA: SPRINGER.
Krishnan, S., & Selvarajan, D. (2014). D104 CASE REPORTS: INTERSTITIAL LUNG DISEASE AND PLEURAL DISEASE: Stones Everywhere!. American Journal of Respiratory and Critical Care Medicine, 189, 1.
Copyright (c) 2024 International Journal of Engineering and Computer Science
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.