Understanding the Capabilities and Implications of Agentic AI in Surveillance Systems

Nisher Ahmed; Md Emran  Hossain; Zakir  Hossain; Md Farhad  Kabir; Iffat Sania  Hossain

doi:10.55927/ijar.v4i1.13682

Authors

Nisher Ahmed College of Technology and Engineering, Westcliff University
Md Emran Hossain College of Technology and Engineering, Westcliff University
Zakir Hossain College of Engineering and Computer Science, California State University
Md Farhad Kabir Marshall School of Business, University of Southern California
Iffat Sania Hossain Martin V. Smith School of Business and Economics, California State University

DOI:

https://doi.org/10.55927/ijar.v4i1.13682

Keywords:

Agentic AI, Surveillance Systems, Automation Decision-Making, Ethical Implications, Privacy and Accountability

Abstract

Agentic AI can also mean the speeding up of new levels of surveillance systems the size of which has never been encountered before which grants automation decision making and realtime responses. Examples of stateful models of an agent are agentic AI, where an agentic AI isn't just a static function, but has capabilities to reason and learn with reference to the environment and goals. The paper explores the possible implications of embedding Agentic AI in surveillance systems, demonstrating how it could revolutionize monitoring, identification of threats, and response systems. Agentic AI: how this would take surveillance to a whole new levelThis is better than never breaking your objectivity at all, but leaves you to micromanage thousands of processes each requiring situational analysis and prediction in real time to create data packets, imploding the challenges of complex environments into just a number/sensible statistic. Yet, the application of Agentic AI for surveillance raises several ethical, legal, and social issues, such as about privacy, accountability, and the risk of misuse. It also outlines challenges to transparency, neutrality and oversight of Agentic AI systems (in their design and deployment), and emphasises the need for powerful regulatory frameworks able to confront risk. Moving forward the ability of Agentic AI to enhance surveillance technologies is significant, but the implementation of such a technology must be implemented correctly while remaining at or below the existing moral paradigms of our society and protecting the fundamental human rights of the individual.

Downloads

Download data is not yet available.

References

Arthan, N., Kacheru, G., & Bajjuru, R. (2019). Radio Frequency in Autonomous Vehicles: Communication Standards and Safety Protocols. Revista de Inteligencia Artificial en Medicina, 10(1), 449478.

Datta, R., Halimuzzaman, M., & Honey, S. (2024). A Comparative Analysis of Safety Performance in Commercial and Residential Construction: Unraveling Critical Insights. Journal of Control & Instrumentation, 15(01), 110.

Datta, R., Pankaj Sarker, K., Shikdar, L., Halimuzzaman, M., & Rezaul Karim, M. (2024). Mobile Applications for Enhancing Safety Audits in Healthcare Construction Sites. Journal of Angiotherapy, 8(9), 16.

Habib, H. (2015). Awareness about special education in Hyderabad. International Journal of Science and Research (IJSR), 4(5), 12961300.

Habib, H., & Janae, J. (2024). Breaking Barriers: How AI is Transforming Special Education Classrooms. Bulletin of Engineering Science and Technology, 1(02), 86108.

Habib, H., Jelani, S. A. K., & Najla, S. (2022). Revolutionizing Inclusion: AI in Adaptive Learning for Students with Disabilities. Multidisciplinary Science Journal, 1(01), 111.

Habib, H., Jelani, S. A. K., & Rasheed, N. T. (2021). Tailored Education: AI in the Development of Individualized Education Programs (IEPs). Multidisciplinary Science Journal, 1(01), 818.

Habib, H., Jelani, S. A. K., Ali, S. S., & Kadari, J. (2023). From Assessment to Empowerment: The Role of AI in Special Education Progress Monitoring. Journal of Multidisciplinary Research, 9(01), 6798.

Habib, H., Jelani, S. A. K., Alizzi, M., & Numair, H. (2020). Personalized Learning Paths: AI Applications in Special Education. Journal of Multidisciplinary Research, 6(01).

Habib, H., Jelani, S. A. K., Numair, H., & Mubeen, S. (2019). Enhancing Communication Skills: AI Technologies for Students with Speech and Language Needs. Journal of Multidisciplinary Research, 5(01).

Halimuzzaman, M., & Sharma, J. (2022). Applications of accounting information system (AIS) under Enterprise resource planning (ERP): A comprehensive review. International Journal of Early Childhood Special Education (INTJECSE), 14(2), 68016806.

Halimuzzaman, M., & Sharma, J. (2024). The Role of Enterprise Resource Planning (ERP) in Improving the Accounting Information System for Organizations. In Revolutionizing the AIDigital Landscape (pp. 263274). Productivity Press.

Halimuzzaman, M., Khaiar, M. A., & Hoque, M. M. (2014). An analysis of progress of rural development scheme (RDS) by IBBL: A study on Kushtia Branch. Bangla Vision, 13(1), 169180.

Halimuzzaman, M., Sharma, D. J., Bhattacharjee, T., Mallik, B., Rahman, R., Rezaul Karim, M., ... & Fokhrul Islam, M. (2024). Blockchain technology for integrating electronic records of digital healthcare system. Journal of Angiotherapy, 8(7).

Halimuzzaman, M., Sharma, J., & Khang, A. (2024). Enterprise Resource Planning and Accounting Information Systems: Modeling the Relationship in Manufacturing. In Machine Vision and Industrial Robotics in Manufacturing (pp. 418434). CRC Press.

Halimuzzaman, M., Sharma, J., Hossain, M. I., Akand, F., Islam, M. N., Ikram, M. M., & Khan, N. N. Healthcare Service Quality Digitization with Enterprise Resource Planning.

Halimuzzaman, M., Sharma, J., Islam, D., Habib, F., & Ahmed, S. S. FINANCIAL IMPACT OF ENTERPRISE RESOURCE PLANNING (ERP) ON ACCOUNTING INFORMATION SYSTEMS (AIS): A STUDY ON PETROLEUM COMPANIES IN BANGLADESH.

Halimuzzaman, M., Sharma, J., Karim, M. R., Hossain, M. R., Azad, M. A. K., & Alam, M. M. (2024). Enhancement of Organizational Accounting Information Systems and Financial Control through Enterprise Resource Planning. In Synergy of AI and Fintech in the Digital Gig Economy (pp. 315331). CRC Press.

Hasan, A. S., Debu, S. S. S. D., Eti, I. J., Halimuzzaman, M., & Rezaul, M. Machine Learning Models for Predicting Risky Pregnancies in Early Clinical Interventions.

Islam, M. F., Debnath, S., Das, H., Hasan, F., Sultana, S., Datta, R., ... & Halimuzzaman, M. (2024). Impact of Rapid Economic Development with Rising Carbon Emissions on Public Health and Healthcare Costs in Bangladesh. Journal of Angiotherapy, 8(7), 19.

Islam, M. F., Eity, S. B., Barua, P., & Halimuzzaman, M. (2023). Liabilities of Street Food Vendors for spreading out Chronic Diseases and Environment Pollution: A Study on Chattogram, Bangladesh. JETIR, 10 (11), Article 11.

Kacheru, G., Bajjuru, R., & Arthan, N. (2019). Security Considerations When Automating Software Development. Revista de Inteligencia Artificial en Medicina, 10(1), 598617.

Kacheru, G., Bajjuru, R., & Arthan, N. (2022). Surge of Cyber Scams during the COVID19 Pandemic: Analyzing the Shift in Tactics. BULLET: Jurnal Multidisiplin Ilmu, 1(02), 192202.

Rana, M. M., Kalam, A., & Halimuzzaman, M. (2012). CO RPO RATE SO C IAL RESPO NSIBILITY (C SR) OF DUTC HBANG LA BANK LIMITED: A CASE STUDY.

Sohel, M. S., Shi, G., Zaman, N. T., Hossain, B., Halimuzzaman, M., Akintunde, T. Y., & Liu, H. (2022). Understanding the food insecurity and coping strategies of indigenous households during COVID19 crisis in Chittagong hill tracts, Bangladesh: A qualitative study. Foods, 11(19), 3103.

Tamraparani, V. (2019). A Practical Approach to Model Risk Management and Governance in Insurance: A Practitioner’s Perspective. Journal of Computational Analysis and Applications, 27(7).

Tamraparani, V. (2019). DataDriven Strategies for Reducing Employee Health Insurance Costs: A Collaborative Approach with Carriers and Brokers. International Journal of Advanced Engineering Technologies and Innovations, 1(1), 110127.

Tamraparani, V. (2020). Automating Invoice Processing in Fund Management: Insights from RPA and Data Integration Techniques. Journal of Computational Analysis and Applications, 28(6).

Tamraparani, V. (2021). Cloud and Data Transformation in Banking: Managing Middle and Back Office Operations Using Snowflake and Databricks. Journal of Computational Analysis and Applications, 29(4).

Tamraparani, V. (2022). Enhancing Cybersecurity and Firm Resilience Through Data Lineage: Best Practices and ML Ops for AutoDetection. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 415427.

Tamraparani, V. (2023). Leveraging AI for Fraud Detection in Identity and Access Management: A Focus on LargeScale Customer Data. Journal of Computational Analysis and Applications, 31(4).

Tamraparani, V. (2024). Applying Robotic Process Automation & AI techniques to reduce time to market for medical devices compliance & provisioning. Revista de Inteligencia Artificial en Medicina, 15(1).

Tamraparani, V. (2024). Revolutionizing payments infrastructure with AI & ML to enable secure cross border payments. Journal of Multidisciplinary Research, 10(02), 4970.

Tamraparani, V., & Dalal, A. (2022). Developing a robust CRM Analytics strategy for Hedge Fund institutions to improve investment diversification. Unique Endeavor in Business & Social Sciences, 5(1), 110.

Tamraparani, V., & Dalal, A. (2023). Self generating & self healing test automation scripts using AI for automating regulatory & compliance functions in financial institutions. Revista de Inteligencia Artificial en Medicina, 14(1), 784796.

Tamraparani, V., & Islam, M. A. (2021). Improving Accuracy of Fraud Detection Models in Health Insurance Claims Using Deep Learning/AI. International Journal of Advanced Engineering Technologies and Innovations, 1(4).

Tamraparani, V., & Islam, M. A. (2023). Enhancing data privacy in healthcare with deep learning models & AI personalization techniques. International Journal of Advanced Engineering Technologies and Innovations, 1(01), 397418.

Tamraparani, Venugopal. (2022). Ethical Implications of Implementing AI in Wealth Management for Personalized Investment Strategies. International Journal of Science and Research (IJSR). 11. 16251633. 10.21275/SR220309091129.