AI and Machine Learning for Remote Suspicious Action Detection and Recognition
DOI:
https://doi.org/10.18034/abcjar.v11i2.694Keywords:
Behavior Recognition, Suspicious Action, Remote Areas, Machine LearningAbstract
There is little question that the unchecked rise in population is to blame for the alarming increase in crime rates seen in industrialized and developing nations. As a direct consequence of this, there has been an increase in the number of calls for the use of video surveillance to address concerns about ordinary life and private property. As a consequence of this, we need a system that is capable of accurately recognizing human activity in real-time. Researchers have lately investigated machine learning and deep learning as potential methods for identifying human activities. To prevent fraud, we devised a technique that employs human activity recognition to examine a series of occurrences, evaluate whether or not a person is a suspect, and then take appropriate action. This system used deep learning to assign labels to the video based on human behavior. We can detect suspicious behavior based on the categories mentioned above of human activity and time duration by utilizing machine learning, which achieves an accuracy of around one hundred percent. This research article will detect suspicious behavior using optimal, effective, and quick methods. Using popular public data sets, the experimental findings described here highlight the approach's remarkable performance while only requiring a small amount of computational complexity.
Downloads
References
Amin, R., & Mandapuram, M. (2021). CMS - Intelligent Machine Translation with Adaptation and AI. ABC Journal of Advanced Research, 10(2), 199-206. https://doi.org/10.18034/abcjar.v10i2.693 DOI: https://doi.org/10.18034/abcjar.v10i2.693
Ballamudi, V. K. R., Desamsetti, H., & Mandapuram, M. (2022). Influence of Digitization on Human Resources (HR) Services and Processes. ABC Research Alert, 10(3), 32–36. https://doi.org/10.18034/ra.v10i3.653 DOI: https://doi.org/10.18034/ra.v10i3.653
Bodepudi, A., Reddy, M., Gutlapalli, S. S., & Mandapuram, M. (2019). Voice Recognition Systems in the Cloud Networks: Has It Reached Its Full Potential? Asian Journal of Applied Science and Engineering, 8(1), 51–60. https://doi.org/10.18034/ajase.v8i1.12 DOI: https://doi.org/10.18034/ajase.v8i1.12
Bodepudi, A., Reddy, M., Gutlapalli, S. S., & Mandapuram, M. (2021). Algorithm Policy for the Authentication of Indirect Fingerprints Used in Cloud Computing. American Journal of Trade and Policy, 8(3), 231–238. https://doi.org/10.18034/ajtp.v8i3.651 DOI: https://doi.org/10.18034/ajtp.v8i3.651
Dekkati, S., & Thaduri, U. R. (2017). Innovative Method for the Prediction of Software Defects Based on Class Imbalance Datasets. Technology & Management Review, 2, 1–5. https://upright.pub/index.php/tmr/article/view/78
Desamsetti, H. (2016). Issues with the Cloud Computing Technology. International Research Journal of Engineering and Technology (IRJET), 3(5), 321-323.
Desamsetti, H., & Mandapuram, M. (2017). A Review of Meta-Model Designed for the Model-Based Testing Technique. Engineering International, 5(2), 107–110. https://doi.org/10.18034/ei.v5i2.661 DOI: https://doi.org/10.18034/ei.v5i2.661
Gutlapalli, S. S. (2016). Commercial Applications of Blockchain and Distributed Ledger Technology. Engineering International, 4(2), 89–94. https://doi.org/10.18034/ei.v4i2.653 DOI: https://doi.org/10.18034/ei.v4i2.653
Gutlapalli, S. S. (2017a). The Role of Deep Learning in the Fourth Industrial Revolution: A Digital Transformation Approach. Asian Accounting and Auditing Advancement, 8(1), 52–56. https://4ajournal.com/article/view/77
Gutlapalli, S. S. (2017b). An Early Cautionary Scan of the Security Risks of the Internet of Things. Asian Journal of Applied Science and Engineering, 6, 163–168. https://ajase.net/article/view/14
Gutlapalli, S. S., Mandapuram, M., Reddy, M., & Bodepudi, A. (2019). Evaluation of Hospital Information Systems (HIS) in terms of their Suitability for Tasks. Malaysian Journal of Medical and Biological Research, 6(2), 143–150. https://doi.org/10.18034/mjmbr.v6i2.661 DOI: https://doi.org/10.18034/mjmbr.v6i2.661
Mandapuram, M. (2017). Security Risk Analysis of the Internet of Things: An Early Cautionary Scan. ABC Research Alert, 5(3), 49–55. https://doi.org/10.18034/ra.v5i3.650 DOI: https://doi.org/10.18034/ra.v5i3.650
Mandapuram, M., & Hosen, M. F. (2018). The Object-Oriented Database Management System versus the Relational Database Management System: A Comparison. Global Disclosure of Economics and Business, 7(2), 89–96. https://doi.org/10.18034/gdeb.v7i2.657 DOI: https://doi.org/10.18034/gdeb.v7i2.657
Mandapuram, M., Gutlapalli, S. S., Bodepudi, A., & Reddy, M. (2018). Investigating the Prospects of Generative Artificial Intelligence. Asian Journal of Humanity, Art and Literature, 5(2), 167–174. https://doi.org/10.18034/ajhal.v5i2.659 DOI: https://doi.org/10.18034/ajhal.v5i2.659
Mandapuram, M., Gutlapalli, S. S., Reddy, M., Bodepudi, A. (2020). Application of Artificial Intelligence (AI) Technologies to Accelerate Market Segmentation. Global Disclosure of Economics and Business 9(2), 141–150. https://doi.org/10.18034/gdeb.v9i2.662 DOI: https://doi.org/10.18034/gdeb.v9i2.662
Reddy, M., Bodepudi, A., Mandapuram, M., & Gutlapalli, S. S. (2020). Face Detection and Recognition Techniques through the Cloud Network: An Exploratory Study. ABC Journal of Advanced Research, 9(2), 103–114. https://doi.org/10.18034/abcjar.v9i2.660 DOI: https://doi.org/10.18034/abcjar.v9i2.660
Thaduri, U. R., Ballamudi, V. K. R., Dekkati, S., & Mandapuram, M. (2016). Making the Cloud Adoption Decisions: Gaining Advantages from Taking an Integrated Approach. International Journal of Reciprocal Symmetry and Theoretical Physics, 3, 11–16. https://upright.pub/index.php/ijrstp/article/view/77
Thodupunori, S. R., & Gutlapalli, S. S. (2018). Overview of LeOra Software: A Statistical Tool for Decision Makers. Technology & Management Review, 3(1), 7–11.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Sreekanth Dekkati, Sai Srujan Gutlapalli, Upendar Rao Thaduri, Venkata Koteswara Rao Ballamudi
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.