The IoT is being created by Internet and billions of physical devices (IoT). These devices are producing more useful or meaningless data. This data must be prepared and transmitted, which is a difficult task. Future research directions and other IoT applications are also discussed. The security sector is undoubtedly one of the IoT framework's application areas. It is essential to a common little effort solution to prevent wrongdoing and guarantee the safety of individuals from the home, military, industry, and other settings. This study covers the depiction driven evolution procedure for AI Security System employing Raspberry Pi IoT setup. It makes note at end of the client’s expectation. Such kind of instance is to share the information and protect with the Internet of Things that are more dependent by having the methods of Artificial Intelligence which supports the level of proximity and some of the non-mistaken with an accuracy of 90 percent proof, and the major confirmation to be made here is being a part of this. This method utilizes the help of electric door that are striking the actuator and the USB type web camera with the example of Image-gathering. It is also a kind of application with a standard programming Interfaces to collect similar gaming plans which are to be more related with the Internet of Things which are based on boarding knowledge of Raspberry Pi and also the steganography type distribution.
Keywords
Artificial Intelligence, Machine Learning, Internet of Things, Webcam, USB.
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CRediT Author Statement
The authors confirm contribution to the paper as follows:
Conceptualization: Karthika P and Balamurali S;
Methodology: Balamurali S;
Software: Karthika P;
Data Curation: Karthika P and Balamurali S;
Writing- Original Draft Preparation: Balamurali S;
Visualization: Karthika P and Balamurali S;
Investigation: Karthika P and Balamurali S;
Supervision: Balamurali S;
Validation: Balamurali S;
Writing- Reviewing and Editing: Karthika P and Balamurali S;
All authors reviewed the results and approved the final version of the manuscript.
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Karthika P
Department of Computer Applications, Kalasalingam Academy of Research and Education, Krishnan Koil, Viruthunagar, Tamil Nadu, India.
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Cite this article
Karthika P and Balamurali S, “Enhancement of a Machine Learning Allocation with Video Copy Detection using IoT with Steganography for Raspberry Pi”, Journal of Machine and Computing, pp. 890-899, April 2025, doi: 10.53759/7669/jmc202505070.
