Transparent Peer Review By Scholar9
Next-Gen Home Security Framework with Facial Recognition and IoT Integration
Abstract
It is now essential to improve home security systems in the current technological era. This research offers a revolutionary method of smart home security by combining a web interface, facial recognition, and the Internet of Things (IoT) into a single solution. The suggested method controls entry to a house by using machine learning algorithms to recognise faces accurately and in real time. An Internet of Things (IoT)-enabled servo motor is turned on to unlock the door after successful recognition. Users may monitor and control the system remotely with greater comfort and flexibility thanks to a Flask-developed web interface. The system is made to overcome the shortcomings of previous models and provide a reliable, effective, and user-friendly home security solution. A thorough discussion of the implementation is given, highlighting its benefits and possible changes to further enhance the system's performance.
Phanindra Kumar Kankanampati Reviewer
10 Oct 2024 03:51 PM
Approved
Relevance and Originality
The Research Article addresses a crucial need for enhanced home security in today's technological landscape. It presents an original solution by integrating facial recognition, IoT, and a web interface, making it particularly relevant in the context of increasing security concerns. This innovative approach not only meets current demands but also contributes to the evolution of smart home technology.
Methodology
The Research Article employs a clear methodology, detailing how the system combines facial recognition with IoT capabilities to control home access. However, more information on the specific machine learning algorithms used for facial recognition would strengthen the methodological rigor. Additionally, providing details about the experimental setup or user testing would enhance the credibility of the findings.
Validity & Reliability
The validity of the proposed system is supported by its reliance on established technologies like facial recognition and IoT. However, to ensure reliability, it would be beneficial to present empirical data demonstrating the system's effectiveness in real-world scenarios. Discussing potential limitations or challenges faced during implementation would provide a more balanced view of the system’s capabilities.
Clarity and Structure
The Research Article is generally well-structured, guiding readers through the problem statement, proposed solution, and implementation details. However, enhancing clarity could be achieved by including visual aids, such as diagrams or flowcharts, to illustrate the system architecture and user interactions. This would help readers better understand the technical components involved.
Result Analysis
The result analysis effectively outlines the advantages of the proposed home security system, including its reliability and user-friendliness. However, including specific performance metrics, such as recognition accuracy rates or user satisfaction scores, would strengthen the analysis. Additionally, discussing future improvements or enhancements could provide valuable insights into the system’s potential evolution and adaptability to emerging security needs.
IJ Publication Publisher
Done Sir
Phanindra Kumar Kankanampati Reviewer