Improved Face Detection Accuracy Using Haar Cascade Classifier Method and Esp32-Cam for Iot-Based Home Door Security

Modern technology has become a vital part of our daily lives, and the world has undergone remarkable advancements in various scientific and technological fields. The advancement of technology presents a variety of opportunities for students to promote academic development and make it easier to access education through online learning systems. The most difficult and most demanding task during learning is to be aware of and support the emotional side of students. Recognizing one's emotions is easy for humans, but it is a challenging task for computers due to the specific features of the human face. However, recent advances in computing and image processing have made it possible and easy to detect and categorize emotions in images and videos. This paper focuses on detecting learners' emotions in real time during synchronous learning. In this regard, a video/chat application has been developed for the tutor to detect the emotions of the learners while presenting his lesson. The emotions detected are separated into three states (Satisfied, Neutral and Unsatisfied); each state is made up of two or three distinct emotions. The objective is to assist teachers in adapting teaching methods in virtual learning settings according to the emotions of learners.

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Anti-Theft Flooring System using ESP32

Muthiyil,

et al. 2024

JEI

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The ESP32-powered anti-theft flooring system represents an innovative and cost-effective solution designed to enhance security across various settings, including homes, businesses, and diverse locations. At its core, the system comprises a network of strategically placed pressure sensors concealed beneath a flooring mat, seamlessly integrated with the ESP32 microcontroller featuring built-in Wi-Fi and a camera. When an object exceeding a predetermined weight threshold traverses the mat, the embedded sensors swiftly activate the ESP32, prompting it to capture a photograph of the event. This image is then promptly forwarded to a pre-configured email address, offering real-time visual insights into potential security breaches. Furthermore, the ESP32 can be programmatically configured to activate an audible alarm, providing an additional layer of security and acting as a powerful deterrent. The system’s design emphasizes user-friendliness, ease of installation, and adaptability to various environmental needs. Its customization options enable users to tailor the system to specific requirements, ensuring a seamless integration into any given space. Importantly, safety measures have been incorporated to prevent false alarms triggered by smaller entities, as the pressure sensors only respond to objects surpassing a predefined weight. Beyond its primary function of theft prevention, the ESP32 anti-theft flooring system unveils a realm of creative possibilities. Its applications extend to smart home automation, traffic monitoring, and even livestock tracking, showcasing the system’s versatility and adaptability in addressing diverse challenges. This multifaceted approach positions the ESP32 system not only as a robust security solution but also as a catalyst for innovation in various technological domains.

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Improved Face Detection Accuracy Using Haar Cascade Classifier Method and Esp32-Cam for Iot-Based Home Door Security

Cited by 3 publications

References 9 publications

Face Mask Detection and Social Distancing using Deep Learning

Face Mask Detection and Social Distancing using Deep Learning

Improving E-Learning by Facial Expression Analysis

Anti-Theft Flooring System using ESP32

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