Application of Real-Time Behavior Tracking Algorithm Combined with Yolov8 in Student Behavior Detection

Xin; Madhavi; Zhe

doi:https://doi.org/10.54216/JISIoT.180230

Journal of Cognitive Human-Computer Interaction | 2023

Survey Paper About Carbon Footprint

The aim of this proof of concept is to develop a framework to trace the carbon footprints emitted by fossil fuels during power generation. The framework will utilize a life cycle assessment approach to identify the amount of greenhouse gas emissions associated with each stage of the power generation process, from raw material (fuel) extraction to power delivery. The proof of concept will focus on the use of coal and natural gas, which are the most widely used fossil fuels in power generation.The data collected from sources is used to create model which can help us to estimate the amount of carbon footprint generated from different types of power plants like coal-fired power plants and natural gas-fired power plants.The results of this proof of concept are analyzed to identify areas where we can reduce the greenhouse gas emission  and also to develop and deploy strategies to transition to cleaner sustainable energy sources.Overall, this concept will provide a valuable tool for energy policymakers and stakeholders to make informed decisions about reducing carbon footprints from fossil fuel power generation

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Mohammad Nawaz Sheriff mail -

Mota Harshavardhan Reddy mail -

Mohamed Tharik mail

link https://doi.org/10.54216/JCHCI.060104

Volume & Issue

Vol. Volume 6 / Iss. Issue 1

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International Journal of BIM and Engineering Science | 2025

Artificial Intelligence in the Construction Industry: a Case Study on Developing an Intelligent Building Permit Management System

Amid rapid technological advancements and escalating environmental and urban challenges, the need to leverage advanced technologies such as Artificial Intelligence (AI) and Building Information Modeling (BIM) to enhance construction process management and urban planning becomes evident. The transformative potential of these technologies in the construction industry is evident, particularly in complex urban settings. This study presents the development of a smart system for managing building permits in the Syrian Arab Republic, utilizing the Python programming language and the Flask web framework, built upon BIM principles. The integration of AI with BIM is well-documented for its effectiveness in improving process management within the construction sector. The system aims to enhance the efficiency of the traditional permit issuance process by increasing transparency, reducing time and costs, and improving accuracy and organization. Implementation of this system in a Syrian city, as a case study, led to significant improvements in processing speed, accuracy, and overall user satisfaction. This paper discusses the system’s design, implementation, and impact on the efficiency of building permit transactions, showcasing how digital solutions can significantly contribute to urban planning and development processes. The methodology aligns with the guidelines outlined in the governmental directive for building permits in Marota City (2023), ensuring compliance with local regulatory frameworks.

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Reezkallah Mishtawi mail -

Sonia Salim Ahmad mail -

Ashi Ezz mail -

Eric Scheepbouwer mail

link https://doi.org/10.54216/IJBES.100208

Volume & Issue

Vol. Volume 10 / Iss. Issue 2

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Journal of Cognitive Human-Computer Interaction | 2023

Jester Lock - A Windows Based File Locker Locker

Windows based app locker have always been there in the app market, but only provide minimal security with the traditional security features like PIN, password. Moreover, the locked file / folder would be visible to everyone which only limits the access, which doesn’t completely preserve the privacy of the user. Hence there is a need of a Windows application that preserves the privacy along with the modern-day security features. In this paper, we have proposed a Windows based file locker application that uses face and emotion recognition along with an interactive GIF interface and have discussed its features.

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R. Ebino Frederic mail -

P. vijay mail -

M. Gurumurthi mail -

V. Hareshanmuhan mail -

V. Sathya mail

link https://doi.org/10.54216/JCHCI.060105

Volume & Issue

Vol. Volume 6 / Iss. Issue 1

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Fusion: Practice and Applications | 2024

Multi-Criteria Evaluation of the Effectiveness of Computer Crime Disclosure Under Ecuadorian Legal Regulations

Decision-making based on multiple criteria is common in various contexts, recognized for its high complexity in seeking viable solutions. Computer crimes encompass any act with criminal intent that seeks to cause harm or put at risk a legally protected interest using computer tools. This study aims to determine whether residents of Santo Domingo are aware of computer crimes established in Ecuadorian legislation, employing multicriteria evaluation techniques and the TODIM and PROMETHEE methods. These methodologies are complemented by neutrosophic single-value sets, based on neutrosophic logic, to effectively manage the indeterminate and inconsistent information typical in real-world scenarios. In this way, the utility of these techniques for addressing complex problems in daily life and in various social domains is demonstrated.

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Medına R. Carlos Alfredo mail -

Guambo Llerena M. Ángel mail -

Toapanta J. Leonardo mail

link https://doi.org/10.54216/FPA.150206

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Vol. Volume 15 / Iss. Issue 2

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Journal of Cognitive Human-Computer Interaction | 2024

Towards a Greener Future: Analyzing the Trends and Influences in Sustainable Energy Literature

The growth in sustainable energy relies significantly on the utilization of clean energy sources, attracting increasing attention in the literature with substantial growth in research outputs. This study employs bibliometric analysis via Scopus to depict the current cleaner energy research landscape and future directions. It amalgamates trends and influential research at the sustainability-renewable energy intersection. By mapping notable authors, institutions, and research clusters, it highlights interdisciplinary aspects across engineering, environmental science, economics, and policy studies. The journal "Renewable and Sustainable Energy Reviews" is pivotal in publishing articles on sustainable development and renewable energy. China leads in related research, with North China Electric Power University as a major contributor. The most cited article in Nature (2012) underscores the importance of sustainable energy for global prosperity, exploring solar, water-based, and biofuel energy, and outlining pathways for a sustainable future. This research not only reviews the current state-of-the-art literature but also informs researchers regarding the critical pathways and emerging trends in the sustainable development goals.

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Alpesh Kumar Dauda mail -

Ambarish Panda mail

link https://doi.org/10.54216/JCHCI.070101

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

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Journal of Cognitive Human-Computer Interaction | 2024

An Overview of Performance Validation, Testing Protocols, and Standards for Smart Meters

This document provides a thorough overview of the testing protocols and standards for smart meters, which are essential parts of the contemporary smart grid. It emphasizes the switch from analog to digital smart meters, which provide two-way communication and real-time data on electricity consumption. In order to guarantee accuracy, dependability, conformity with international standards such as those from the IEC, NIST, and BIS, and the protection of customer data, the document highlights the significance of conducting thorough testing. In order to evaluate several performance factors including insulation, accuracy, and electromagnetic compatibility, it covers a variety of tests, such as metrology, load switch capability, data exchange protocols, and communicability. Smart meters must be thoroughly tested and validated in order for them to operate effectively, reliably, and safely. This will help utilities minimize revenue losses and encourage good energy management.

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Vikram Kulkarni mail -

Bhisaji Surve mail

link https://doi.org/10.54216/JCHCI.070102

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

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Journal of Cognitive Human-Computer Interaction | 2024

Plasticycle 3D

A novel solution has been developed to tackle the largest environmental threat caused by detritus. Our innovative proposal involves a specialized mechanism that employs Convolutional Neural Networks (CNNs) for image processing to automatically segregate garbage. The segregated plastics can be melted based on their type and transformed into 3D filaments, which are subsequently used with 3D printers to create new products. Artificial Intelligence is responsible for running this entire process while ensuring cost efficiency, functionality, and low power consumption as its primary goals. This machine's user-friendly interface ensures access even for those who live on the streets... In addition to promoting a healthier lifestyle through recycled goods production opportunities via our recycling project could help establish new sustainable business models providing employment possibilities. Moreover, utilizing these manufactured items decreases living costs substantially making them an affordable yet environmentally friendly option at half price reduction. Our advanced technology brings us one step closer towards overcoming this critical challenge resulting in creating cleaner ambiance leading toward greener healthy earth benefiting future generations too!

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Muralidharan A. mail -

Pramod Chandra P. mail -

Steni Dev S. A. mail

link https://doi.org/10.54216/JCHCI.070103

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

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Journal of Cognitive Human-Computer Interaction | 2024

Sensor-Based System for Preventing Vehicle Overloading and Reducing Road Accidents

Vehicle overloading is a global problem causing accidents and infrastructure damage. We propose a sensor-based system to detect and alert drivers of overloading. The system consists of sensors that measure weight and compare it to the maximum limit. A trial will test its efficacy. The system aims to improve road safety and reduce accidents caused by overloading. The proposed system has significant potential for widespread implementation. Further development could lead to improved public safety and reduced infrastructure damage.

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Tharun Manipati mail -

Sakthivel B. mail -

Vamsi Krishna T. mail -

Rithesh R. mail

link https://doi.org/10.54216/JCHCI.070104

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

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Journal of Cognitive Human-Computer Interaction | 2024

Defense Against Adversarial Ai

The increasing prevalence of deep learning technology has paved the way for a new era of AI-powered capabilities, promising revolutionary advancements across various societal domains such as healthcare and autonomous vehicles. Despite offering potent solutions to complex problems, the formidable power of these AI systems is accompanied by a susceptibility that malicious actors could exploit. Adversarial attacks, particularly targeting deep learning models, involve the crafting of altered inputs, often imperceptible changes to images, to deceive or undermine the functionality of the AI system. Within the domain of autonomous driving systems, adversarial attacks pose a severe risk. Envision a situation where a precisely manipulated adversarial attack targets a red traffic light sign, causing the AI system to misclassify it as an entirely unrelated object, perhaps identifying it as a bird. The potential consequences of such misclassifications underscore the serious impact that adversarial attacks can exert on the safety and dependability of autonomous vehicles. The potential repercussions of such misclassification are severe, with the risk of causing traffic accidents and posing a notable safety threat. Ensuring the resilience and security of AI technologies against adversarial threats is of utmost importance as AI continues to play a pivotal role in critical applications such as healthcare, finance, and autonomous systems. It necessitates a holistic strategy that melds advanced research, meticulous testing, and the deployment of robust security measures. This comprehensive approach is essential for fostering trust and mitigating potential harm in an ever- growing, AI-driven world.

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Bhavani G. mail -

Soundarya S. mail -

Tejashwini V. mail -

Sumitha S. mail

link https://doi.org/10.54216/JCHCI.070105

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2026

Application of Real-Time Behavior Tracking Algorithm Combined with Yolov8 in Student Behavior Detection

In the intelligent teaching environment, it is indirect and difficult for teachers to capture learners’ learning attitudes and behaviors through digital learning behavior data provided by intelligent platforms. The purpose of this paper is to improve the precision of student behavior detection in teaching, and to provide teachers with a more reliable basis for making teaching plans. The Yolov8 algorithm is applied to student behavior recognition, and a bounding box loss function based on dynamic focusing mechanism is introduced to make a balance between samples with good regression quality and poor regression quality. Through experimental analysis, we can see that the real-time behavior tracking algorithm combined with Yolov8 proposed in this paper has a good application effect in student behavior detection. Moreover, it not only improves the precision of student behavior recognition, but also improves the stability of the algorithm, which is conducive to the effective development of subsequent smart teaching models.

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Xin Bai mail -

Madhavi Devaraj mail -

Zhe Zhang mail

link https://doi.org/10.54216/JISIoT.180230

Volume & Issue

Vol. Volume 18 / Iss. Issue 2

Details open_in_new