2771-1463ISSN (Online)
2771-1471ISSN (Print)
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.
Read MoreDoi: https://doi.org/10.54216/JCHCI.070101
Vol. 7 Issue. 1 PP. 08-16, (2024)
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.
Read MoreDoi: https://doi.org/10.54216/JCHCI.070102
Vol. 7 Issue. 1 PP. 17-25, (2024)
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!
Read MoreDoi: https://doi.org/10.54216/JCHCI.070103
Vol. 7 Issue. 1 PP. 26-35, (2024)
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.
Read MoreDoi: https://doi.org/10.54216/JCHCI.070104
Vol. 7 Issue. 1 PP. 36-40, (2024)
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.
Read MoreDoi: https://doi.org/10.54216/JCHCI.070105
Vol. 7 Issue. 1 PP. 41-47, (2024)