Daily Archives: June 4, 2025

Authors: Dr. RajaGopal Kayapati

 

Abstract: Electrical power distribution systems are critical infrastructures that require robust fault detection and repair mechanisms to ensure uninterrupted service. Traditional fault detection systems often struggle with accuracy and real-time adaptability. This paper proposes a hybrid machine learning (ML) framework that integrates ensemble learning and deep learning models to predict faults and recommend repair actions in power distribution systems. The proposed system combines the strengths of decision trees, random forests, and long short-term memory (LSTM) networks to improve accuracy, precision, and response time. Experimental results on benchmark electrical datasets demonstrate a significant performance improvement over conventional models. This hybrid approach provides utility companies with a scalable, intelligent fault management solution, thereby reducing downtime and maintenance costs.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.135

 

Published by: vikaspatanker

Authors: NAZISH KHAN, Ms. Shruti Rawat

 

 

Abstract: Gender discrimination in the workplace persists despite considerable strides toward gender equality in many societies. At the heart of this issue lie entrenched societal norms and biases that shape organizational structures and decision-making processes. One of the most insidious aspects of gender discrimination is its often subtle and unconscious nature, making it challenging to identify and address. Research has shown that women continue to face disproportionate barriers to career advancement, including biases in hiring, promotion, and compensation practices. Moreover, women are more likely to encounter microaggressions, harassment, and stereotyping in the workplace, creating hostile environments that undermine their professional growth and well-being. The impacts of gender discrimination extend far beyond individual experiences, affecting organizational culture and performance. When talented individuals are overlooked or marginalized based on gender, companies miss out on valuable perspectives and contributions. This not only stifles innovation but also perpetuates inequalities within the workforce. Additionally, gender discrimination can erode employee morale, leading to decreased productivity, higher turnover rates, and reputational damage for organizations. To effectively address gender discrimination, it is essential to recognize and challenge the underlying biases and systemic inequalities that perpetuate it. This requires a comprehensive approach that includes policy interventions, cultural shifts, and individual awareness. Organizations must prioritize diversity and inclusion initiatives, implementing strategies to mitigate bias in recruitment, promotion, and performance evaluation processes. Training programs that raise awareness of unconscious bias and foster inclusive behaviors can help create more equitable work environments.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Nikhil Kumar Khemaria, Vinay Kumar Pathak

 

 

Abstract: The paper study exhibits the force quality issue because of establishment of wind turbine with the network. In this proposed plan appropriation static compensator (DSTATCOM) is associated with a battery vitality stockpiling framework (BESS) to relieve the force quality issues. The battery vitality stockpiling is incorporated to support the genuine force source under fluctuating wind power. The DSTATCOM control plan for the network associated wind vitality era framework for force quality change is recreated utilizing MATLAB/SIMULINK in force framework piece set. At last the proposed plan is connected for both adjusted and uneven nonlinear burdens.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Prof.Said Shubhangi K., Prof . Auti Mayuri A., Miss.Gund Sakshi Dattatray, Miss.Jadhav Shreya Shivaji, Miss.Satware Vidya Laxman

 

 

Abstract: The increasing demand for safety and efficiency on construction sites has prompted the need for innovative technological solutions aimed at protecting workers in dynamic and hazardous environments. This research introduces a novel IoT-based smart helmet designed specifically for construction workers. The proposed helmet is embedded with intelligent sensors and communication modules that enable real-time monitoring of the worker’s location, ambient environmental conditions, and task status. The helmet aims to bridge the gap between passive protective gear and active monitoring systems, thereby enhancing situational awareness and minimizing response times during emergencies. By incorporating modules such as a smoke sensor, GPS, proximity detection, emergency buttons, and wireless data transmission, the helmet transforms into an advanced safety monitoring tool. It is capable of automatically switching to "Work Mode" when worn and relays data continuously to a cloud-based server via ThinkSpeak. In the event of a detected emergency—such as exposure to smoke or the press of an emergency button—instant email alerts are sent to supervisors with the worker’s exact location. This real- time data acquisition and communication significantly improves site supervision, promotes worker accountability, and contributes to a safer construction environment.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Assistant Professor S.Janani

Abstract: Artificial Intelligence (AI) and the Internet of Things (IoT) are Innovatively integrated to advance smart cities. Urban infrastructure depends on Wireless Sensor Networks (WSNs) to gather and transmit data, enabling edge-based AI models to make context-aware decisions. This literature review examines the evolution of city models, IoT technologies of role, and the application of edge computing and AI techniques to enhance context-aware systems. Additionally, it incorporates insights into AI implementation across various domains, including healthcare, education, mobility, governance, and environmental sustainability. We discuss research potential, technological advancements, and significant concerns like energy efficiency, scalability, privacy, and security. Diagrams illustrating city architecture and conceptual AI frameworks are included to enhance understanding.

 

 

Published by: vikaspatanker

Authors: A.BABISHA

 

 

Abstract: With the rapid penetration of the Internet into every part of our daily life, it is agreed that it will be an important medium for future communication, perhaps even more important than the television This product is a self-contained product made to facilitate the users with the facility to detect which video amongst the 2 is a real or fake one. This can be very helpful the society to control and reduce blackmailing and sharing of obscene content. We extract the feature points from the images in the training dataset using FAST and get the feature point descriptors using BRIEF. Then using DLIB face detector to detect face region and regions inside the face. We group the feature points based on the region that they are falling in. Then the feature point descriptors are aggregated to train the random forest classifier.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Pratik R. Taye, Satyam M. Kharate, Saket D. Aadhav, Prof. Suraj D. Kulkarni

 

 

Abstract: The Automatic Street Light Fault Detection and Monitoring System Using IoT is an advanced approach for maximizing efficiency in the management of street lights and energy consumption. With the help of the Internet of Things (IoT), the proposed system allows for automatic fault detection, monitoring, and management of street lights infrastructure. An array of intelligent sensors are utilized in the proposed system to identify and communicate faults in wiring or burnt out lamps to the control unit using wireless means. This modern technique reduces the need for manual inspections, helps lower the downtime for repairs, and guarantees that street lights remain on. More so, the system has advanced reporting capabilities that automate maintenance schedule reports and energy usage reports. Automation of the report generation further increases efficiency in fault detection and subsequently lowers operational costs while enhancing safety in public spaces.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: A.BABISHA

 

 

Abstract: With the rapid penetration of the Internet into every part of our daily life, it is agreed that it will be an important medium for future communication, perhaps even more important than the television This product is a self-contained product made to facilitate the users with the facility to detect which video amongst the 2 is a real or fake one. This can be very helpful the society to control and reduce blackmailing and sharing of obscene content. We extract the feature points from the images in the training dataset using FAST and get the feature point descriptors using BRIEF. Then using DLIB face detector to detect face region and regions inside the face. We group the feature points based on the region that they are falling in. Then the feature point descriptors are aggregated to train the random forest classifier.

DOI: http://doi.org/

 

 

Published by: vikaspatanker