Category Archives: Uncategorized

Authors: Ramya K. Cherukuvada, Raghu V. Kaspa

Abstract: Credit card fraud poses a substantial threat to the financial services industry, with billions of dollars lost annually across the globe. Traditional rule-based fraud detection systems are increasingly proving to be inadequate against sophisticated, constantly evolving fraud techniques. The dynamic nature of fraud demands equally dynamic countermeasures, and Artificial Intelligence (AI) has emerged as a highly effective solution. AI-powered fraud detection systems can learn from historical transaction data, recognize patterns, and adapt in real-time to detect potentially fraudulent activities. This paper provides an in-depth exploration of how AI is being leveraged in credit card fraud detection, the machine learning models used, real-world applications, challenges, and the future of fraud prevention technologies.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.139

 

Published by: vikaspatanker

Authors: Assistant Professor Sujata, Professor Dr. Brij Mohan Goel

Abstract: The proposed strategy should increase safety without sacrificing performance. It is being evaluated to determine whether any of the published research has any restrictions in terms of cloud-based software security issues. By using encrypted hybrid technique we can enhance the socket-based performance mechanisms like packet loss, latency rate, probability of error etc. The model suggested in the research is being compared with existing technologies in terms of performance, safety and dependability. This study is meant to investigate the proposed initiative's need, inspiration, and challenges. This research will examine how the intended work will be carried out in the actual world after examining the problem description. The Endeavour's algorithm and mechanism would describe the tools and procedures used in study. In this paper, the results of the study have been presented by the proposed model in such a way that it can perform better than previous studies. There are a variety of approaches you may take to this research, which we'll go over in more depth below. Exploratory studies may yield out new topics. Providing answers to a problem through doing research. Research work considered machine learning approach in order to classify different by of attacks in order to improve the security of hybrid socket based approach.

 

 

Published by: vikaspatanker

Authors: Khadri S S

Abstract: The flourish of Internet of Things (IoT) is leveraging the reform of today’s agriculture, including the development of new intelligent irrigation systems for the management of water resources. The integration of analytics-informed weather information in IoT-enabled irrigation systems enhancing accuracy, sustainability, and farm-level efficiency is examined in the current work. Traditional irrigation methods may rely on rigid schedules or manual manipulation that result in waste, lack of uniformity in the irrigation area, or in an inability to obtain the desired crop yield at the correct time of the year, particularly in areas with variable precipitation.
To overcome these limitations ,the system proposed here leverages a comprehensive network of IoT devices—including soil moisture sensors, temperature and humidity monitors, rain gauges, and weather stations—to gather live environmental data. This information is transmitted using communication protocols such as LoRaWAN, Wi-Fi, or NB-IoT to a centralized cloud environment. There, predictive models and machine learning algorithms analyze weather indicators like rainfall predictions and evapotranspiration rates, cross-referencing them with soil data to inform irrigation needs in real time.
Field evaluations revealed that the smart system cut water usage by 30–40% compared to traditional practices and boosted crop yields by 15–20% by maintaining optimal soil hydration. A user-friendly interface also gives farmers real-time oversight and the flexibility to intervene manually when needed. By combining IoT connectivity, multi-source data integration, and adaptive automation, the system helps farmers navigate extreme weather events such as droughts and sudden rainfall. Its affordable components and scalable design make it suitable for farms of all sizes.
Ultimately, this research highlights how IoT-powered weather analytics can drive more sustainable water use in agriculture, lower operational costs, and contribute meaningfully to global food security. It calls for greater adoption of smart irrigation systems that align agricultural productivity with environmental stewardship.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.137

Published by: vikaspatanker

Authors: Akshay M Dadas, Nagsen S Bansod, Dr.A.A.Khan, Dr.R.S.Deshpande

Abstract: Customers find online auctions convenient because they can transact from any location yet they face reliability issues due to fraud and false bidding sides a secure online auction platform based on blockchain and smart contracts and encryption features to provide clear and reliable operations to users the systems prototype received testing as a first step the investigation demonstrates that these system technologies enable users to prevent fraudulent practices and ensure data protection along with establishing increased confidence in platform usage.

DOI: http://doi.org/

 

Published by: vikaspatanker

Authors: Akshay M Dadas, Nagsen S Bansod, Dr.A.A.Khan, Dr.R.S.Deshpande

Abstract: Customers find online auctions convenient because they can transact from any location yet they face reliability issues due to fraud and false bidding sides a secure online auction platform based on blockchain and smart contracts and encryption features to provide clear and reliable operations to users the systems prototype received testing as a first step the investigation demonstrates that these system technologies enable users to prevent fraudulent practices and ensure data protection along with establishing increased confidence in platform usage.

DOI: http://doi.org/

 

Published by: vikaspatanker

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