Authors: P.Lavanya, Bibhuti Bhusan Rath, A. Lashya, K. Kirankumar, B. Likitha

 

Abstract: Ensuring consistent and efficient energy harvesting from solar photovoltaic (PV) systems remains a challenge due to unpredictable environmental conditions. To address this, a hybrid Maximum Power Point Tracking (MPPT) technique is presented, combining a conventional perturb-and-adjust method with fuzzy logic-based control. This approach dynamically modifies the control signal for a step-up converter, allowing the PV array to maintain optimal power output. The system's performance was analysed using MATLAB/Simulink under both stable and varying sunlight conditions. Results confirm that the hybrid controller delivers better efficiency, quicker response to changes, and reduced output fluctuations when compared to traditional MPPT strategies. These findings highlight its potential for integration into intelligent solar energy systems.

DOI: http://doi.org/ijsret.vol.11.issue3.148

 

Published by: vikaspatanker

Authors: Ms. Neekita Singh, Dr.Jasbir Kaur, Mrs.Sandhya Thakkar

Abstract: This paper presents a comprehensive framework combining data science, geospatial analysis, and interactive visualizations to study crimes against women in India. Analyzing crime trends includes three key components: using data science, an interactive Power BI dashboard visualization [6], and a Python-based crime hotspot mapping application using Streamlit. The crime hotspot app allows users to search for any location in India and view crime data displayed on a map, potentially aiding in crime prevention by providing real- time awareness [5]. By integrating these tools, the framework offers a multi-faceted approach to crime analysis, enabling deeper insights into spatial and temporal crime patterns. The study aims to assist policymakers, law enforcement, and the public in understanding and mitigating crime.

DOI: http://doi.org/ijsret.vol.11.issue3.147

 

Published by: vikaspatanker

Authors: Ogundare, Adaramola, Raji, Raji, Ajenikoko, Adebeshin, Onot

Abstract: Every power system comprises many generators that are connected in parallel. For the system to operate in steady-state stability, all the generators must run synchronously. If any of the connected generators loses synchronism, system stability is lost, and voltage collapse may occur. To avoid this situation, steady-state stability (SSS), which involves voltage stability and synchronisation of generators, must be monitored. This paper, therefore, focuses on the SSS using the 6-bus IEEE test network and the Nigerian 30-bus, 330 kV grid network as case studies. Power-flow analysis was carried out for the case studies. Static var compensator (SVC) and additional parallel transmission lines were used to carry out voltage improvement for each network. The use of SVC for both IEEE and Nigerian networks indicates better voltage compensation than using transmission line enhancement, but the reverse is true for power loss reduction. The power losses in the 6-bus IEEE for original and improved networks with SVC and additional transmission lines are 1.8 %, 1.6 %. and 1.2 % respectively. At the same time, those of the Nigerian 30-bus, 330 kV network are 4.3%, 3.7%, 3.10%, respectively. Synchronous Power Coefficient (SPC) was used to carry out SSS by considering load additions in steps of 20% to the original and modified networks. SSS of the modified network with SVC and the original network were approximately the same. In contrast, the SSS was improved for the networks modified with additional transmission lines. Since SSS depends on the system inertia during load variation, the inertia of the network modified with the transmission lines is improved, while SVC does not exhibit noticeable inertia properties.

Published by: vikaspatanker

Authors: Anay Sunilkumar Pandya

Abstract: This paper presents the conceptual design and testing of an AI-enhanced, terrain-adaptive energy optimization module for electric two-wheelers. Unlike traditional plug-and-play extenders, this system uses a combination of gyroscopic sensors and machine learning to predict driver behavior and road conditions, optimizing power delivery accordingly. Simulated testing shows potential range improvements of up to 38% while maintaining battery longevity. The innovation is particularly suited for urban EV users in mixed-terrain environments. The invention is novel and under consideration for intellectual property protection.

Published by: vikaspatanker

Authors: Y Kushi Reddy, Yallamanchi Himabindu, Anish NC, CV Anusha Reddy, S Harshit Sai,

 

 

Abstract: In recent years, the integration of artificial intelligence (AI) into healthcare has enabled innovative approaches for early disease detection and diagnosis. This paper presents the design and development of an AI-powered mobile application that performs preliminary health diagnosis based on user-reported symptoms. The proposed system utilizes machine learning models trained on verified medical datasets to identify possible health conditions from input symptoms, aiming to assist users in seeking timely medical consultation. The application is built using Python, TensorFlow, and a Flask-based backend, with a simple and interactive user interface. The system also emphasizes user privacy and data security. Testing demonstrates the model’s potential to deliver reliable symptom-based predictions, thereby offering a scalable and accessible solution to basic health assessment. This project showcases how AI technologies can be effectively applied in the medical domain to bridge gaps in early diagnosis and promote preventive healthcare.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Shankar.K, Mrs.J.ANITHA, M.E.

Abstract: Concrete is the most widely used construction material in the world, and its production is responsible for a significant amount of CO2 emissions, making it a major contributor to global warming. Selfcompacting concrete (SCC) is a type of concrete that can flow under its own weight and fill all the spaces in the formwork without the need for external vibration, which makes it more sustainable compared to traditional concrete. In this study, the performance of SCC using Sugarcane bagasse ash (SCBA) and Ground granulated blast furnace slag (GGBS) as mineral admixtures was investigated for sustainable construction. The study focused on determining the optimum percentages of both SCBA and GGBS to produce SCC with enhanced properties. The SCC mix with SCBA10 GGBS20 achieved a compressive strength, which is significantly higher than the control mix without any mineral admixtures. The flexural strength and tensile strength of SCC mixes with SCBA10 GGBS20 were also higher than the control mix. In terms of durability, the SCC mixes with SCBA10 GGBS20 exhibited better resistance to water penetration, chloride ion penetration, and acid attack compared to the control mix. The UPV test results showed that SCC mixes with SCBA10 GGBS20 had a more uniform and dense structure, which indicates better overall durability. The study is aligned with Sustainable Development Goal 12 (SDG 12) of the United Nations, which aims to ensure sustainable consumption and production patterns. The optimal mix of SCBA10 GGBS20 can lead to the production of high- performance SCC, which is crucial for sustainable construction practices. In conclusion, this study demonstrates the feasibility of using SCBA and GGBS as mineral admixtures in SCC production to enhance its performance and sustainability. The study's findings provide valuable insights for researchers, engineers, and construction professionals to develop sustainable and costeffective concrete mixes for construction projects.

Published by: vikaspatanker

Authors: Sonali Bahuguna, Professor Indu Sharma

Abstract: This research examines the connection between educational and vocational interests and the academic performance of secondary school students in Delhi. Considering the recent inclusion of vocational courses in more than 800 government schools as part of the samagra shiksha scheme, this study examines the correlation between students' interests and their academic achievements. The study employs a stratified random sample of 500 students from various socio-economic and institutional backgrounds, utilizing standardized interest inventories and academic data analysis. The findings indicate a strong positive relationship between educational and vocational interests and academic performance, with vocational interests having a greater predictive power. This supports the belief that incorporating student interests into educational content can enhance academic engagement and achievement.

 

 

Published by: vikaspatanker

Authors: Priyanka Verma, Garima Singh, Assistant Professor Pooja Sharma

Abstract: Traffic congestion at signalized intersections is a critical issue in urban areas, leading to increased travel time, fuel consumption, and environmental pollution. This study presents an optimized traffic signal timing plan for Vyapam Square, Bhopal, using Webster’s formula, a widely recognized method for minimizing delays at signalized intersections. The research involves field data collection, including traffic volume counts, saturation flow rates, and existing signal timings. Using this data, the optimal cycle length and green time allocation for each phase are computed, ensuring a balanced distribution of green time while minimizing average vehicle delay. A graphical representation of traffic flow versus delay is provided to visualize the efficiency improvements before and after optimization.

 

 

Published by: vikaspatanker

Authors: Tejes theethan M, Akshaya R, Merlin Shiny j, Dharani M

 

Abstract: This work is the structure of an autonomous driving system. This paper aims to determine the current state of autonomous vehicles, their potential impacts, and the necessary preparation for smart urban mobility. Autonomous refers to the movement or the work done on its own. Autonomous driving systems are divided into several ways, such as Autonomous under- water vehicles, Autonomous airborne vehicles, and Autonomous land vehicles. The potential benefits of lane autonomous vehicles are to describe the importance of navigation algorithms, speed control methods, adoption factors, and the increased infrastruc- ture needs for Connected autonomous vehicles’ integration. The major key elements are based on sensors, navigation, radar, planning techniques, communication, and software. The results of this research have important implications for future research and the framework of autonomous vehicle technologies in road trans- portation. Index Terms—autonomous driving, sensor, RADAR, navigation, software

DOI: 10.61137/ijsret.vol.11.issue3.142

 

Published by: vikaspatanker

Authors: Faiza Shaik

 

 

Abstract: The use of nanorobotics in cancer therapy represents a groundbreaking evolution in the field of biomedical sciences, offering precision, efficiency, and adaptability in targeting malignant cells. These nanometer-scale devices are engineered to perform complex tasks at the cellular and molecular levels, enabling the direct delivery of anticancer agents to tumors while minimizing damage to healthy tissue. This paper explores the foundational principles of nanorobotics, their diverse types, and the technological advancements enabling their application in oncology. It delves into the mechanisms through which nanorobots navigate biological environments, recognize cancerous cells, and administer therapeutic agents with unmatched specificity. Additionally, the paper addresses the integration of sensors, actuators, and logic gates within nanorobots to enhance decision-making and responsiveness in real-time conditions. Challenges such as biocompatibility, immune response, power sources, and regulatory hurdles are discussed in detail. Furthermore, current experimental studies, clinical trials, and future perspectives in the development of nanorobotics for cancer therapy are critically analyzed. The convergence of nanotechnology, robotics, and medicine through nanorobotics holds the promise of redefining cancer treatment paradigms with higher survival rates and lower side effects.

DOI: http://doi.org/

 

 

Published by: vikaspatanker