Category Archives: Uncategorized

Performance of Seismic Analysis of Rc Structure High Rise G+13 Multi-Storied Building by ETABS
Authors:-B. Sri Kalyan, B. Harish, M. S. Prasanth, K. S. S. A. N. Kishore Kumar, B. Sridhar, J. Teja

Abstract-Earthquake is a natural calamity that has taken toll of millions of lives throughout the ages. The earthquake ranks as one of the destructive events recorded so far in India in terms of death and damage to infrastructure. Due to the present environmental condition and behavior of tectonic plates, it has become utmost necessary for civil engineers to consider the effects of the earthquake during the designing of the building. Also, most parts of India are under the earthquake-prone zone, so it has become necessary to consider earthquake load while designing a structure to minimize the effects of the earthquake. In this project work, a (G+13) storey high rise building is analysed in seismic zone-V by both equivalent lateral force method and response spectrum method. After analysis, various response parameters like storey shear, storey displacement, storey drift, etc. are studied and the results are also compared. The analysis of building under construction is also done and the results of base shear at different storey level of construction phase are also compared.

DOI: 10.61137/ijsret.vol.11.issue2.310

Published by: Kajal Tripathi

Design and Structural Behaviour of Modern Structure by Using ETABS
Authors:-B. Sri Datta Subramanyam1, S.S.S.Narendra2, N. Lakshman3, D.V. Venkata Sai4, G. Gnana Das5

Abstract-ETABS stands for extended three-dimensional analysis of building systems. The main purpose of this software is to design multi-storeyed building in a systematic process. The effective design and construction of an earthquake resistant structure have great importance all over the world. This project presents multi-storied residential building analysed and designed with lateral loading effect of earthquake using ETABS. This project is designed as per IS 1893-PART 2:2002, IS 456-2000. Every structural engineer should design a building with most efficient planning and also be economical. They should ensure that is serviceable, habitable in healthy environmental for its occupants and have longer design period. Structurally robust and aesthetically pleasing building are beginning constructed by combining the best properties of any construction material and at the same time meeting a specific requirement like type of building and its loads, soil condition, time, flexibility and economy. The high-rise buildings are best suited solution. This Project discusses the analysis of a multistoried building depending up on the area prepare a plan based on the requirements. The plan area is 3500sqft of 15m height i,e G+4. And each floor consisting of 2 flats. Each flat with 3bhk software used to draw the plan is AutoCAD 2019.We have analysis and design of multistoried building using ETABS we have applied all the loads and its combination to the structure and it is safe.

DOI: 10.61137/ijsret.vol.11.issue2.309

Published by: Kajal Tripathi

Earthquake Performance of Multistorey Building by Using Sap2000
Authors:-B. Sri Datta Subramanayam, P. Jagadeeswar Reddy, D. Vinay, K. Shameela Keerthi, G. John Mukesh, N. Mani Kumar, V. Durga Vinod Kumar

Abstract-Earthquake in the simplest terms can be defined as Shaking and vibration at the surface of the earth resulting from underground movement along a fault plane. The vibrations produced by the earthquakes are due to seismic waves. Among different types of dampers, viscoelastic [VE] dampers are used for this numerical study. Viscoelastic dampers are considered to be better than most of the passive energy dissipation devices. Researches done on the improvement of its performance for analyzing structures have always been in vogue. The significant change in the response of the structures to make it resistant to earthquake and wind forces is the main idea behind using such devices. In this numerical study, seismic response of G+4 structures will analyze having with and without damper. The damper will be considered in the place of critical sections. Modeling and analysis of the structures and installation of the dampers are done by using finite element modeling software [SAP2000]. Time history analysis was used to simulate the response of the structures. The structure is design in accordance with seismic code is 1893: 2000 under seismic zone III with the help of SAP 2000. Damper systems are designed to prevent injuries to the residents by absorbing the input seismic energy and reduce the deformations in the structure.

DOI: 10.61137/ijsret.vol.11.issue2.308

Published by: Kajal Tripathi

Seismic Analysis and Design of Multi-Storey Building With and Without Shear Wall G+15 Using Staad.Pro
Authors:-B Sri Kalyan, A Ganga Nagini, M Leela Archana, P Prathyusha, K V V Harsha Vardhan, M Durga Prasad, P T V S Varma

Abstract-A multi storey building is a building that consists has multiple floors above ground in the building. Multi-storey buildings aim to increase the floor area of the building without increasing the area of the land and saving money. Analysis of multi-storey building frames involves lot of complications and edacious calculations by conventional methods. To carry out such analysis is a time-consuming task. Substitute frame method for analysis can be handy in approximate and quick analysis instead of bidding process. Till date, this method has been applied by designers for vertical loading conditions. The represented plan given to office purposes can accommodate with minimum facilities. Generally, buildings may be failed by bending moments, shear forces acting on members of the building. By keeping these failures in mind, we designed beams, columns, footings by considering maximum loads on members. For loads calculation, substitute frame method is used for reducing the complexity of calculations and saving time. We know R.C structural system is most common nowadays in urban regions with multi-bay and multi-storey’s, keeping its importance in urban regions especially, A building frame consists of number of bays and storey. A multi-storey, multi- paneled frame is a complicated statically intermediate structure. A design of R.C building With and without shear wall of G+15 storey frame work is taken up. The building in plan (30m x 20m) consists of columns built monolithically forming a network. The design is made using software on structural analysis design (STAAD-PRO). The building subjected to both the vertical loads as well as horizontal loads. The vertical load consists of dead load of structural components such as beams, columns, slabs etc and live loads. The horizontal load consists of the wind forces thus building is designed for dead load, live load and wind load and seismic loads as per IS 875. The building is designed as two-dimensional vertical frame and analyzed for the maximum and minimum bending moments and shear forces by trial-and-error methods as per IS 456-2000. The help is taken by software available in institute and the computations of loads, moments and shear forces and obtained from this software.

DOI: 10.61137/ijsret.vol.11.issue2.307

Published by: Kajal Tripathi

Air Pollution Detection Using MQ135 and ESP3266
Authors:-Assistant Professor Mrs. Anuja S. Phapale, Om Mahajan, Vedant Mahanavar, Kiran Mangde, Pranav Patil

Abstract-Air pollution is a serious environmental and health problem worsened by an increase in industrialization and urban sprawl. Real-time air quality monitoring is critical for understanding access to pollution and minimizing risks. This paper presents a low-priced portable air quality monitoring and measuring system based on MQ135 gas sensor and ESP8266 microcontroller. The system is made to detect key pollutants, such as carbon monoxide, carbon monoxide (CO), carbon dioxide (CO2), ammonia (NH3), benzene, and other volatile organic compounds (VOCs). The readings, which will ensure accurate readings from the developed system at any point in time in the future The proposed developed system has many features, including low power consumption, wireless communication, and real- time data acquisition, which make it suitable for mobile and remote applications.. MQ135 ensures accurate detection of pollutants and the sensor is linked with the ESP8266-12E module, which transfers data to the cloud for further processing. A specialized software component parses the collected data to interpret air quality trends for the users and estimate their health impact. This low-cost and easy- to-use system individual and community- level air quality monitoring. Its portability and real-time data provide another useful tool for researchers, environmental agencies, and policymakers. The experimental results demonstrate that the system successfully covers the fluctuations in pollution. Future improvements could include the incorporation of artificial intelligence methods for enhanced prediction and a wider air quality analysis spectrum.

DOI: 10.61137/ijsret.vol.11.issue2.306

Published by: Kajal Tripathi

Big Data Analytics for Real-Time Fraud Detection in Insurance Claims
Authors:-Shaba Khatoon , Asst.Prof. Ankita Srivastava, Prof.Shish Ahmad

Abstract-The integration of Artificial Intelligence (AI) and Big Data Analytics is revolutionizing industries by optimizing efficiency, accuracy, and security. In healthcare and insurance, AIdriven Intelligent Document Processing (IDP) automates workflows such as claims automation, medical data extraction, and regulatory compliance management. By utilizing Machine Learning (ML), Natural Language Processing (NLP), and Optical Character Recognition (OCR), IDP accelerates document classification, data validation, and anomaly detection, reducing errors by 90% and cutting processing time by 80%. In the financial sector, AI enhances fraud analytics, risk modeling, and compliance monitoring. Advanced deep learning architectures, pattern recognition, and predictive analytics improve credit risk assessment and real-time fraud mitigation. AI-powered anomaly detection techniques identify suspicious transactions, reducing cybersecurity threats and financial fraud losses.

DOI: 10.61137/ijsret.vol.11.issue2.305

Published by: Kajal Tripathi

Urban Flood Hazard Assessment: Harnessing Ensemble Machine Learning for Next-Generation Risk Analytics
Authors:-Mrs.T.Sankaramma, Ch.Mahesh, M.Venkata Sai Harshith, Shaik Saad, V.Venkata Sai Sanjay, Shaik Mohammad Ashiq Ilahi

Abstract-Urban flood hazard assessment through an ensemble machine learning approach minimizes the bias of individual models and offers a more detailed insight into the evolution of flood risks over time. By integrating diverse models, this approach increases the precision of flood event predictions. In this research, we utilized an ensemble machine learning framework to analyse flood hazards. The results reveal that the ensemble model outperforms conventional methods, such as the classification and regression tree (CART) and random forest (RF). The generated hazard maps confirm the accuracy of the data, facilitating public awareness and pinpointing regions vulnerable to flooding.

DOI: 10.61137/ijsret.vol.11.issue2.304

Published by: Kajal Tripathi

AI-Powered Mental Health Insights: A Comprehensive Review of Machine Learning & Deep Learning Approaches for Social Media Analysis
Authors:-Mrs.R.Veera Meenakshi, B.Vanitha Sri, V.N.V.Karthikeya, P.G.Pranava, K.Uday Meher, A.Sreeja

Abstract-Artificial intelligence is revolutionizing healthcare, particularly in the prediction and diagnosis of various diseases through machine learning (ML) and deep learning (DL) algorithms. With the widespread use of social media platforms like Twitter, Facebook, and Reddit, individuals frequently express their thoughts and emotions online. Mental health has emerged as a significant concern, especially following the COVID-19 pandemic, prompting researchers to leverage ML and DL techniques to analyse social media data for mental health prediction. This study offers a comprehensive review of ML and DL algorithms applied to the prediction of mental disorders, based on an analysis of 37 selected research papers. It presents a comparative accuracy table of ML and DL models for four key mental disorders: Depression, Anxiety, Bipolar Disorder, and ADHD. The findings aim to provide a foundational reference for researchers and practitioners, assisting in future advancements in this field. Additionally, this study compiles a list of publicly available datasets, serving as a valuable resource for further research in mental health analysis using artificial intelligence.

DOI: 10.61137/ijsret.vol.11.issue2.303

Published by: Kajal Tripathi

AI-Driven Global Solar Radiation Prediction: Harnessing Machine Learning and Satellite Imagery for Accurate Forecasting
Authors:-Mrs.A.Srujana Jyothi, M.Siri Sathvika, M.Madhur, I.Chathurya, G.Ram Subhash, K.V.K.Varma

Abstract-Accurate prediction of Daily Global Solar Radiation (DGSR) is crucial for applications in renewable energy, agriculture, and climate studies. This paper explores the effectiveness of Machine Learning (ML) algorithms and satellite imagery in enhancing DGSR prediction accuracy. Traditional ML models typically rely on various meteorological parameters (e.g., temperature, wind speed, atmospheric pressure, and sunshine duration) and radiometric parameters (e.g., aerosol optical thickness, water vapour). In this study, we investigate the impact of incorporating normalized reflectance from satellite images across different spectral channels to improve prediction accuracy. We employ two ML-based regression models: Artificial Neural Networks (ANN) and Support Vector Machines (SVM). The results indicate that the selection of input parameters significantly affects the accuracy of daily solar radiation forecasts. Moreover, the ANN model outperforms SVM, demonstrating superior predictive capability.

DOI: 10.61137/ijsret.vol.11.issue2.302

Published by: Kajal Tripathi

Android Flight Price Prediction Web-Based Platform: Leveraging Generating AI for Real-Time Airfare Forecasting
Authors:-Mrs. M. Mani Deepika, P. Nasivi Ramya Anjani, V. Sai Jyothika Chowdary, Y. Anitha Chowdary, M. Swarna, K.Vamsika

Abstract-The aviation industry faces significant challenges in accurately and swiftly predicting flight fares due to the sector’s dynamic nature. Factors such as fluctuating demand, fuel prices, and route complexities contribute to this unpredictability. To address these issues, this research introduces a novel approach leveraging generative artificial intelligence (GAI) to forecast airfares in real time with high precision. The proposed framework integrates generative models, deep learning architectures, and historical pricing data to enhance predictive accuracy. Utilizing GAI within an advanced web engineering framework, this method effectively captures intricate patterns and relationships within historical airline data. By employing deep neural networks, the model efficiently processes diverse scenarios, extracting critical insights to improve the understanding of key factors influencing flight costs. Furthermore, the approach prioritizes real-time forecasting, enabling rapid adaptation to market fluctuations and providing valuable insights for dynamic pricing strategies.

DOI: 10.61137/ijsret.vol.11.issue2.301

Published by: Kajal Tripathi