| 1 |
Author(s):
Sashya Vinodha P.
Page No : 1-2
|
Development of a Multi-Module AI Infotainment System for Real-Time Assistance and Control
Abstract
This paper presents the development of an intelligent multi-module infotainment system designed to enhance vehicle safety and driver experience through real-time data integration. By synthesizing inputs from diverse sources—including localized weather data, GPS coordinates, and simulated driving behavior—the system provides proactive features such as smart maintenance notifications, real-time driver coaching, and automated emergency response protocols. Unlike standard infotainment units, this framework utilizes predictive analytics and natural language processing to offer tailored feedback and ensure swift communication with emergency contacts during critical events. The proposed system addresses current market gaps in personalized driver assistance and demonstrates a scalable architecture for future AI-driven automotive technologies.
| 2 |
Author(s):
Pratishtha Srivastava.
Page No : 1-3
|
Smart Glasses for Safety and Hazard Awareness: A Review of Context-Aware Assistive Systems in Safety-Critical Environments
Abstract
Global estimates indicate that approximately 285 million individuals live with visual impairments, confronting severe barriers to independent mobility in complex urban environments [1]. This navigation gap is most pronounced in high-traffic transit hubs; the Indian Railway system, for instance, manages over 23 million daily passengers [12] and an annual volume exceeding 8.6 billion [12], yet its navigational infrastructure remains largely inaccessible to the visually impaired. This paper provides a systematic review of the field, employing the PRISMA methodology to synthesize findings from 60 relevant articles published between 2015 and 2025 [2]. Our primary objective is to define the technical and design requirements necessary to bridge the "Information-Safety Gap" in safety-critical hubs. By shifting from basic "Assisted Seeing" to a paradigm of "Managed Reaction," we evaluate how Augmented Reality (AR) smart glasses—integrated with context-aware sensors and conversational User Experience (UX)—can transform hazardous environments into navigable spaces.
| 3 |
Author(s):
samiksha Jadhav.
Page No : 1-3
|
AI-Powered Web Application for Student Placement Prediction
Abstract
Campus placement prediction plays a crucial role in enhancing student career opportunities and institutional performance. This paper presents a Smart Placement Prediction System that leverages Machine Learning techniques to predict student employability outcomes. The system utilizes Logistic Regression to classify students based on academic performance, technical skills, and extracurricular activities. A full-stack web application is developed with role-based access for students, administrators, and recruiters. The dataset is preprocessed and used to train the model, achieving high prediction accuracy. The system provides insights into key placement factors and helps institutions take proactive measures to improve placement rates. The results demonstrate the effectiveness of machine learning in automating and improving the placement prediction process..
| 4 |
Author(s):
Bharath .
Page No : 1-3
|
UNITEX HYDROLIC MECHINE COMPANY
Abstract
ABSTRACT
To really get how a company works, you have to go
behind the scenes—see how teams work together,
watch the processes unfold, and figure out what drives
performance. I spent two months inside Unitek Hydraulic
Machine Company, a small manufacturer in Coimbatore,
Tamil Nadu, to do just that. My main aim was to break
down Unitek’s structure, trace how their machines
actually get built, check out how they handle quality, and
use SWOT to see where they stand. I talked to
employees, spent hours watching the workflow, and
studied everything from internal documents to testing
records. What’d I find? Unitek has real technical strength
and keeps customers happy. Still, they struggle with high production costs, are slow to adopt automation,
and nobody knows them outside India. There's big
potential if they target exports and start building smart
hydraulic systems. At the heart of it all, Unitek’s clear
structure and focus on quality keeps them steady and
their customers loyal. My top suggestions: get serious
about ERP software, improve digital marketing, and
invest in training.
| 5 |
Author(s):
Boopesh S, Vetri Prabhu T .
Page No : 1-4
|
A LEVEL OF STUDY ON MULTIMODAL TRANSPORTATION
Abstract
The logistics industry plays a crucial role in economic growth and business operations
by ensuring efficient movement of goods and services. The internship at Allcargo Gati
Limited, Chennai provided practical exposure to logistics operations, supply chain
management, and digital logistics systems.
This study focuses on understanding operational workflow, express distribution
services, departmental functions, digital transformation, and strategic positioning of
Allcargo Gati in the logistics industry. The report also evaluates strengths, weaknesses,
opportunities, and challenges faced by the company.
The logistics sector is evolving rapidly with technological advancements such as ERP
systems, cloud computing, real-time tracking, and automation. Allcargo Gati has
adopted digital logistics systems and integrated supply chain solutions to improve
efficiency and customer satisfaction.
The internship helped in gaining knowledge about shipment handling, sorting, tracking
systems, customer service, and warehouse operations. The study concludes with
findings and suggestions to enhance operational efficiency and service quality.
| 6 |
Author(s):
Prof. S. H. Choudhari, Mr. Dipak P. Patil, Mr. Durgesh S. Patil, Mr. Nadim N. Tadavi, Mr. Saurabh O. Devare, Mr. C. D. Patil.
Page No : 1-4
|
A Review on Automatic Railway Gate System
Abstract
Railway safety is a critical concern in transportation systems, especially at unmanned or partially controlled level crossings where accidents frequently occur due to human error or lack of proper signaling. To address this issue, a Solar Powered Automatic Railway Gate System is proposed to enhance safety, reduce manual intervention, and ensure energy-efficient operation. This system automatically controls the opening and closing of railway gates based on train detection using sensors, thereby preventing collisions between trains and road vehicles. The proposed system integrates solar energy as a renewable power source, making it sustainable and suitable for remote areas where electricity supply is unreliable. A combination of microcontroller-based control unit, infrared (IR) sensors or ultrasonic sensors, and motor-driven gate mechanisms is used to detect the approaching train and operate the gate accordingly. When a train is detected within a predefined range, the system triggers the gate to close automatically and activates warning signals such as buzzers and LED indicators for road users. After the train passes, the gate reopens safely.
| 7 |
Author(s):
SUNIL KUMAR.P.
Page No : 1-5
|
Digital Marketing Strategies for Small Businesses
Abstract
Digital marketing has transformed the way small businesses operate and grow in the
modern economy. This study aims to examine various digital marketing strategies and
analyze their impact on small business growth. The research adopts a descriptive
methodology using secondary data collected from journals, websites, and industry
reports. Key strategies analyzed include social media marketing, search engine
optimization (SEO), email marketing, and content marketing. The findings reveal that
digital marketing significantly enhances brand visibility, customer engagement, and
revenue generation for small businesses. Social media platforms are identified as the
most effective tools due to their wide reach and cost efficiency. However, lack of
technical knowledge and limited resources remain key challenges. The study concludes
that adopting well-planned digital marketing strategies can lead to sustainable growth
and competitive advantage for small businesses.
| 8 |
Author(s):
Karthika K.
Page No : 1-5
|
ROLE OF CONTENT MARKETING IN SHAPING USER BUYING BEHAVIOUR
Abstract
Content marketing has emerged as a powerful strategic tool that significantly influences user buying behaviour in the modern digital marketplace. Unlike traditional promotional methods, content marketing focuses on creating and distributing valuable, relevant, and consistent content to attract and engage a clearly defined audience. This approach helps consumers move through different stages of the buying decision process by increasing brand awareness, shaping perception, building trust, and encouraging long-term relationships. Informative and engaging content such as blogs, videos, social media posts, reviews, and storytelling enables consumers to evaluate alternatives, reduce perceived risk, and make informed purchase decision. Additionally, personalized and interactive content enhances user engagement and emotional connection with brand, further impacting purchase intentions and brand loyalty. This abstract highlights how content marketing influence consumer attitudes, preference, and decision-making patterns, emphasizing its role in shaping buying behaviour in a highly competitive and information-rich environment.
| 9 |
Author(s):
V. Nanthini.
Page No : 1-5
|
Impect of social media marketing on consumer buying behavior
Abstract
ABSTRACT
Platforms such as Facebook, Instagram, and YouTube allow companies to reach
a large number of consumers quickly and effectively. This study focuses on the
impact of social media marketing on consumer buying behaviour. Social media
advertisements, influencer promotions, product reviews, and online interactions
play a major role in influencing the purchasing decisions of consumers. Many
consumers rely on social media platforms to gather information about products,
compare brands, and read customer reviews before making a purchase. The
study also highlights how social media creates awareness, builds brand loyalty,
and increases customer engagement. Overall, social media marketing has a
significant influence on consumer behaviour and helps businesses improve their
marketing strategies and sales performan
| 10 |
Author(s):
Raman Singh.
Page No : 1-5
|
Multi-Purpose Amphibious UGV.
Abstract
This electronic document details the design methodology and fabrication process for a small-scale Unmanned Ground Vehicle (UGV) engineered for high resilience and robust remote operation in challenging, potentially amphibious environments. The platform integrates the Ai-Thinker ESP32-CAM System-on-Chip (SoC) to provide real-time, high-resolution visual feedback and Wi-Fi based remote control. Actuation is achieved using high-torque MG996R servo motors and L293D-controlled drive motors, managed using the Arduino environment. Crucially, the chassis utilizes Additive Manufacturing (AM), focusing on a water-resistant hull design and flexible wheels printed in Thermoplastic Polyurethane (TPU 95A). The material analysis shows the TPU offers exceptional elongation (>560%) and good chemical resistance, key factors for amphibious endurance and operational durability.
Key Words: Unmanned Ground Vehicle, ESP32-CAM, TPU 95A, Additive Manufacturing, MG996R, Remote Control.
| 11 |
Author(s):
D Girija.
Page No : 1-5
|
THE EFFECT OF LEADERSHIP STYLE ON EMPLOYEE SATISFACTION
Abstract
ABSTRACT :
Leadership style plays a crucial role in shaping employee attitudes, motivation, and overall job satisfaction within an organization. This study examines the effect of different leadership styles such as transformational, transactional, autocratic, and democratic leadership on employee satisfaction levels. Effective leadership influences communication, employee engagement, trust, and workplace culture, which directly impact how employees perceive their jobs and organizational environment The research analyses how leaders’ behaviours, decision-making approaches, and interpersonal relationships affect employee morale, commitment, and productivity. Data collected through surveys and questionnaires help identify which leadership styles contribute positively to employee satisfaction and which may lead to dissatisfaction, stress, or higher turnover intentions. The study also considers factors such as organizational structure, work environment, and employee demographics.
KEYWORDS: Online Advertising, Consumer Buying Behaviour, Consumer Perception, Influencer Marketing, Customer Engagement, commerce Behaviour
| 12 |
Author(s):
M.Janani.
Page No : 1-5
|
ROLE OF CONTENT MARKETING IN SHIPPING USER BUYING BEHAVIOUR
Abstract
ABSTRACT:
In the modern digital landscape, content marketing has become a critical tool for influencing consumer buying behaviour. The primary objective is to understand how different forms of content such as blogs, videos, social media posts, and influencer marketing affect consumer engagement and buying intentions. The research adopts a descriptive methodology and relies on secondary data sources including academic journals, industry reports, and online articles. The findings reveal that high-quality, informative, and engaging content significantly impacts consumer awareness and trust. Video content and influencer marketing are found to be particularly effective in influencing purchasing decisions due to their visual appeal and credibility. Furthermore, consistent and personalized content enhances customer loyalty and long-term relationships. The study concludes that businesses must strategically utilize content marketing to stay competitive in the digital age. Overall, content marketing not only drives immediate sales but also builds strong brand equity over time.
KEYWORDS: Content Marketing, Consumer Buying Behaviour, Digital Marketing, Customer Engagement, Brand Awareness, Influencer Marketing
| 13 |
Author(s):
R.Rithika mary.
Page No : 1-5
|
A STUDY ON CUSTOMER SATISFACTION TOWARDS GAIN GARMENTS
Abstract
ABSTRACT
Customer satisfaction is a key factor that determines the success and growth of any business
organization, especially in the garment industry where competition is intense and customer
preferences change frequently. The present study titled “A Study on Customer Satisfaction
towards Gain Garments” focuses on analysing the level of satisfaction among customers
with respect to the products and services offered by the company.
The main objective of the study is to evaluate customer satisfaction and identify the factors
influencing their perception towards Gain Garments. The study examines various aspects such
as product quality, pricing, design, timely delivery, and customer service. Understanding
these factors helps the company to improve its performance and meet customer expectations
effectively.
The research is based on a descriptive research design. Primary data has been collected
through a structured questionnaire from a sample of 100 customers using random sampling
method. Secondary data has been gathered from books, journals, and online sources. The
collected data has been analysed using simple statistical tools such as percentage analysis and
graphical representation.The findings of the study reveal that most customers are satisfied with the quality of garments
and timely delivery provided by Gain Garments. The study also indicates that customer
satisfaction plays an important role in building loyalty and encouraging repeat purchases.
In conclusion, the study highlights that maintaining high product quality, improving service
efficiency, and understanding customer needs are essential for enhancing customer
satisfaction. By focusing on these aspects, Gain Garments can strengthen its market position
and achieve long-term success in the competitive garment industry.
| 14 |
Author(s):
Sinchana M C.
Page No : 1-5
|
The Sustainable Aquqrium: Powered IoT Solution for Effortless Fish care.
Abstract
Abstract—The paper presents a smart and compact aquatic system that combines IoT sensors, machine learning, and image processing to automate and optimize aquarium maintenance. The system continuously monitors key water parameters such as turbidity, temperature, conductivity, pH and water level, using sensors interfaced with an STM32 microcontroller. A machine learning model analyzes this data to predict water quality in real time, while a CNN-based image processing module detects fish breed such as Bala Shark, Bristenose Pieco ,Clown Loach, Freshwater Angelfish, Neon Tetra, Silver Dollar and Swordtail and fish diseases from captured images. Additionally, the system features automated fish feeding and water level monitoring for improved care and efficiency. Designed for ease of use, the portable setup is ideal for homes, educational institutions and research environments, offering a realiable and intelligent solution for fish keeping with manual effort.
Index Terms—Sustainable Aquarium, IoT, Water Quality Prediction, Solar Panel Fish Breed Detection, Fish Disease Detection, Machine Learning, CNN, STM32,Automation.
| 15 |
Author(s):
Deepanshu Singh.
Page No : 1-7
|
Energy Consumption Using LSTM
Abstract
The global transition toward carbon neutrality
and the integration of intermittent renewable energy sources
have necessitated unprecedented sub-hourly forecasting precision
within Smart Grid environments. Given that building energy
consumption accounts for nearly 40per of global total energy
use and 33per of greenhouse gas emissions, predicting volatile
load patterns is fundamental for demand-side management and
grid stability. This paper presents a rigorous, multi-layered
investigation into hybrid Long Short-Term Memory (LSTM)
networks for multivariate time-series modeling. Unlike traditional
stochastic models such as ARIMA, which assume stationarity and
linearity, our proposed framework captures the non-linear, multi-
seasonal nature of electricity demand by integrating Discrete
Wavelet Decomposition for multiresolution feature extraction. To
address the ”vanishing gradient” problem and improve long-
term sequence stabilization, we implement a ”Teacher Forcing”
training strategy, utilizing ground-truth outputs to prevent error
accumulation. Furthermore, we propose a hybrid architecture
that leverages Support Vector Regression (SVR) for residual re-
finement and Deep Extreme Machine Learning (DELM) for rapid
sequence learning. All model hyperparameters were tuned using
the Developed Henry Gas Solubility Optimization (DHGSO) algo-
rithm to ensure structural robustness. Experimental validation
was conducted using the London Smart Meter dataset and a
two-year multi-campus university dataset. Results highlight a
(15–20)per improvement in Root Mean Square Error (RMSE)
and significant reductions in Mean Absolute Error (MAE)
compared to standalone LSTM and MLP models. Finally, we
employ Layer-wise Relevance Propagation (LRP) to enhance
model interpretability, identifying critical 24-hour and 168-hour
temporal lags. This study provides a robust solution for utility
providers seeking to minimize operational risks through precise,
high-fidelity demand prediction.
| 16 |
Author(s):
Vasu Pandey.
Page No : 1-7
|
TeeVision: Customize and Buy your Fits
Abstract
This project presents an interactive web-based platform that allows users to customize clothing in real time before making a purchase. The application is developed using modern frontend technologies such as JavaScript and React.js, along with tools like Three.js and Framer Motion to enhance visual interaction and user experience. Users can personalize outfits by adding text, uploading images, and modifying colors, with instant preview of changes. The system focuses on improving user engagement and providing a more flexible online shopping experience. Overall, the project demonstrates how modern web technologies can be effectively used to build dynamic, responsive, and user-friendly e-commerce applications.
| 17 |
Author(s):
Dr. Chitranka k .
Page No : 1-8
|
E-Triggering Effect: How E Commerce advertisements trigger the problem recognition in consumer buying behaviour.
Abstract
This study investigates the E‑Triggering Effect, defined as the process by which e‑commerce advertisements activate problem recognition in consumer buying behaviour. Problem recognition is the first and most critical stage of the Engel‑Kollat‑Blackwell model, yet it has received limited empirical attention compared to later stages such as purchase intention or brand attitude. The research addresses four specific gaps: the direct effect of e‑commerce ads on problem recognition, the role of personalisation, the influence of scarcity cues, and the moderating effect of product involvement. A quantitative, causal‑explanatory design was adopted using two between‑subjects experiments. Experiment 1 employed a 2 (personalisation: personalised vs. generic) × 2 (scarcity: present vs. absent) design with 120 participants. Experiment 2 employed a 2 (product involvement: low vs. high) × 2 (ad type: e‑commerce ad vs. no ad control) design with another 120 participants. Problem recognition was measured using a validated 7‑point Likert scale. Independent samples t‑tests and two‑way ANOVA were used for analysis. The results supported all four hypotheses. E‑commerce advertisements significantly increased problem recognition compared to no ad exposure (t(118) = 9.97, p < 0.001). Personalised ads triggered stronger problem recognition than generic ads (t(118) = 7.08, p < 0.001). Ads containing scarcity cues produced higher problem recognition than those without scarcity cues (t(118) = 4.51, p < 0.001). A significant interaction effect (F(1,116) = 12.7, p < 0.001) revealed that the triggering effect of ads was stronger for low‑involvement products than for high‑involvement products. These findings confirm that e‑commerce advertisements effectively trigger problem recognition, and that personalisation, scarcity cues, and product involvement significantly moderate that effect. The study provides actionable insights for digital marketers seeking to design ads that initiate consumer decision‑making at the earliest possible stage.
| 18 |
Author(s):
Malaika Matheen Khan, Dr. Sadiya Nair.
Page No : 1-9
|
Passive Vs Active Social Media Use and it’s Impact on Self-Esteem
Abstract
This study investigated the relationship between self-esteem and active/passive usage patterns of social media in 56 participants (18-30). Average levels of usage for both active and passive usage were identified to be moderate overall, and slightly higher for passive usage. No statistically significant relationships between levels of usage and levels of self-esteem were found. While males utilized passive usage more, and females actively utilised more, older adults aged 26-30 expressed the highest self-esteem levels and the lowest usage, indicating the potential for life stage/age to be a greater factor than usage levels alone.
| 19 |
Author(s):
Ayushi Singh.
Page No : 1-14
|
Cognitive Alignment in Multi-Agent Generative AI Systems: A Framework for Trustworthy Collaborative Intelligence
Abstract
The rapid evolution of generative artificial intelligence (AI) has led to the emergence of multi-agent systems capable of autonomous reasoning, collaboration, and decision-making. However, ensuring alignment among multiple AI agents and human intent remains a critical challenge. This paper introduces a novel concept termed Cognitive Alignment in Multi-Agent Generative Systems (CAMAGS), focusing on how multiple AI agents can maintain consistent reasoning, ethical alignment, and cooperative behavior. We propose a hybrid framework combining neuro-symbolic reasoning, alignment constraints, and self-reflective feedback loops. The study evaluates emerging risks such as hallucination propagation, agent conflict, and ethical drift. Results suggest that cognitive alignment mechanisms significantly improve trust, reliability, and scalability in collaborative AI ecosystems.
Keywords: Artificial Intelligence, Multi-Agent Systems, Alignment, Generative AI, Trustworthy AI, Neuro-symbolic AI
| 20 |
Author(s):
Parupalli sirisha.
Page No : 1-28
|
A STUDY ON EMLOYEES SATISFACTION AT RATTA AVANEE PVT LITS
Abstract
The rapid growth of social media platforms has significantly transformed the way businesses
communicate with consumers, making social media marketing a critical component of
modern marketing strategies. This study examines the impact of social media marketing on
customer purchase intention by analysing key factors such as content quality, interactivity,
trust, brand engagement, and electronic word-of-mouth. Using data collected from consumers
active on social media platforms, the research employs quantitative analysis to assess the
relationship between social media marketing activities and consumers’ willingness to
purchase. The findings indicate that social media marketing has a positive and significant
influence on customer purchase intention, with interactive content and perceived credibility
playing a particularly strong role. These results provide valuable insights for marketers
seeking to enhance customer purchase intention through effective social media marketing
practices.
