Book Store

Authors: C.K.Sukanya, V.Priyadharshini

 

 

Abstract: As the world becomes increasingly digital, the concept of the traditional bookstore is evolving rapidly. This paper explores how emerging technologies can transform the bookstore experience in the near future. From augmented reality (AR) and artificial intelligence (AI) to smart shelves and personalized recommendation systems, technology is set to redefine how readers discover, interact with, and purchase books. Future bookstores may become hybrid spaces—part library, part community hub, part digital experience center—offering immersive storytelling through AR, voice-guided book previews, and AI-powered reading assistants. This presentation highlights key innovations and envisions a future where bookstores blend physical charm with digital convenience, enhancing accessibility, engagement, and reader satisfaction.

 

 

Published by: vikaspatanker

Development of a smart Wearable System for Monitoring Student Attendance and Activity Participation through ID Scanning
Authors:-Amuncio, Jun Rey, Crisostomo, Kenneth, Gatinao, Hannah Michaela G, Palomo, Gerber Jay L, Paculanan, Kristian Jay C, Cedie E. Gabriel , Reginald S. Prudente

Abstract-:The study presents the development and evaluation of a smart wearable system to monitor student appearance and activity participation through ID scanning at South East Asian Institute of Technology (SEAIT), Tupi, South Kotabato. Methods of traditional appearance in educational institutions are often disabled, error-prone and susceptible to manipulation. The project integrates human-computer interaction (HCI) principles into a smart wearable device that uses ID scanning to automate the attendance and recording of student participation. The system aims to improve accuracy, reduce administrative burden, and increase the user experience through user -friendly interfaces and real -time data processing. The purposeful test and performance assessment demonstrated that the system provides more efficiency and satisfaction than traditional methods, although some users expressed concern over the need for privacy and additional support. Overall, the system shows strong ability to increase institutional operations in the resource-limit environment.

DOI: 10.61137/ijsret.vol.11.issue3.110

Published by: Kajal Tripathi

Bridging the Digital Divide: How Camstar Mes Is Revolutionizing Modern Manufacturing
Authors:-Satish Kumar Nalluri, Varun Teja Bathini

Abstract-:In today’s factories, machines and software don’t always talk to each other smoothly. Workers still juggle spreadsheets, punch in data by hand, and chase down errors—tasks that eat up time and open the door for mistakes. But what if the factory could almost run itself? This research explores how two powerful technologies—Camstar MES (a brain for manufacturing operations) and RPA (software “robots” that mimic human clicks and keystrokes)—team up to close those gaps. Imagine Camstar as the vigilant supervisor, tracking every widget on the assembly line in real time, while RPA bots quietly handle the tedious paperwork: updating inventory, logging defects, or even pinging a manager when a machine acts up. Together, they turn clunky, error-prone workflows into a seamless dance of data.

DOI: 10.61137/ijsret.vol.11.issue3.109

Published by: Kajal Tripathi

Understanding Streaming Success Through Spotify Analytics
Authors:-Satish Kumar Nalluri, Varun Teja Bathini

Abstract-:In today’s factories, machines and software don’t always talk to each other smoothly. Workers still juggle spreadsheets, punch in data by hand, and chase down errors—tasks that eat up time and open the door for mistakes. But what if the factory could almost run itself? This research explores how two powerful technologies—Camstar MES (a brain for manufacturing operations) and RPA (software “robots” that mimic human clicks and keystrokes)—team up to close those gaps. Imagine Camstar as the vigilant supervisor, tracking every widget on the assembly line in real time, while RPA bots quietly handle the tedious paperwork: updating inventory, logging defects, or even pinging a manager when a machine acts up. Together, they turn clunky, error-prone workflows into a seamless dance of data.

DOI: 10.61137/ijsret.vol.11.issue3.108

Published by: Kajal Tripathi

Understanding Streaming Success Through Spotify Analytics

Authors: Ure Sanath Kumar, Borkar Srikanth, Erukonda Mohan Manoj, Dr. Diana Moses

 

 

Abstract: The Top Spotify Songs in 73 Countries dataset provides a dynamic overview of global music trends by tracking the most popular songs across 73 countries daily. It includes key attributes such as song rank, track name, artist name, country, stream count, and ranking date, allowing for in-depth analysis of song popularity. Additionally, it contains song characteristics like danceability, energy, loudness, and valence, offering insights into musical trends and listener preferences. This dataset is particularly useful for music analysts, data scientists, and researchers aiming to explore streaming patterns, predict music trends, and analyze regional differences in music consumption. It can be leveraged for data visualization, trend analysis, machine learning models, and recommendation systems. Furthermore, businesses in the music industry can utilize this dataset to gain insights into audience preferences and optimize marketing strategies.

 

 

 

Published by: vikaspatanker