Publications — Gudsky Research Foundation

Abstract: This paper focuses on tracking students' academic progress and learning outcomes in real-time across schools. The research introduces a desktop-based Learning Management System (LMS) integrated with machine learning (ML) algorithms. The LMS supports various tasks, including attendance tracking, assignment and quiz preparation, subject-specific mark analysis, and automated notifications for teachers and parents. By automating routine activities, the system reduces manual workload for both students and teachers, enhancing overall efficiency.

Abstract: This research paper presents the design and implementation of an AI surveillance car capable of object detection, line following, and live streaming. Leveraging Internet of Things (IoT) technology, the car can be remotely controlled and monitored. Key features include real-time object detection for tracking surrounding objects, line following for navigating predefined paths, and live streaming for remote camera access. Experimental results demonstrate accurate obstacle detection, reliable line following, and high-quality live streaming. The study offers a comprehensive and practical approach to developing AI surveillance vehicles using IoT.

Abstract: This research presents an IoT-based irrigation method designed to transform agricultural practices. The Internet of Things (IoT) is revolutionizing the agriculture industry by addressing significant challenges faced by farmers. Our paper reviews existing IoT-based applications in agriculture and introduces a user-friendly irrigation system utilizing Arduino UNO, a Bluetooth module, and a soil-moisture sensor. Unlike previous complex systems, our solution emphasizes simplicity and ease of use for farmers. The system enables real-time monitoring of soil moisture and allows farmers to set customized moisture thresholds for different crops. When soil moisture drops below the set threshold, the system automatically activates irrigation, helping to prevent both overwatering and underwatering, thereby improving agricultural efficiency.

Abstract: This book explores the pivotal role of interference mitigation in cellular vehicle-to-everything (CV2X) communications, a key technology for modern transportation systems. It examines the sources, types, and impacts of interference on CV2X performance, and provides a comprehensive analysis of current mitigation techniques, including spectrum sharing, radio resource management, interference cancellation, and traffic management. The book also addresses legislative and standardization challenges, and discusses technical difficulties and opportunities in minimizing interference, especially in high-density and heterogeneous networks. By delving into these complexities, the book offers valuable insights for advancing CV2X communications and their applications in transportation.

Abstract: This study investigates inventory turnover performance in a Delhi-based retail supermarket, analyzing both food and non-food product categories. It compares periodic and perpetual inventory systems, ultimately employing a hybrid method based on available data. The research utilized secondary data and qualitative methods to explore inventory tracking, transaction recording, and cost-of-goods calculations, offering insights into inventory system selection for resource-constrained firms.

Summary: Our project presents a Voice-Controlled Car prototype aimed at filling the gap in systematic evaluations of voice-controlled systems. The prototype utilizes Natural Language Processing (NLP) techniques, and an Arduino UNO interfaced Bluetooth module for wireless communication with the "AMR Voice Control" Android app. Through algorithmic processes, the system extracts and executes multiple voice commands sequentially. Extensive testing with multiple phrases demonstrates strong performance in the Bluetooth range (8.5–12 meters) and response accuracy. The prototype is capable of extracting commands like forward, backward, stop, left and right form sentences. It follows all these commands one-by-one in a sequence. Additional features include live streaming via an ESP32-CAM module and obstacle recognition using an ultrasonic sensor, enhancing its practicality in real-world scenarios. This project offers an effective and practical voice-activated solution for HMI applications, prioritizing usability and practicality.

Abstract: This research introduces a Voice-Controlled Car prototype that addresses the existing literature gap in systematic evaluations of voice-controlled systems. The prototype employs Natural Language Processing (NLP) techniques and an Arduino UNO-interfaced Bluetooth module to facilitate wireless communication with a dedicated Android app, “AMR Voice Control.” Through an algorithmic process, the system extracts and executes multiple voice commands sequentially. Strong performance in terms of Bluetooth range (8.5–12 m). The effectiveness of the technique is demonstrated by the short processing times (2–7 ms) for command extraction and execution times ranging from 8.95 to 21.08 s. The prototype was tested with 50 statements and demonstrated solid performance. The average execution time for six commands takes 20.11 s. The prototype has extra features like live streaming via an ESP32-CAM module and obstacle recognition using an ultrasonic sensor to increase its usefulness in real-world scenarios. Performance study uses Python and data visualization tools to visualize the relationship between execution time and the number of instructions, which offers valuable insights for future voice-controlled system optimizations.

Abstract: This research presents a prototype software solution designed to streamline and secure the Indian Railways' ticketing process, particularly for general class passengers. The study highlights the inefficiencies in existing systems, including the absence of proper tracking for local travelers. The proposed model integrates facial recognition technology to manage queues in offline booking areas and employs automation to replace manual operations. The system ensures accurate passenger identification and booking, enhancing both user experience and railway safety protocols.

Abstract: This research paper addresses a significant literature gap in healthcare monitoring systems by proposing a novel methodology that integrates weight monitoring into an Internet of Things (IoT)-based framework. In the era of technological advancement, IoT serves as a powerful tool for obtaining health-related data remotely. While existing studies have explored various IoT applications, including connected cars and automated residences, the crucial parameter of patient weight has been overlooked in current healthcare monitoring systems. The proposed methodology leverages the ESP8266 module for Wi-Fi connectivity, facilitating seamless data transmission and remote monitoring capabilities. Key IoT applications such as oxygen sensors, heart rate sensors, ECG modules, and temperature sensors are already established in healthcare systems, but the incorporation of a weight sensor is essential for a holistic understanding of a patient's overall health. Regular monitoring of weight provides valuable insights, enabling healthcare providers to make informed decisions. Through the integration of a weight sensor, this research enhances the capabilities of healthcare providers, allowing them to remotely access accurate and real-time weight measurements alongside other vital signs. This comprehensive approach empowers healthcare professionals to deliver more effective care, especially in remote settings where regular patient visits may be challenging.

Abstract: Railway stations often face critical safety challenges, especially at track and platform edges during high-traffic hours. This study proposes an IoT-based alert system aimed at enhancing safety and communication for railway track maintenance workers. The system addresses common issues like insufficient training, poor communication between station masters and field workers, and high-risk exposure to active tracks. By detecting track vibrations and notifying supervisors in real-time, the device significantly lowers the risk of accidents. The paper details the design, testing, and real-world applicability of this IoT solution in India’s extensive railway network. The proposed method achieved its objectives and demonstrated the potential to reduce worker casualties and improve on-site awareness and response times.