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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Applied Power Engineering (IJAPE) Bulletin of Electrical Engineering and Informatics Journal of Robotics and Control (JRC)
Reddy, Ch. Rami
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Injury Prediction in Sports using Artificial Intelligence Applications: A Brief Review Kumar, G. Syam; Kumar, M. Dilip; Reddy, Sareddy Venkata Rami; Kumari, B. V. Seshu; Reddy, Ch. Rami
Journal of Robotics and Control (JRC) Vol 5, No 1 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i1.20814

Abstract

Avoiding injuries in sports has always depended on historical records and human experience. This is despite using injuries being a major and unsolvable issue. The development of more precise preventative procedures using the now available approaches has been excruciatingly sluggish. The development of artificial intelligence (AI) and machine learning (ML) as potentially valuable procedures to improve damage prevention and recovery procedures has been made possible by technological advances that have made these areas more accessible. This article presents a detailed summary of ML approaches as they have been used to predict and anticipate sports injuries to this point in time. The research conducted over the last five years has been collated, and its results have been untaken. Assuming the present absence of accessible sources, standardized statistics, and a dependence on obsolete deterioration prototypes, it is impossible to draw any definitive conclusions regarding the real-world effectiveness of machine learning in terms of its application to the prediction of sports injuries. However, it has been hypothesized that resolving these two problems would make it possible to deploy innovative, strong machine-learning architectures, which will hasten the process of increasing the state of this area while also offering proven clinical tools.
PM flux-reversal machine for wind energy application Bharathi, Manne; Prasanth, I. S. N. V. R.; Devi, Tellapati Anuradha; Kumar, Malligunta Kiran; Kumar, D. Ravi; Reddy, Ch. Rami
International Journal of Applied Power Engineering (IJAPE) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v13.i4.pp909-919

Abstract

Currently, attempts are being made to harness wind energy by means of non-conventional electrical machines such as flux reversal machines (FRM). The main advantage of the FRM, when compared with existing synchronous generators (SG), is that all the active parts like PMs and armature windings are mounted on the stator part, whereas leaving the rotor has simple and robust. In this study, the three-phase 6/8-pole flux reversal generators (FRGs) are selected, sized, designed, and analyzed using finite element analysis (FEA). The working principle, choice of stator and rotor poles, and machine design dimensions evaluation (analytical sizing procedure), as well as relevant performance details are discussed in this paper. This study is used to analyze, a popular 6/8 pole, 0.8 kW, 50 Hz, and examine the suitability for the wind energy applications in terms of torque and power density, torque ripple, power factor, and cogging torque under 2D finite element analysis (FEA). The analysis provides an update on the current state-of-the-art and as well as future thrust areas of research necessary to bridge the gap on what is still desired for the practical application of FRMs for wind energy.
Development of dual functional converter for drive and charging power conversion for EV drive Tadivaka, Teja Sreenu; Kumar, Malligunta Kiran; Teja, Srungaram Ravi; Reddy, Ch. Rami
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i2.pp794-807

Abstract

The adaptability of electric vehicle drives is primarily concerned with the size and efficiency of power conversion. This paper presents a unified power converter for the drive and charge functions of brushless direct current-based electric vehicle drives (BLDC). The symmetrical utilization of BLDC phase windings during charging operation is implemented for efficient power conversion. The unified converter operation, configuration, and control are presented. The proposed converter is simulated in the MATLAB/Simulink platform. The performance is evaluated using operational variables such as voltage, current, torque, and speed. A comparative study is presented regarding the size and efficiency of the proposed and existing drives. The proposed drive achieved 0.01 p.u. ripple in torque, 10-sec transient time for a change in speed full throttle command, and unity power factor current for charging operation, proving its robustness over the comparable drives.
Islanding detection of integrated DG system using rate of change of frequency over reactive power Kumari, B. V. Seshu; Prasad, Ambati Giri; Srilakshmi, S. Sai; Buchireddy, Karri Sairamakrishna; Reddy, Ch. Rami
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i3.pp1637-1644

Abstract

This paper offers a passive islanding detection method that is effective for distributed generation. When a distributed generator (DG) keeps a location powered even when access to the external electrical grid is lost, this circumstance is referred to as islanding. The power distribution system currently includes distributed generators (DGs), which provide inexpensive electricity and have fewer environmental impacts. Sometimes, these DGs continue to supply the nearby loads because of line outages and islands made by system separations. As a result, there are scenarios with unacceptable power quality. The islanding is identified if the result of the rate of change of frequency over reactive power exceeds the threshold value. The MATLAB test results from this study demonstrate the effectiveness of the suggested approach for different islanding and non-islanding scenarios.
Real-time vehicle detection and speed estimation system using Raspberry Pi and camera module Jyothi, B; Pabbuleti, Bhavana; Sanjeev, Gadi; Rao, Kambhampati Venkata Govardhan; Srilakshmi, S. Sai; Jee, Atul; Kumar, Malligunta Kiran; Bikku, Thulasi; Reddy, Ch. Rami
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9931

Abstract

In the era of intelligent transportation systems, real-time vehicle detection and distance estimation play a crucial role in enhancing road safety and traffic efficiency. This study proposes a low-cost, real-time system that integrates you only look once–version 8 (YOLOv8)-based deep learning for vehicle detection with monocular vision techniques for distance estimation, implemented on a Raspberry Pi embedded platform. The objective is to provide a scalable, affordable solution for traffic monitoring and collision avoidance in resource-constrained environments. The methodology involves using a camera module connected to Raspberry Pi for live video capture, YOLOv8 for object detection, and a calibrated monocular distance estimation algorithm based on bounding box dimensions and known vehicle sizes. Experimental results show that the system achieves over 90% detection accuracy under standard lighting conditions and maintains a distance estimation error below 10% for vehicles within 15 meters. The model processes video frames in real time (~0.17 seconds per frame), proving its effectiveness for embedded deployment. In conclusion, the proposed system offers a robust, power-efficient alternative to high-cost light detection and ranging (LiDAR) or stereo vision systems. Its modular design supports future enhancements such as speed estimation or multi-camera integration, making it highly relevant for smart city applications and low-cost vehicular safety systems.
Co-Authors Bharathi, Manne Bikku, Thulasi Buchireddy, Karri Sairamakrishna Devi, Tellapati Anuradha Jee, Atul Jyothi, B Kumar, D. Ravi Kumar, G. Syam Kumar, M. Dilip Kumari, B. V. Seshu Malligunta Kiran Kumar Pabbuleti, Bhavana Prasad, Ambati Giri Prasanth, I. S. N. V. R. Rao, Kambhampati Venkata Govardhan Reddy, Sareddy Venkata Rami Sanjeev, Gadi Srilakshmi, S. Sai Tadivaka, Teja Sreenu Teja, Srungaram Ravi