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All Journal IAES International Journal of Robotics and Automation (IJRA) Indonesian Journal of Electrical Engineering and Computer Science
Deshmukh, Sanjay
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Automotive Engineering Electrical & Electronics Engineering

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An autonomous robotic arm for efficient rock collection in uncharted territories Deshmukh, Sanjay; Thakker, Bhaumik Hitesh; Gupte, Vedangi Nilesh; Kapadia, Taher Kutbuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp779-786

Abstract

The autonomous rock collector using robotic arm for exploration of unknown territories (ARCAxUT) is introduced as an innovative solution for the efficient retrieval of rock samples in unexplored space regions. Traditional, human-reliant methods are costly and hazardous, prompting the development of ARCAxUT. Equipped with a smart robotic arm, an RGB-D camera, and NUC computer, the system autonomously detects and estimates the mass of various rock samples. Validated in simulated and real-world environments, the algorithm ensures precise gripper control, achieving an impressive 95.4% accuracy in rock size estimation. This breakthrough offers transformative capabilities for space missions, revolutionizing celestial body sample collection and advancing broader societal implications in space exploration technologies.
IoT-enabled smart healthcare system with machine learning for real-time vital sign monitoring and anomaly detection Deshmukh, Sanjay; Shah, Shrey; Wahedna, Asim; Sabnis, Nimish
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1155-1163

Abstract

This paper presents an innovative IoT-enabled smart healthcare system that combines real-time vital sign monitoring with machine learning-based anomaly detection. The system utilizes a MAX30102 photoplethysmography sensor interfaced with an ESP-32 microcontroller to collect heart rate and blood oxygen saturation (SpO2) data. MQTT protocol ensures efficient data transmission to a cloud database. A long short-term memory (LSTM) neural network architecture is employed for time-series prediction of vital signs and anomaly detection. The system demonstrates high accuracy, with mean squared errors of 0.3% in offline testing and over 90% accuracy in real-time prediction. This affordable and scalable solution offers continuous monitoring capabilities, making it viable for widespread adoption in healthcare settings. The integration of IoT and machine learning techniques provides a robust framework for early detection of health anomalies, potentially improving patient care and outcomes in various medical scenarios.
Design and implementation of QUADRESCUE: A ROS-based quadruped robot for disaster response support Deshmukh, Sanjay; Chanakya, Ojas; Gabani, Om; Patni, Kashish; Deshmukh, Asmita
IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v14i3.pp387-398

Abstract

Search and rescue (SAR) operations in hazardous environments demand robotic systems capable of traversing complex terrains while ensuring responder safety. Traditional wheeled platforms often fail in debris-laden areas, and fully autonomous quadrupeds remain financially out of reach for many rescue agencies. This paper presents the design and development of QUADRESCUE, a modular operator-assisted quadruped robot built to bridge the gap between affordability and capability in disaster response. QUADRESCUE delivers core SAR functionalities including remote visual inspection, real-time terrain mapping via an RGB-D camera, payload transport, and GPS-based survivor localization. Built with a robust three degrees of freedom (3DoF) per leg design, the robot uses inverse kinematics algorithms to precisely control twelve servo motors for stable locomotion across uneven terrain. The system integrates the robot operating system (ROS) for seamless operation, real-time joystick control for easy navigation, an IMU for orientation sensing, and a GPS module with 3-meter accuracy. Field evaluations demonstrate 80–94% success rates on challenging surfaces, substantially outperforming wheeled counterparts 19% to 39% with a 200-meter control range and 45 minutes of runtime. QUADRESCUE offers a lightweight, cost-effective, and repairable solution that combines practical usability with advanced performance, making it well-suited for real-world deployment in emergency rescue situations.
Co-Authors Chanakya, Ojas Deshmukh, Asmita Gabani, Om Gupte, Vedangi Nilesh Kapadia, Taher Kutbuddin Patni, Kashish Sabnis, Nimish Shah, Shrey Thakker, Bhaumik Hitesh Wahedna, Asim