MONESHKUMAR M

Detail-oriented professional with a robust background in hardware diagnostics and system repair, leveraging extensive experience as an Apple Service Technician to troubleshoot and optimize Apple devices, including MacOS systems. Recently earned an M.Tech in Mechatronics Engineering, enhancing expertise in embedded systems, robotics, and control systems. Capable of integrating mechatronic principles into innovative hardware design and development. Aiming to secure a Hardware Engineer position to utilize technical skills and problem-solving abilities in advancing cutting-edge hardware solutions.

• Apple Certified Macintosh Technician (ACMT), 05/01/21, 11/01/21
• Apple Certified iOS Technician (ACiT), 05/01/21, 11/01/21

• Sustainable Predictive model on Autonomous Mobile robot using Deep Learning, 01/01/24, 05/01/24, NVIDIA's Isac Sim simulator which advanced GPUs and TensorRT in accelerating the deep learning inference, reducing latency and enhancing real-time decision-making capabilities develop the predictive model for advanced field of autonomous robotics.
• Enhancing Electronics Manufacturing Precision: Haptic Technics for Accurate PCB Soldering and Component Assembly, 07/01/23, 12/01/23, These systems can replicate the delicate touch of human hands, applying the right amount of force and making fine adjustments as needed. The use of haptic technics also improves the training and skill development of human operators, as they can practice and refine their techniques with immediate tactile feedback.
• Enhancing Car Door Safety: IR Sensor-Based Hand Detection and Plunger Actuator Mechanism, 02/01/23, 06/01/23, This advanced safety feature ensures that hands, fingers, or any other objects are not caught in the door, minimizing the risk of injury. The plunger actuator mechanism is designed to respond rapidly and precisely, providing a reliable barrier against accidental closures.
• Fault Diagnosis of IC Engine Gear Box using Deep Learning, 09/01/22, 01/01/23, Collected high-frequency vibration signals from the gearbox under various conditions, preprocessed and transformed into images using MATLAB's DIP tools. Trained deep learning models (CNNs/RNNs) on these images to identify patterns for normal and faulty states.
• Smart Sensor Based Structural Health Monitoring System, 01/01/19, 06/01/19, Making of Smart technics to sense the condition of the Buildings.