Aniket Fasate

Experience

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  Indian Institute of Technology, Kanpur

  Jun 2018 - Jun 2018

  Summer Trainee ( AI/ML and IoT)

  Autonomous Vehicle Prototype Development: Pioneering an autonomous vehicle, we initiated the project by assembling the vehicle from scratch. IoT sensors, ultrasonic sensors, and ESP32 controllers facilitated data collection. Subsequently, the data underwent meticulous training in MATLAB using backpropagation. The Raspberry Pi, employed for self-training testing, exemplifies robustness in real-world scenarios. This project integrates cutting edge technologies, showcasing proficiency in sensor fusion, deep learning, and embedded systems, culminating in a comprehensive autonomous vehicle prototype. Show less

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  Defence Research and Development Organisation (DRDO)

  Jun 2019 - Jul 2019

  Summer Trainee( AI/ML and IoT)

  • Sentimental Analysis: Engineered an intricate sentiment analysis system employing TensorFlow for neural network architecture, Scikit-learn for machine learning algorithms, and NLTK for natural language processing. Implemented a Convolutional Neural Network (CNN) model with tokenization, embedding layers, and the Adam optimizer for precise text analysis. Rigorous dataset handling, preprocessing, and backpropagation were executed. The Graphical User Interface (GUI) elevated the user experience, integrating real-time feedback. This project showcases comprehensive expertise, offering a robust sentiment identification tool with diverse AI/ML libraries. Show less

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  Freelancer.com

  Jun 2020 - Feb 2021

  AI/ML and IoT
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  Avinya Intelligence

  Aug 2020 - now

  Chief Executive Officer

  In the dynamic landscape of modern manufacturing, the integration of the Internet of Things (IoT) and Artificial Intelligence (AI) stands as a pivotal innovation, fundamentally transforming quality control processes. This paper delves into the multifaceted approach of utilizing IoT and AI to drastically reduce manufacturing defects, thereby elevating product quality and operational efficiency. IoT devices, strategically embedded within manufacturing units, collect a vast array of real-time data, encompassing machine performance, environmental conditions, and production output. This data, characterized by its volume, variety, and velocity, forms the bedrock upon which AI algorithms operate. AI, with its advanced analytical capabilities, interprets this complex data, identifying patterns and anomalies that are imperceptible to human operators. Through machine learning and predictive analytics, AI facilitates proactive defect detection, preempting potential issues before they escalate into significant production flaws. This synergy of IoT and AI not only enhances the detection of defects but also contributes to continuous process improvement by providing insights for operational optimization. The paper further explores case studies where this integrated approach has led to a substantial reduction in defect rates, underlining the transformative impact on quality assurance. This exploration signifies a paradigm shift in manufacturing quality control, showcasing a future where technological convergence drives unparalleled precision and reliability in production processes. Show less

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  Indian Institute of Technology, Bombay

  Feb 2021 - Aug 2023

  Research Assistant

  Site Survey Kit: Engineered in MPU6050 and MPU9250 versions, this kit excels in on-site motion data collection. Achieving high-frequency data acquisition (up to 4kHz accelerometer, 8kHz gyroscope), the handheld device offers real-time insights with graph plotting. Its hosting server capabilities and Over-The-Air updates enhance convenience, ideal for construction and research, providing a portable solution for motion analysis, structural health monitoring, and dynamic behavior research.• Data Logger: Presenting two versions tailored for diverse monitoring needs. Version 1 integrates DHT22 and LDR sensors, optimizing climate monitoring with real-time user connectivity. Version 2 employs K-type thermocouples for precise Fahrenheit readings, catering to high-temperature environments. Both versions prioritize advanced data analysis, featuring hosting servers for seamless data management.• Dandi Project: Implementing ESP series microcontrollers, the Dandi Project optimizes structural health monitoring on a 40-meter platform. Utilizing predictive analytics, the device assesses structural integrity. Featuring a user-friendly GUI, OTA updates, and advanced telemetry, this project seamlessly amalgamates IoT capabilities, data analytics, and predictive maintenance for enhanced structural robustness.• Utilizing ESP32-CAM and YOLOv3, this project employs OpenCV and ESPAsyncWebServer for efficient image processing and web hosting. Through innovative tunneling, users experience dynamic object identification on screens, harmonizing cutting-edge algorithms with ESP32-CAM capabilities for advanced real-time environmental monitoring.• AI/ML Projects: Engaged in diverse projects, including advanced tasks like object detection and image classification Additionally, simpler yet impactful projects involve sentiment analysis, spam email detection, and predictive text generation. Show less

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  Northeastern University

  Jan 2024 - now

  Research Assistant

  XR/AVR Technology:• Proficient in programming Teensy 3.2 and AVR microcontrollers for advanced capacitive sensing applications, focusing on non-contact eye movement tracking in XR/AVR environments.• Led the full project lifecycle, emphasizing the design, development, and integration of sensor technologies within robotics systems, enhancing immersive user experiences.• Dedicated to pioneering intuitive navigation solutions for XR/AVR applications, significantly improving immersive experiences through user engagement and interactive technology solutions. Show less