Towards User Centric Automation of Everything

Overview

This dissertation explores the concept of user centric automation, addressing the limitations of current automation systems and presenting a novel framework that focuses on data-driven, quantum-enhanced automation pipelines. The proposed solution focuses on a user-centric approach, empowering non-technical or illiterate users to provide real-world inputs and seamlessly receive intuitive visual outputs.

Objectives

• To design a holistic, user-centric automation framework enabling intuitive interactions through inputs like touch, audio, video, and text, making automation accessible to all users.
• To leverage advanced data-driven methodologies and quantum computing for automating the entire machine learning pipeline, ensuring efficiency, scalability, and adaptability.
• To identify and develop innovative automation applications across critical domains such as healthcare, education, infrastructure, and sustainable development.

Key Features

• Data-Driven Automation Pipeline:

  • Automated data collection using quantum sensors.
  • Automated data cleaning (handling missing values, outliers, and categorical encoding).
  • Automated data modeling with optimization techniques (Pyomo-based frameworks).

• Quantum Algorithm Integration:

  • Automated generation of quantum algorithms tailored to specific user needs.
  • Integration of classical and quantum processes for hybrid optimization.
  • Functional-level synthesis of quantum circuits.

• Applications:

  • Practical implementations in diverse domains such as education, healthcare, agriculture, and infrastructure, aiming for inclusivity and sustainability.

Key Sections

1. Understanding the Evolution of Automation of Everything: Historical perspectives on automation, including ancient mythologies and their influence on modern automation systems.

2. Analysis of Current Technologies: Detailed examination of existing automation frameworks, including AutoML, OpenAI, Lambeq, Classiq, and Quantastica.

3. New Initiatives for User Centric Automation of Everything:

   • Challenges in existing automation systems.
   • Reinventing conceptual foundations for user centric automation.
   • Data-driven automation of the entire machine learning pipeline.

4. Applications: Emerging fields like automated education, healthcare, social engineering, agriculture, and even space habitat development.

5. Conclusion: The research proposes a novel user-centric automation pipeline that enables intuitive interaction with automation systems, generates optimal quantum algorithms tailored to user data, and visualizes outcomes, laying the groundwork for transformative automation technologies grounded in labor, creativity, and computation.

Future Directions

• Enhance automated data modeling frameworks and develop more sophisticated methods for generating complex quantum algorithms.
• Introduce wearable quantum rings as innovative input-output devices to revolutionize user interactions and online services.
• Explore new computational models and conceptual foundations to establish a unified theory of user-centric automation.

Acknowledgment

I extend my heartfelt gratitude to Prof. Vikas Saxena, Director & Head, CSE & IT Department, JIIT, Noida for his invaluable guidance and support throughout the development of this dissertation on Towards User Centric Automation of Everything.