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International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
Figure E.1(d): Image Generation Figure E.1(f): Hotword Detection Module (Jarvis)
Figure E.1(d): commanding notepad using query
3. METHODOLOGY
To create a robust and beneficial personal assistant system, the JARVIS project was developed in a systematic and planned
way. It starts with an intensive requirement-gathering phase during which the team interviews potential users and
stakeholders to find out what they will require and expect from the proposed system. Using interviews, surveys, and market
research to gain an in-depth understanding of necessary features and functionalities, lays the groundwork for future steps.
The project takes the design and architecture phase with the requirements acquired. JARVIS directions the comprehensive
system, block diagram, and entity relation are made. Focus on separation of concerns: Separation of concerns big emphasis,
promotes scalability, modularity, and flexibility, allowing for easy future enhancements, changes, and integrations, keeping the
System/s responsive to changes in technological advances and user needs. After design comes technology selection, which is
even more crucial. It plans the best-suited programming languages, libraries, frameworks, and APIs to build features, such as
speech recognition, natural language processing, and an online interface for the project. This foundational stage lays the
foundation for the implementation stage to come.
Implementation is when we take plans into action, literally putting well-designed plans into practice. The developers
painstakingly code the different modules and components of the JARVIS system, integrating third-party services and APIs and
ensuring that everything works smoothly across platforms. This phase is characterized by iteration and continuous
improvement to achieve the desired outcome.
Testing and validation is an imperative step in ensuring the quality and reliability of the JARVIS system. Unit Testing,
Integration Testing, and System Testing are done to find and fix any bugs or problems. Comments from users and validation
are also welcomed to certify that the system is effective and usable, which will help how to change or upgrade the system.
When most of the development cycle is over, deployment and optimization take center stage. JARVIS: Used by the community
to develop and deploy new features to JARVIS or to download and install the latest production instances of JARVIS.
Optimization and monitoring for ongoing performance, reliability, and user experience improvements. Users submit feedback,
and any reported bugs are quickly patched, with incremental improvements constantly made to enhance their experience with
the app, keeping the JARVIS project as an updated, innovative, user-friendly, and highly functioning program. This entire
methodology, the JARVIS project will provide users with a state-of-the-art personal assistant platform that goes above and
beyond and ultimately sets the stage for further advancements in the space.
1. Introduction: Describe the problem of cognitive workload balance in dynamic settings such as healthcare, aviation, and
education
2. Data Collection Collect multimodal data: physiological (EEG, heart rate), behavioral (task metrics), environmental (noise,
task complexity), emotional state.
3. System Design: Create a modular design that connects voice input to a microphone, STT, and NLP with backend processing
including a Knowledge Base, and GUI and voice output modules.
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