README.md

README.md

@@ -1,17 +1,31 @@
 # intel-oneAPI
 
-#### Team Name -
-#### Problem Statement - 
-#### Team Leader Email -
+#### Team Name -Insight guardians
+#### Problem Statement - Open innovation for education
+#### Team Leader Email - [email protected]
 
 ## A Brief of the Prototype:
-  This section must include UML Daigrms and prototype description
-
+The existing education system lacks a reliable and real time method to monitor and analyze student behavior within classrooms, leading to challenges in identifying
+struggling or disengaged students.This problem can result in ineffective interventions and hinder academic progress.To address this issue, an AI and ML based Class Monitoring System is proposed,incorporating Intel's ONEAPI library OneDnn for enhanced accuracy and performance.By leveraging advanced algorithms and machine learning techniques, the system aims to provide educators and administrators with valuable insights into student engagement, attendance, and behavior patterns.The integration of OneDnn is expected to optimize deep learning operations and hardware utilization, leading to efficient data processing, reliable predictions, and improved decision making for effective support and educational outcomes.
+![image](https://user-images.githubusercontent.com/113164986/236693051-0563428f-9916-4536-bb30-9d0f05f7f9de.png)
+
 ## Tech Stack: 
-   List Down all technologies used to Build the prototype **Clearly mentioning Intel® AI Analytics Toolkits, it's libraries and the SYCL/DCP++ Libraries used**
-
+   1 Python as the primary programming language
+   2 Flask, a lightweight web framework, will be used for web application development
+   3 Sensors and camera
+   4 The system will utilize SQLite or PostgreSQL as the database
+   5 It wil l be deployed using Docker and cloud platforms like AWS or GCP
+In the project, the following oneAPI AI Analytics Toolkits libraries and SYCL/DPC++ libraries have been used:
+1.oneDNN: The oneDNN library has been utilized to optimize deep learning operations and enhance the accuracy and performance of the Class Monitoring System.
+2.oneDAL: The oneDAL library has been employed for data analytics tasks in the project.
+3.oneTBB : The oneTBB library has been utilized for parallel programming in the project.
+4.oneAPI DPC++ Compiler and SYCL: The oneAPI DPC++ Compiler and SYCL programming model have been used in the project for heterogeneous programming.
 ## Step-by-Step Code Execution Instructions:
-  This Section must contain set of instructions required to clone and run the prototype, so that it can be tested and deeply analysed
+1)First implement the libraries
+2)Understand about the data
+3)Test different Models and find the best model out of it
+4)Train the model using Intel OneAPI Dnn
+4)Save the model
 
 ## What I Learned:
-   Write about the biggest learning you had while developing the prototype
+One of the biggest learnings while developing a prototype is the importance of iteration and flexibility. The initial design and implementation may not always align perfectly with the desired outcome, and it's crucial to embrace feedback and adapt the prototype accordingly. This iterative approach allows for continuous improvement and refinement based on user needs and project goals. Additionally, the process of developing a prototype often reveals unforeseen challenges and complexities, highlighting the significance of thorough planning, research, and testing. Furthermore, effective communication and collaboration within the development team and with stakeholders contribute to a successful prototype, as it ensures everyone is aligned and working towards the same vision. Lastly, maintaining a user-centered approach and incorporating user feedback throughout the development cycle helps create a prototype that truly addresses user needs and provides a valuable solution.