Papers

1. Blockchain-Enhanced Client Selection and AdaTrim for Secure Federated Learning in IoT Networks
Status: Submitted

2. Trimmed Averaging for Efficient Federated Learning in the Internet of Things
Status: Submitted

Last Week's Progress

Brain storming implementation of my future works for the previous submitted papers

This Week Todo's

1. Continuing with my study and research on creating an efficient federated learning framework for Internet of things that uses block chain for both securing the stored data and the data that is transit.
-Currently surveying and outsourcing papers that are focused on federated learning.

2. Developing a secure IOT-Driven Realtime home security system with BlockChain technology.
-Currently gathering and looking for papers that have developed and worked on the similar idea.

Project Progress

1. Digital Twin (18%)
2. Purepet (80 %)

Last Week's Project

1. Digital Twin (18%)
-Reviewing implemented features in the WEB GL application for the digital twin
2. Purepet (80 %)
- Modifying the user interface design of the mobile application

This Week's Project

1. Digital Twin (18%)
- Studying Python web framework(Flask and Django)
2. Purepet (80 %)
-Intergrating the mo0bile application with the web application

Monthly Goals

Continue working toward optimizing the Federated Average algorithm to improve its robustness and efficiency. This includes incorporating insights from the literature review on Edge IoT, applying QAT to the neural network model, and fine-tuning the model with new datasets.

Annual Goals

1. Submit at least two articles to scientific journals.
2. Submit and attend at least one NSL-approved domestic conference.
3. Submit and attend at least one NSL-approved international conference.