Papers

1. Blockchain-Enhanced Client Selection and AdaTrim for Secure Federated Learning in IoT Networks
Status: Rejected, Needs resubmission to another Journal

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

3. Impact of neural network Configurations in Federated Learning Optimization for Intrusion Detection in Edge-Iot devices (Tentative)

Last Week's Progress

3. Impact of neural network Configurations in Federated Learning Optimization for Intrusion Detection in Edge-Iot devices (Tentative)
- Downloading papers for reference so as to do a comprehensive literature review
- Writing the introduction to the paper

This Week Todo's

3. Impact of neural network Configurations in Federated Learning Optimization for Intrusion Detection in Edge-Iot devices (Tentative)
-Designing system model
-Summarizing and formulating literature review for the paper

Project Progress

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

Last Week's Project

1. Digital Twin (18%)
- Modifying the web interface for the Web application of the digital twin
2. Purepet (80 %)
-Further modifying the app interface design

This Week's Project

1. Digital Twin (18%)
- Learning three.js for the web application of the digital-twin
2. Purepet (80 %)
-Carrying out research on integrating live advertisements in the mobile 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.