Report

Golamnsl

May 23, 2022 - May 29, 2022

Papers

Paper 1: Deep-Block: Blockchain-assisted Secure and Energy Efficient UAV-BS Deployment Using Deep Learning (Target: IEEE Transaction on Vehicular Technology)

Paper 2: Anti-Drone Design Techniques and Technology: Challenges, Oppurtunities, and Future Directions (Target: IEEE Journal on Selected Areas in Communications)

Paper 3: IoMT-Net: Blockchain Integrated Unauthorized UAV Localization Using Lightweight Convolution Neural Network for Internet of Military Things. (Submitted to: IoT Journal) [Accepted]

Paper 4: Deep Learning in Anti-Drone: Review on Drone Identification, Classification and Localization Based on Deep Learning (Target Journal: IEEE Journal on Selected Areas in Communications)

Paper 5: Blockchain Inspired Intruder UAV Localization Using Lightweight CNN for Internet of Battlefield Things (Target: MILCOM 2022)

50% Progress
Last Week's Progress

Paper 3:
* Worked on the extraction of the paper for WoiP for Milcom coference
* Already started working on the system model

Paper 2:
* Continued work on the survey on the comparative analysis of different models
* Continue writing the paper

This Week Todo's

Paper 5:
* Complete the simulation work for the conference submission
* Finish the paper writing for final submission
* Submit as soon as possible to MILCOM

Paper 3:
* Re-check if there are any further errors for proof-read submission

Project Progress

Anti-Drone System

50% Progress
Last Week's Project

* Presented the project progress presentationon Capstonr Design
* Surveyed related workon Ant-Drone system

This Week's Project

* Work on the final project report and as the project is finish
* Start working on another project proposal

Monthly Goals

* Finish the remaining papers to submit on the journal
* Start working on the upcoming conference paper

Annual Goals

* Get accepted at least two SCI journal and submit as many as possible

* Attend as many competetive international conferences

* Make sure to learn aand gain depth knowledge about the anti-drone system