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) [Revision (with Dr. Rubina)]
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 1:
* Finished the simulation process (accuracy of prediction)
* Almost finish the paper writing (still need to re-write the performance evaluation part)
Paper 2:
* Surveyed some papers aucostic based and WiFi based neutralization
* Write the comparative studies between aucostic and WiFi based drone neutralization
Paper 1:
* Complete the paper (writing, fine-tuning, cross check, etc)
* Submit after professor approval
Paper 2:
* Survey on acoustic based drone detection and neutralization
* Create the comparative studies with vision and RF and write down on the paper
Anti-Drone System, Development of UAV routing protocol for civil and military
Project 1:
* Surveyed different drone neutralization technique to find out optimal solution
* Discussion with the project members and fixing the project goal
Project 2:
* No task assignedin the previous week
Project 1:
* Make ppt file for the project progress presentation to professor Lee
* Continue working on the Survey paper on Anti-Drone system
Project 2:
* No further instruction for any task to complete
* Finish the remaining papers to submit on the journal
* Start working on the upcoming conference paper
* 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