Paper 1: Real-Time Drone Detection Scheme Using Deep Learning from Thermal Sensors Data to Prevent the Threat of UAV to Nuclear Facilities, (Target: IEEE Wireless Communication Letters)
Paper 2: Anti-Drone Design Techniques and Technology: A Survey (Target: IEEE Access/ IEEE 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]
Paper 4: Comparative Performance Evaluation of Enhanced-OLSR with Topology-based Routing Protocols for UANET (Submitted to: MDPI Drones Specal Issue) [Major Revision]
Paper 5: 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 4:
* Revised the paper based on the comment from the reviewer
* Submite the revised manuscript
Paper 3:
* Worked on the simulation to provide more performance result based on reviewers comment
* Add more context on the paper for reviewers suggestion
Paper 5:
* Started writing the KICS paper
Paper 3:
* Complete the simulation and add the results on the paper
* Finish the revision of the paper and submit before deadline
Paper 4:
* Awaiting for the decision from the journal
* Re-chechk the paper and fine-tune it
Paper 5:
Keep writing the paper for KICS conference
Development of UAV routing protocol for civil and military, Anti-drone project
Project 1:
* Complete the revision and submit to the journal
Project 2:
Started writing the survey paper
Project 1:
* Awaiting decision of the paper
* Chech the paper for more fine-tuning
Project 2:
* No task on this week
* Complete the revision from the IoT journal and submit it before deadline
* Start working on the winter intensive and finish the KICS 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