Report

Golamnsl

April 5, 2021 - April 11, 2021

Papers

Paper 1: UAV-assisted Solar Energy Distribution Technique Based on Partial Brownian Movement for the Internet of Things (Target: JCN).

Paper 2: Development of Routing Protocol in UAV Network for Military Environment, [Winter Intensive] (Target: ICT Express)

Paper 3: LSTM Based Solar Irradiance Prediction From Remote Sensing of Meteorological Data, (Target: IEEE Geoscience and Remote Sensing Letters)

Paper 4: A Machine Learning-based Energy Prediction Scheme for Energy-Harvesting Base Station, (Target- Upcoming Conference)

Paper 5: Accuracy Improvement of Solar Energy Prediction for Energy Harvesting WSN using Hybrid Deep Learning Technique (Winter Intensive) (Target: ICT Express or Renewable Energy (Elsevier)

75% Progress
Last Week's Progress

Paper 4:
* Continue the simulation of energy prediction
* Keep collecting the dataset of the Drone base station for simulation

Paper 3:
* Started working on the review comment of the 1st reviewer

This Week Todo's

Paper 3:
* Continue working on the review comment of the 1st reviewer
* Do more literature survey

Paper 4:
* Continue collecting the dataset of drone base station
* Keep working on the simulation of energy prediction

Project Progress

Development of UAV routing protocol for civil and military, Anti-drone project

70% Progress
Last Week's Project

Project 1:
* Worked on the simulation of OLSR routing in OPNET


Project 2
* Surveyed papers regarding traffic control management in the intelligent transportation system

This Week's Project

Project 1:
* COntinue the simulation of OLSR routing in OPNET
* Survey papers related to OLSR implementation in FANET

Project 2:
* Survey more papers regarding the intelligent transportation system project

Monthly Goals

1. Complete working on the revision of the journal of IEEE Geoscience and Remote Sensing Letters

2. Complete the winter intensive paper and submit it

Annual Goals

* Submit at least two Journal in one year

* Attend one International Conference

* Make sure to learn as many simulation tools as possible