Report

Golamnsl

April 12, 2021 - April 18, 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)

60% Progress
Last Week's Progress

Paper 4:
* Continue the dataset collection of nodes energy consumption
* Started the dataset pre-processing task

Paper 5:
* Worked on the simulation of knowledge-based neural network (KBNN) based energy prediction
* Continued the paper writing

This Week Todo's

Paper 3:
* Start working on the revision of the paper for reviewer number 1
* Complete the revision of the first two review comment

Paper 5:
* Continue the simulation and finish it within this week
* Finish the paper writing and prepare for submission

Project Progress

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

60% Progress
Last Week's Project

Project 1:
* Survey on the OLSR implementation at outdoor environment
* Continue working on OLSR routing

Project 2:
* Survey papers related to ITS on global trends

This Week's Project

Project 1:
* Continue the simulation work of OLSR routing
* Survey papers regarding OLSR implementation in indoor environment

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