Papers

1. Machine Learning with IIoT
2. Deep Learning -based forecasting approach in Smart Grids with micro-clustering and Bi-directional LSTM Network
3. Energy Load Clustering in Smart Grid: Methodologies, Applications and Future Trends
4. Continue survey of related works to gain understanding of research works in IIoT and IoT

Last Week's Progress

1. Attended Lectures
2. Submitted Reports and Assignments
3. Surveyed paper on Smart Grids and Machine Learning

This Week Todo's

1. Attend Lectures
2. Continue with review of Deep Learning -based forecasting approach in Smart Grids with micro-clustering and Bi-directional LSTM Network and Energy Load Clustering in Smart Grid: Methodologies, Applications and Future Trends
3. Continue with Machine Learning

Project Progress

IoT applications for Smart Home

Last Week's Project

[1] Discussing task allocation for IoT application project
[2] Learn data pre-processing in ML

This Week's Project

[1] Focus on understanding the alternative thermal array dataset for the IoT application project
[2] Continue learn machine learning in GMLCC

Monthly Goals

Be able to create iot project on matlab/python

Annual Goals

submit conforence and/or iot journal page