1. Project 1: Smart Home REU student: Jason Ling Graduate mentors: Safa Bacanli Faculty mentor(s): Damla Turgut
Week 6 (June 18 – June 25, 2018)
Accomplishments:
Learned basics of TensorBoard to graph cost function
Modified fully-connected neural network to lower Huber Loss to around 5 units (UMass dataset)
NSF REU Research Experience on Internet of Things 2018

2. Project 1: Smart Home REU student: Jason Ling Graduate mentors: Safa Bacanli Faculty mentor(s): Damla Turgut
Week 6 (June 18 – June 25, 2018)
Accomplishments (cont.):
Able to control both doors and windows of Smart Home
Converted C to Python code for Temperature and Humidity Sensor
Created a library of functions for the Smart Home
Parsed the entire UMass dataset into the same format
Read multiple papers related to Cyber Physical Systems (CPS) and Hybrid Temperature Control (HTC) in a Smart Home Environment
NSF REU Research Experience on Internet of Things 2018

3. Project 1: Smart Home REU student: Jason Ling Graduate mentors: Safa Bacanli Faculty mentor(s): Damla Turgut
Week 6 (June 18 – June 25, 2018)
Problem & Solutions
Problem: Neural network has around 50% accuracy with a low Huber Loss & Solution: Shuffle data and get training accuracy
Problem: Temperature Sensor Module (KY-028) outputs inaccurate data & Solution: Need to calibrate the sensor
Plans for next week:
Get respectable level of accuracy for the fully-connected neural network
Combine UMass dataset into one CSV file instead of multiple
Figure out KY-028 problem or just ditch it
Read more papers on CPS and HTC Systems
Collect Smart Home data
Begin thinking about the security risks of CPS in a Smart Home Environment
NSF REU Research Experience on Internet of Things 2018