URL Bit
- Utilized Arduino UNO as edge device for Condition Based Monitoring, trained LSTM model on factors like vibration, power consumption, resulting in a 30% reduction in machine downtime
- Analyzed time series datasets to predict the RUL and predict faults 7 days in advance with 94% accuracy using Random Forest algorithms
- Published the research paper in International Research Journal of Engineering and Technology 2021
Swarangi Gaurkar
Software Engineer
My research interests include Automated Software Engineering, Cloud Computing and Machine Learning.
