All Outputs (2)

Machine Learning-based Real-Time Sensor Drift Fault Detection using Raspberry Pi (2020)
Presentation / Conference Contribution
Saeed, U., Ullah Jan, S., Lee, Y., & Koo, I. (2020, January). Machine Learning-based Real-Time Sensor Drift Fault Detection using Raspberry Pi. Presented at 2020 International Conference on Electronics, Information, and Communication (ICEIC), Barcelona, Spain

From smart industries to smart cities, sensors in the modern world plays an important role by covering a large number of applications. However, sensors get faulty sometimes leading to serious outcomes in terms of safety, economic cost and reliability... Read More about Machine Learning-based Real-Time Sensor Drift Fault Detection using Raspberry Pi.

Machine Learning for Detecting Drift Fault of Sensors in Cyber-Physical Systems (2020)
Presentation / Conference Contribution
Jan, S. U., Saeed, U., & Koo, I. (2020, January). Machine Learning for Detecting Drift Fault of Sensors in Cyber-Physical Systems. Presented at 2020 17th International Bhurban Conference on Applied Sciences and Technology (IBCAST), Islamabad, Pakistan

Cyber-Physical System (CPS) emerges as a potential direction to improve the applications relating to object-to-object, human-to-human and human-to-object communications in both the real world and virtual world. The examples of CPSs include Smart Gird... Read More about Machine Learning for Detecting Drift Fault of Sensors in Cyber-Physical Systems.