Fault Prediction and Recovery Using Machine Learning Techniques and the HTM Algorithm in Vehicular Network Environment

• Published in: IEEE open journal of intelligent transportation systems Vol. 5; pp. 132 - 145
• Main Authors: Zidi, Salah, Alaya, Bechir, Moulahi, Tarek, Al-Shargabi, Amal, Khediri, Salim El
• Format: Journal Article
• Language: English
• Published: New York IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; classification; Classification algorithms; Communications traffic; Fault detection; Fault diagnosis; fault prediction; fault recovery; Hidden Markov models; hierarchical temporal memory (HTM); Internet of Vehicles; Internet of Vehicles (IoV); Machine learning; Machine learning algorithms; Mobile ad hoc networks; Network latency; Recovery; Sensors; Vehicles; Vehicular ad hoc networks; Vehicular network; Wireless sensor networks

The amount of data available to vehicles has become very large in the vehicular networks' environment. Failures that mislead real-time data from vehicle sensors and other devices have become massive, and the need for automated techniques that can analyze data to detect malicious sources has bec...