Performance evaluation and profiling of employees

• Main Author: Teh, Marcus Ming Sheng
• Other Authors: Miao Chun Yan
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/171993
• Institution: Nanyang Technological University

Performance evaluation and profiling of employees is important as it offers valuable insights into efficiency and safety of fleet operators. With a growing concern for road safety, it has become imperative for fleet operators to prioritize safe driving practices among their employees. Evaluating driver performance goes beyond merely punctuality, it delves into driving habits and styles. Encompassing factors such as speeding, harsh acceleration, harsh deceleration, harsh cornering, and lane departure. Such data can be gathered efficiently using additional hardware tools mounted on the vehicles which will log such occurrences. These data can then be processed and explored to serve as a foundation for driver profiling, shedding light on individual driving habits and tendencies. With such data, models can be created to predict driver grades, allowing the system to learn the distinctive patterns and characteristics associated with drivers of varying safety levels. Such models are adaptable and can be continuously improved as more data is collected and analysed, leading to increasingly accurate profiling.