This paper provides an in-depth study of vibration-based condition monitoring for heavy machinery, focusing on the devices and methods used for data collection. The authors review 114 research papers, emphasizing the importance of predictive maintenance in reducing downtime, maintenance costs, and project delays. They highlight the role of vibration sensors, particularly accelerometers, in measuring vibrations and collecting data. The paper discusses various types of accelerometers, such as piezoelectric, PCB, wired, wireless, MEMS, and triaxial accelerometers, and their applications in different industries. The authors also explore the advantages and challenges of vibration-based condition monitoring, including data interpretation complexity and the impact of breakdowns on operational costs and safety. The review covers a wide range of heavy machinery, including industrial manufacturing machinery, construction equipment, mining machinery, transportation vehicles, and energy generation equipment. The paper concludes by summarizing the findings and providing insights into efficient condition monitoring systems, aiming to enhance machine efficiency and reliability.This paper provides an in-depth study of vibration-based condition monitoring for heavy machinery, focusing on the devices and methods used for data collection. The authors review 114 research papers, emphasizing the importance of predictive maintenance in reducing downtime, maintenance costs, and project delays. They highlight the role of vibration sensors, particularly accelerometers, in measuring vibrations and collecting data. The paper discusses various types of accelerometers, such as piezoelectric, PCB, wired, wireless, MEMS, and triaxial accelerometers, and their applications in different industries. The authors also explore the advantages and challenges of vibration-based condition monitoring, including data interpretation complexity and the impact of breakdowns on operational costs and safety. The review covers a wide range of heavy machinery, including industrial manufacturing machinery, construction equipment, mining machinery, transportation vehicles, and energy generation equipment. The paper concludes by summarizing the findings and providing insights into efficient condition monitoring systems, aiming to enhance machine efficiency and reliability.