Asset management has significantly evolved with the integration of modern communication technologies and the Internet of Things (IoT). This project aims to enhance asset management by implementing real-time monitoring for predictive maintenance and data-driven decision-making. Through IoT technology, sensors and modules are embedded in physical assets to collect data on their condition, performance, and environment. This data is transmitted via wireless networks to IoT platforms, where it is analysed using cloud-based algorithms and monitoring systems. The insights gained enable organisations to predict failures, optimise resource usage, and reduce downtime and operational costs. The proposed system incorporates cost-effective hardware, including Arduino-based microcontrollers, LoRa transmitters and receivers, and secure data communication protocols. Data analytics tools, using Microsoft Excel, were used to evaluate asset performance and identify trends. The findings demonstrate that integrating IoT with asset management significantly improves operational efficiency, facilitates early fault detection, extends asset lifespan, and enhances overall productivity. In conclusion, this approach offers a comprehensive and scalable solution for managing complex systems, marking a substantial advancement in engineering asset management.
Nasir et al. (Wed,) studied this question.