Construction equipment breakdowns create numerous complications. Some of these include delayed work, increased maintenance costs due to repairs, safety issues related to equipment having the potential to break down or malfunction unexpectedly. In response, we have initiated a research project, which focuses on developing a method of maintaining construction equipment prior to any type of failure. We will accomplish this with the use of IoT devices (modules with the ability to send and receive information), as well as using machine learning, or intelligent algorithms capable of learning from historical and current operating data. By using this innovative maintenance method, we will effectively have the ability to monitor equipment operations on an ongoing basis, as well as identify any abnormalities and predict when equipment may have failure-related issues. We will gather a substantial amount of data from several different types of sensors located on the equipment we are monitoring. For example, the sensors will identify how well the construction equipment is operating and the environmental conditions surrounding it. We will be utilizing The Azure IoT Hub to facilitate the management of the data we collect, with all of the data being migrated into Azure Cosmos DB for storage and processing. The provided robust data model supports the organization and structure of newly collected data through ETL process for machine learning purposes. We will analyze the historical operating characteristics of each piece of equipment to develop predictive models to identify early indications of mechanical wear and optimize maintenance strategies by predicting failure of the equipment before it becomes an issue. Finally, we will develop a Power BI real-time monitoring dashboard to display the overall health of each piece of construction equipment.
Predictive Maintenance, Machine Learning, Internet of Things (IoT), Construction Machinery, Failure Prediction, Azure IoT Hub, Cosmos DB, ETL Pipelines, Real-Time Monitoring
International Journal of Trend in Scientific Research and Development - IJTSRD having
online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International
Journal which provides rapid publication of your research articles and aims to promote
the theory and practice along with knowledge sharing between researchers, developers,
engineers, students, and practitioners working in and around the world in many areas
like Sciences, Technology, Innovation, Engineering, Agriculture, Management and
many more and it is recommended by all Universities, review articles and short communications
in all subjects. IJTSRD running an International Journal who are proving quality
publication of peer reviewed and refereed international journals from diverse fields
that emphasizes new research, development and their applications. IJTSRD provides
an online access to exchange your research work, technical notes & surveying results
among professionals throughout the world in e-journals. IJTSRD is a fastest growing
and dynamic professional organization. The aim of this organization is to provide
access not only to world class research resources, but through its professionals
aim to bring in a significant transformation in the real of open access journals
and online publishing.