TRANSFORMING ASSET MANAGEMENT WITH GRAPH DATABASES
Our research, “Unleashing the Potential of Graph Database in Smart Asset Management: Enhancing Predictive Maintenance in Industry 4.0” explores into how graph databases can revolutionize predictive maintenance for smarter asset management.
In the era of Industry 4.0, managing massive amounts of data from various sources is a challenge. Our study highlights how graph databases, with their flexibility and scalability, can handle this complexity, making data more accessible and useful for predictive maintenance.
We explore the use of graph databases to store and analyze asset information, showcasing their ability to handle complex relationships and vast data volumes. This approach enhances predictive maintenance by providing more accurate and timely insights.
By integrating advanced technologies like big data, IoT, and AI, we pave the way for smarter, more efficient asset management. Our research demonstrates the potential of graph databases to support the dynamic needs of modern industries.
Discover more about how we’re pushing the boundaries of smart asset management: https://doi.org/10.1007/978-3-031-53824-7_2