Enhancing Biotechnological Research with Blockchain-Enhanced Big Data Platforms

Abstract

This paper addresses challenges in constructing a Hadoop cluster big data visualization platform, such as low accuracy and throughput in data acquisition and significant error rates. It proposes integrating blockchain technology to enhance the platform's capabilities. By employing FCM clustering and wavelet neural networks for load prediction and data classification, and executing these processes on a distributed platform, the system achieves improved data visualization and accuracy. The methodology involves advanced data handling from collection through wireless transmission to processing, showing promising enhancements in data acquisition accuracy and throughput, as well as reduced transmission errors. This approach exemplifies the potential of blockchain to improve data management systems in biotechnological applications, aligning well with the journal's focus on innovative biotechnological data solutions.