• ISSN: 2349-6002
  • UGC Approved Journal No 47859
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Enhancing Real-Time Data Processing for Neuroscience with AWS: Challenges and Solutions

  • Unique Paper ID: 167454
  • Volume: 9
  • Issue: 10
  • PageNo: 1057-1067
  • Abstract:
  • Neuroscience research increasingly relies on real-time data processing to analyze complex neural signals, enabling discoveries that advance our understanding of the brain. The demand for rapid data processing and analysis has led researchers to explore cloud-based solutions like Amazon Web Services (AWS) to handle the massive volumes of data generated by modern neuroscience experiments. This paper examines the challenges and solutions associated with enhancing real-time data processing for neuroscience using AWS. The key challenges include data latency, bandwidth limitations, and the complexity of integrating diverse data sources. Additionally, the need for high computational power and efficient data storage solutions poses significant hurdles. AWS offers a suite of services, such as AWS Lambda, Amazon S3, and AWS IoT, that can be leveraged to address these challenges. Solutions discussed in this paper include implementing serverless architectures to reduce latency, utilizing scalable storage options to manage data efficiently, and employing machine learning models for rapid data analysis. We also explore case studies where AWS has been successfully implemented in neuroscience research, highlighting the benefits of cloud computing in improving the speed and accuracy of data analysis. This paper provides a comprehensive overview of how AWS can be harnessed to overcome the challenges of real-time data processing in neuroscience, ultimately enhancing research capabilities and outcomes.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 9
  • Issue: 10
  • PageNo: 1057-1067

Enhancing Real-Time Data Processing for Neuroscience with AWS: Challenges and Solutions

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