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Amazon EC2 request - Stevens Institute of Technology #31

@blackhawk70

Description

@blackhawk70

1. Requester Information:
Dr. Marouane Temimi
Associate Professor
Department of Civil, Environmental, and Ocean Engineering (CEOE)
Tel:+12012165303
Mail to: mtemimi@stevens.edu

2. Project Information:
The project aims to introduce an innovative, automated deep learning-based approach for near real-time satellite monitoring of river ice conditions within the northern watersheds of the United States and Canada. This technique harnesses high-resolution imagery from the VIIRS bands onboard the NOAA-20 and NPP satellites and utilizes the U-Net deep learning algorithm for the semantic segmentation of images, even under challenging conditions such as varying cloud cover and land surface variations.

3. Project Description:
The project involves the development of software and scripts in multiple programming languages, including Bash, MATLAB, Python, and the Google Earth Engine.

4. Resource Requirements:
CPUs: 30
Memory: 64 Gb
Network Bandwidth: at least 1Gbps
EBS bandwidth: at least 1Gbps
Disk size: at least 300Gb
OS: Linux (Ubuntu)
Root access required

Options:

  1. Cloud Provider: AWS

  2. Required Services in the Cloud:

    List of AWS Services

  • EC2

  • Amazon CloudWatch or Amazon Managed Grafana

    List of Azure Services

  • Virtual Machines

  • Azure File Storage

  • Azure Machine Learning

5. Timeline:
The project requires resources as soon as possible because the system is operational for Alaska, and it is currently winter, which is a critical period for river ice monitoring. The project is expected to run for a minimum of one year.

6. Security and Compliance Requirements:
No security and compliance requirements

7. Estimation:
Monthly: 624.15/Month for 1 year or 475.96/Month for 3 years

8. Approval:
Contact Dr. Marouane Temimi (contact info above)

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Need end dateProjects that need a documented end date.R2OHC Resource requestInfrastructure Request - Google, AWS, On-premisesawscloud

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