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G-DaM: A Distributed Data Storage with Blockchain Framework for Management of Groundwater Quality Data
Sukrutha L T Vangipuram1, Saraju P Mohanty2, Elias Kougianos2
1Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, USA.
This study introduces a secure method for collecting groundwater data using Distributed Data Storage (DDS) and Blockchain (BC) technologies. This approach enhances data integrity and quality, crucial for addressing global freshwater scarcity.
Area of Science:
- Environmental Science
- Computer Science
- Data Security
Background:
- Groundwater overuse is a significant driver of global freshwater scarcity.
- Accurate forecasting of groundwater availability is essential for resource management.
- Secure and reliable data collection is a major challenge in groundwater studies.
Purpose of the Study:
- To develop an innovative approach for secure groundwater data transmission and storage.
- To combine Distributed Data Storage (DDS) and Blockchain (BC) technologies for enhanced data management.
- To address limitations of traditional centralized data storage and sharing methods.
Main Methods:
- Raw data from the Internet of Things (IoT) is transmitted to DDS and BC edges.
- A distributed and decentralized architecture is employed for data storage.
- Double hashing and smart contracts are utilized for data integrity and access control.
Main Results:
- The proposed system ensures secure data transmission, preventing hacking and tampering.
- Implementation of DDS and BC technologies demonstrated improved data quality and integrity.
- The decentralized architecture overcomes challenges associated with centralized storage.
Conclusions:
- Combining DDS and BC offers a modern, secure solution for groundwater data management.
- This approach enhances the reliability of groundwater availability forecasting.
- The study highlights the potential of integrating distributed storage and blockchain for environmental data security.
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