Smart water meter data analyzed to solve water issues through the Concepts of DataBase management System
This repository contains the code and documentation for our Smart Water Meter Data Analysis project, developed by a team of students from the Amrita School of Computing, Coimbatore. Our goal is to utilize smart water meter technology to solve water-related issues by detecting inappropriate water consumption and improving water management.
Traditional water meters have limitations when it comes to reducing water wastage and identifying losses due to leaks, frauds, and defective meters. Our project aims to address these issues by leveraging smart water meter technology. By analyzing the collected data, we can detect anomalies and provide valuable insights for better water management.
- Remote monitoring of water consumption and infrastructure maintenance through leak detection.
- Automatic billing and customer management for efficient water utility services.
- Battery-powered smart water meters that support system configuration and enable easy installation.
- Conservation of water resources by identifying inappropriate water consumption patterns.
- Improved accuracy and efficiency compared to traditional water meters.
- Front-end: HTML, CSS, JavaScript (for creating the user interface web page)
- Database: Live SQL Server & pgAdmin 4 (for storing and managing the collected data)
- Identification and analysis of different types of smart water meters and their specifications.
- Examination of subscriber data, including Meter ID, Subscriber ID, meter capacity, mobile number, type of residence, and address/locality.
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Clone this repository to your local machine using the following command:
git clone https://github.com/Harsha-Vardhan-Tangudu/smart-water-meter-data-analysis.git -
Open the project in your preferred code editor.
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Set up the necessary front-end components and dependencies using HTML, CSS, and JavaScript.
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Configure the database connection to Live SQL Server and pgAdmin 4 for data storage and retrieval.
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Implement the required data analysis algorithms and visualizations based on your project requirements.
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Test the project thoroughly and make any necessary adjustments.
We welcome contributions from the open-source community to enhance this project and make it more impactful. If you would like to contribute, please follow these steps:
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Fork this repository.
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Create a new branch with a descriptive name for your feature or bug fix.
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Make your changes and ensure that the project is still functioning correctly.
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Commit your changes and push them to your forked repository.
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Submit a pull request, clearly documenting the changes you have made.
We appreciate your time and effort in helping us improve this project!
If you have any questions, suggestions, or would like to collaborate on this project, please feel free to reach out to us:
- Tangudu Harsha Vardhan: [LinkedIn](https://www.linkedin.com/in/tangudu-harsha-vardhan-2714971aa/)
Let's work together to make a positive impact on water management and conservation!