https://github.com/hatim001/temperature-analysis-aws-stack
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (8.9%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: Hatim001
- License: mit
- Language: Python
- Default Branch: main
- Size: 1.15 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Temperature Analysis Service - AWS Stack
Overview
The Temperature Analysis service is a robust AWS cloud-based solution designed to process and monitor temperature data in real time. It detects anomalies, alerts stakeholders, and provides statistical analysis through a user-friendly API.
Architecture
The architecture is serverless and event-driven, ensuring scalability and cost-efficiency:
- EC2 Instances: Simulate temperature data streams using the
temperature_simulation.pyscript. - Kinesis Data Stream: Captures the simulated temperature data for real-time processing.
- Kinesis Data Firehose: Batches the data and prepares it for processing.
- Lambda Functions: (
processor.pyandstatistics.py) process the incoming data to detect anomalies, store the results, and calculate statistics. - Amazon RDS: Stores the processed data, allowing for complex queries.
- Amazon S3: Holds raw data and scripts for the simulation and Lambda functions.
- Amazon SNS: Manages temperature spike alerts and sends notifications.
- API Gateway: Interfaces with Lambda to provide a RESTful API to users.
The provided architecture.png illustrates how each component interacts within the AWS ecosystem to deliver this service.
Folder Structure
- LICENSE: Contains the license details for the project.
- README.md: This file, which provides project documentation.
- aws/:
architecture.png: The image file of the service architecture.cloud_formation.json: CloudFormation template for deploying AWS resources.
- data/:
IOT-temp.csv: Sample CSV file with IoT temperature data.
- lambda/:
processor.py: Lambda function for processing data from Kinesis.statistics.py: Lambda function for computing temperature statistics.- zips/: Zipped packages of Lambda functions for deployment.
processor.zipstatistics.zip
- simulation/:
temperature_simulation.py: Script to simulate temperature data generation.
Deployment
The service is deployed using the cloud_formation.json CloudFormation template, which provisions all necessary AWS resources and configures them accordingly.
License
This project is licensed under the MIT License - see the file for details.
Owner
- Login: Hatim001
- Kind: user
- Repositories: 1
- Profile: https://github.com/Hatim001