Performance analysis of Cloud and IOT Health Care Data
Title: Securing Patient Data in Cloud-IoT using Data mining Techniques
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Implementation Plan:
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Step 1: Initially, We Collect and Load the Cleveland Heart Disease dataset for Data Collection Process.
Step 2: Next, We preprocess the Loaded data using Synthetic Minority Oversampling Technique (SMOTE)
Step 3: Next, We perform the Feature extraction process using Principal Component Analysis (PCA) Method.
Step 4: Next, We perform classification process using Generative Adversarial Networks(GAN) with Adaptive Moment Estimation optimization algorithm.
Step 5: Next, We Transmit the data to the Cloud environment to reduce storage issues and guarantee immediate access to vital information.
Step 5.1: This process starts with the encryption and decryption of data using Homomorphic encryption with the Laplacian technique.
Step 5.2: Next, We Perform the Routing process using Leach protocol to optimize energy consumption and communication efficiency.
Step 5.3: Next, we store the data in the Cloud Architecture server.
Step 6: Next, we implement Healthcare Monitoring in IoT to provide effective and timely patient care.
Step 7: Finally, The proposed work is verified using performance metrics such as
7.1: Number of Epochs vs. accuracy (%)
7.2: Number of Epochs vs. Precision (%)
7.3: Number of Users vs. Authentication Time(s)
7.4: Number of Users vs. Throughput (%)
7.5: Number of User vs. Packet Delivery Ratio (%)
Dataset Link:
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https://www.kaggle.com/datasets/aavig...
Software Requirement:
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1. Development Tool: Python – 3.11.6
2. Operating System: Windows 10 (64-bit)
Note:
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1) If the above plan does not satisfy your requirement, please provide the processing details, like the above step-by-step.
2) Please note that this implementation plan does not include any further steps after it is put into implementation.
3) This project is only based on simulations. Not a real time project.
4) If the above plan satisfies your requirement please confirm with us.
Existing:
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We perform the EXISTING process based on the Reference 1: Title: IoT-Cloud-Based Smart Healthcare Monitoring System for Heart Disease Prediction via Deep Learning
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