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RSK World
iot-sensors
RSK World
iot-sensors
IoT Sensors Dataset - Time Series Analysis + Anomaly Detection + Sensor Fusion + Predictive Maintenance
iot-sensors
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  • .gitignore386 B
  • LICENSE1.2 KB
  • PROJECT_INFO.md3.3 KB
  • README.md7.7 KB
  • index.html25.9 KB
  • iot-sensors.zip58.6 KB
  • requirements.txt289 B
index.html
index.html
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<!DOCTYPE html>
<!--
    IoT Sensor Dataset - Demo Page
    Website: https://rskworld.in
    Email: help@rskworld.in
    Phone: +91 93305 39277
    Author: RSK World
-->
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>IoT Sensor Dataset - RSK World</title>
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    <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
    <style>
        body {
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
            min-height: 100vh;
            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
        }
        .header-section {
            background: rgba(255, 255, 255, 0.95);
            padding: 2rem 0;
            box-shadow: 0 2px 10px rgba(0,0,0,0.1);
        }
        .card {
            border: none;
            border-radius: 15px;
            box-shadow: 0 4px 15px rgba(0,0,0,0.1);
            margin-bottom: 2rem;
            transition: transform 0.3s;
        }
        .card:hover {
            transform: translateY(-5px);
        }
        .card-header {
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
            color: white;
            border-radius: 15px 15px 0 0 !important;
            padding: 1.5rem;
        }
        .sensor-badge {
            display: inline-block;
            padding: 0.5rem 1rem;
            border-radius: 20px;
            margin: 0.25rem;
            font-size: 0.9rem;
        }
        .badge-temp { background: #ff6b6b; color: white; }
        .badge-humidity { background: #4ecdc4; color: white; }
        .badge-pressure { background: #45b7d1; color: white; }
        .badge-motion { background: #f9ca24; color: #333; }
        .btn-purple { background: #6f42c1; color: white; }
        .btn-purple:hover { background: #5a32a3; color: white; }
        .stats-card {
            text-align: center;
            padding: 1.5rem;
        }
        .stats-value {
            font-size: 2.5rem;
            font-weight: bold;
            color: #667eea;
        }
        .footer {
            background: rgba(255, 255, 255, 0.95);
            padding: 2rem 0;
            margin-top: 3rem;
        }
    </style>
</head>
<body>
    <!-- Header Section -->
    <div class="header-section">
        <div class="container">
            <div class="row align-items-center">
                <div class="col-md-8">
                    <h1 class="mb-2"><i class="fas fa-clock text-success"></i> IoT Sensor Dataset</h1>
                    <p class="lead text-muted">Multi-sensor IoT data for analytics, anomaly detection, and sensor fusion</p>
                </div>
                <div class="col-md-4 text-end">
                    <a href="https://rskworld.in" class="btn btn-outline-primary" target="_blank">
                        <i class="fas fa-globe"></i> Visit RSK World
                    </a>
                </div>
            </div>
        </div>
    </div>

    <div class="container my-5">
        <!-- Dataset Info -->
        <div class="card mb-4">
            <div class="card-header">
                <h3 class="mb-0"><i class="fas fa-info-circle"></i> Dataset Information</h3>
            </div>
            <div class="card-body">
                <div class="row">
                    <div class="col-md-6">
                        <h5>Category: <span class="badge bg-primary">Time Series Data</span></h5>
                        <h5>Difficulty: <span class="badge bg-danger">Advanced</span></h5>
                        <p class="mt-3"><strong>Description:</strong></p>
                        <p>This dataset contains multi-sensor IoT data with temperature, humidity, pressure, motion, and other sensor readings over time. Perfect for IoT analytics, anomaly detection, predictive maintenance, and sensor fusion applications.</p>
                    </div>
                    <div class="col-md-6">
                        <h5>Technologies:</h5>
                        <span class="badge bg-secondary sensor-badge">CSV</span>
                        <span class="badge bg-secondary sensor-badge">JSON</span>
                        <span class="badge bg-secondary sensor-badge">Pandas</span>
                        <span class="badge bg-secondary sensor-badge">Time Series</span>
                        <h5 class="mt-4">Features:</h5>
                        <ul>
                            <li>Multi-sensor data</li>
                            <li>Temporal patterns</li>
                            <li>Anomaly labels</li>
                            <li>Multiple devices</li>
                            <li>Sensor fusion ready</li>
                        </ul>
                    </div>
                </div>
            </div>
        </div>

        <!-- Statistics Cards -->
        <div class="row mb-4">
            <div class="col-md-3">
                <div class="card stats-card">
                    <div class="stats-value" id="totalReadings">0</div>
                    <div class="text-muted">Total Readings</div>
                </div>
            </div>
            <div class="col-md-3">
                <div class="card stats-card">
                    <div class="stats-value" id="totalDevices">0</div>
                    <div class="text-muted">Devices</div>
                </div>
            </div>
            <div class="col-md-3">
                <div class="card stats-card">
                    <div class="stats-value" id="avgTemp">0°C</div>
                    <div class="text-muted">Avg Temperature</div>
                </div>
            </div>
            <div class="col-md-3">
                <div class="card stats-card">
                    <div class="stats-value" id="anomalies">0</div>
                    <div class="text-muted">Anomalies</div>
                </div>
            </div>
        </div>

        <!-- Charts -->
        <div class="row">
            <div class="col-md-6">
                <div class="card">
                    <div class="card-header">
                        <h5 class="mb-0"><i class="fas fa-chart-line"></i> Temperature & Humidity Over Time</h5>
                    </div>
                    <div class="card-body">
                        <canvas id="tempHumidityChart"></canvas>
                    </div>
                </div>
            </div>
            <div class="col-md-6">
                <div class="card">
                    <div class="card-header">
                        <h5 class="mb-0"><i class="fas fa-chart-area"></i> Pressure Readings</h5>
                    </div>
                    <div class="card-body">
                        <canvas id="pressureChart"></canvas>
                    </div>
                </div>
            </div>
        </div>

        <div class="row mt-4">
            <div class="col-md-6">
                <div class="card">
                    <div class="card-header">
                        <h5 class="mb-0"><i class="fas fa-chart-pie"></i> Sensor Distribution by Device</h5>
                    </div>
                    <div class="card-body">
                        <canvas id="deviceChart"></canvas>
                    </div>
                </div>
            </div>
            <div class="col-md-6">
                <div class="card">
                    <div class="card-header">
                        <h5 class="mb-0"><i class="fas fa-exclamation-triangle"></i> Anomaly Detection</h5>
                    </div>
                    <div class="card-body">
                        <canvas id="anomalyChart"></canvas>
                    </div>
                </div>
            </div>
        </div>

        <!-- Data Preview -->
        <div class="card mt-4">
            <div class="card-header">
                <h5 class="mb-0"><i class="fas fa-table"></i> Data Preview</h5>
            </div>
            <div class="card-body">
                <div class="table-responsive">
                    <table class="table table-striped table-hover" id="dataTable">
                        <thead>
                            <tr>
                                <th>Timestamp</th>
                                <th>Device ID</th>
                                <th>Temperature (°C)</th>
                                <th>Humidity (%)</th>
                                <th>Pressure (hPa)</th>
                                <th>Motion</th>
                                <th>Anomaly</th>
                            </tr>
                        </thead>
                        <tbody id="tableBody">
                        </tbody>
                    </table>
                </div>
            </div>
        </div>

        <!-- Download Section -->
        <div class="card mt-4">
            <div class="card-header">
                <h5 class="mb-0"><i class="fas fa-download"></i> Download Dataset</h5>
            </div>
            <div class="card-body">
                <div class="row">
                    <div class="col-md-6">
                        <h6>Available Formats:</h6>
                        <a href="data/iot_sensors.csv" class="btn btn-primary me-2" download>
                            <i class="fas fa-file-csv"></i> Download CSV
                        </a>
                        <a href="data/iot_sensors.json" class="btn btn-success me-2" download>
                            <i class="fas fa-file-code"></i> Download JSON
                        </a>
                        <a href="iot-sensors.zip" class="btn btn-warning" download>
                            <i class="fas fa-file-archive"></i> Download ZIP
                        </a>
                    </div>
                    <div class="col-md-6">
                        <h6>Python Analysis Scripts:</h6>
                        <a href="scripts/analyze_sensors.py" class="btn btn-info me-2 mb-2" download>
                            <i class="fab fa-python"></i> Analysis Script
                        </a>
                        <a href="scripts/anomaly_detection.py" class="btn btn-info me-2 mb-2" download>
                            <i class="fas fa-bug"></i> Anomaly Detection
                        </a>
                        <a href="scripts/ml_prediction.py" class="btn btn-danger me-2 mb-2" download>
                            <i class="fas fa-brain"></i> ML Prediction
                        </a>
                        <a href="scripts/sensor_fusion.py" class="btn btn-purple me-2 mb-2" download>
                            <i class="fas fa-project-diagram"></i> Sensor Fusion
                        </a>
                        <a href="scripts/real_time_simulator.py" class="btn btn-warning me-2 mb-2" download>
                            <i class="fas fa-stream"></i> Real-Time Simulator
                        </a>
                        <a href="scripts/api_server.py" class="btn btn-dark mb-2" download>
                            <i class="fas fa-server"></i> API Server
                        </a>
                    </div>
                </div>
            </div>
        </div>

        <!-- Advanced Features Section -->
        <div class="card mt-4">
            <div class="card-header">
                <h5 class="mb-0"><i class="fas fa-rocket"></i> Advanced Features</h5>
            </div>
            <div class="card-body">
                <div class="row">
                    <div class="col-md-4 mb-3">
                        <div class="card h-100 border-primary">
                            <div class="card-body">
                                <h6 class="card-title text-primary">
                                    <i class="fas fa-brain"></i> Machine Learning
                                </h6>
                                <p class="card-text small">
                                    <strong>ml_prediction.py</strong> - Advanced ML models including:
                                    <ul class="small">
                                        <li>Random Forest for anomaly classification</li>
                                        <li>Temperature prediction models</li>
                                        <li>Model training and evaluation</li>
                                        <li>Model persistence and loading</li>
                                    </ul>
                                </p>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-4 mb-3">
                        <div class="card h-100 border-success">
                            <div class="card-body">
                                <h6 class="card-title text-success">
                                    <i class="fas fa-project-diagram"></i> Sensor Fusion
                                </h6>
                                <p class="card-text small">
                                    <strong>sensor_fusion.py</strong> - Multiple fusion algorithms:
                                    <ul class="small">
                                        <li>Weighted average fusion</li>
                                        <li>Kalman filter fusion</li>
                                        <li>Bayesian sensor fusion</li>
                                        <li>Multi-sensor integration</li>
                                    </ul>
                                </p>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-4 mb-3">
                        <div class="card h-100 border-warning">
                            <div class="card-body">
                                <h6 class="card-title text-warning">
                                    <i class="fas fa-stream"></i> Real-Time Simulator
                                </h6>
                                <p class="card-text small">
                                    <strong>real_time_simulator.py</strong> - Live data streaming:
                                    <ul class="small">
                                        <li>Real-time data generation</li>
                                        <li>Streaming simulation</li>
                                        <li>Batch data generation</li>
                                        <li>CSV/JSON export</li>
                                    </ul>
                                </p>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-4 mb-3">
                        <div class="card h-100 border-info">
                            <div class="card-body">
                                <h6 class="card-title text-info">
                                    <i class="fas fa-server"></i> REST API
                                </h6>
                                <p class="card-text small">
                                    <strong>api_server.py</strong> - Flask RESTful API:
                                    <ul class="small">
                                        <li>GET /api/data - Retrieve data</li>
                                        <li>GET /api/stats - Statistics</li>
                                        <li>POST /api/data - Add readings</li>
                                        <li>GET /api/anomalies - Anomaly data</li>
                                    </ul>
                                </p>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-4 mb-3">
                        <div class="card h-100 border-danger">
                            <div class="card-body">
                                <h6 class="card-title text-danger">
                                    <i class="fas fa-bug"></i> Anomaly Detection
                                </h6>
                                <p class="card-text small">
                                    <strong>anomaly_detection.py</strong> - Multiple algorithms:
                                    <ul class="small">
                                        <li>Z-Score method</li>
                                        <li>Isolation Forest</li>
                                        <li>Local Outlier Factor (LOF)</li>
                                        <li>Method comparison</li>
                                    </ul>
                                </p>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-4 mb-3">
                        <div class="card h-100 border-secondary">
                            <div class="card-body">
                                <h6 class="card-title text-secondary">
                                    <i class="fas fa-chart-line"></i> Data Analysis
                                </h6>
                                <p class="card-text small">
                                    <strong>analyze_sensors.py</strong> - Comprehensive analysis:
                                    <ul class="small">
                                        <li>Statistical analysis</li>
                                        <li>Temporal patterns</li>
                                        <li>Device comparisons</li>
                                        <li>Correlation analysis</li>
                                    </ul>
                                </p>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
        </div>
    </div>

    <!-- Footer -->
    <div class="footer">
        <div class="container text-center">
            <p class="mb-2">
                <strong>IoT Sensor Dataset</strong> - Created by 
                <a href="https://rskworld.in" target="_blank">RSK World</a>
            </p>
            <p class="text-muted small mb-0">
                Email: <a href="mailto:help@rskworld.in">help@rskworld.in</a> | 
                Phone: <a href="tel:+919330539277">+91 93305 39277</a> | 
                Website: <a href="https://rskworld.in" target="_blank">rskworld.in</a>
            </p>
        </div>
    </div>

    <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0/dist/js/bootstrap.bundle.min.js"></script>
    <script>
        // Sample data generation
        function generateSampleData() {
            const devices = ['DEV001', 'DEV002', 'DEV003', 'DEV004', 'DEV005'];
            const data = [];
            const now = new Date();
            
            for (let i = 0; i < 100; i++) {
                const timestamp = new Date(now - (100 - i) * 60000); // Every minute
                const deviceId = devices[Math.floor(Math.random() * devices.length)];
                const temp = 20 + Math.random() * 15 + (Math.random() > 0.9 ? 10 : 0); // Occasional spike
                const humidity = 40 + Math.random() * 40;
                const pressure = 980 + Math.random() * 40;
                const motion = Math.random() > 0.7 ? 1 : 0;
                const anomaly = (temp > 32 || humidity < 20 || pressure < 990) ? 1 : 0;
                
                data.push({
                    timestamp: timestamp.toISOString(),
                    device_id: deviceId,
                    temperature: parseFloat(temp.toFixed(2)),
                    humidity: parseFloat(humidity.toFixed(2)),
                    pressure: parseFloat(pressure.toFixed(2)),
                    motion: motion,
                    anomaly: anomaly
                });
            }
            return data;
        }

        const sensorData = generateSampleData();

        // Update statistics
        document.getElementById('totalReadings').textContent = sensorData.length;
        document.getElementById('totalDevices').textContent = new Set(sensorData.map(d => d.device_id)).size;
        const avgTemp = sensorData.reduce((sum, d) => sum + d.temperature, 0) / sensorData.length;
        document.getElementById('avgTemp').textContent = avgTemp.toFixed(1) + '°C';
        document.getElementById('anomalies').textContent = sensorData.filter(d => d.anomaly === 1).length;

        // Temperature & Humidity Chart
        const tempHumidityCtx = document.getElementById('tempHumidityChart').getContext('2d');
        new Chart(tempHumidityCtx, {
            type: 'line',
            data: {
                labels: sensorData.map(d => new Date(d.timestamp).toLocaleTimeString()),
                datasets: [{
                    label: 'Temperature (°C)',
                    data: sensorData.map(d => d.temperature),
                    borderColor: 'rgb(255, 99, 132)',
                    backgroundColor: 'rgba(255, 99, 132, 0.2)',
                    yAxisID: 'y'
                }, {
                    label: 'Humidity (%)',
                    data: sensorData.map(d => d.humidity),
                    borderColor: 'rgb(54, 162, 235)',
                    backgroundColor: 'rgba(54, 162, 235, 0.2)',
                    yAxisID: 'y1'
                }]
            },
            options: {
                responsive: true,
                scales: {
                    y: {
                        type: 'linear',
                        position: 'left',
                        title: { display: true, text: 'Temperature (°C)' }
                    },
                    y1: {
                        type: 'linear',
                        position: 'right',
                        title: { display: true, text: 'Humidity (%)' },
                        grid: { drawOnChartArea: false }
                    }
                }
            }
        });

        // Pressure Chart
        const pressureCtx = document.getElementById('pressureChart').getContext('2d');
        new Chart(pressureCtx, {
            type: 'line',
            data: {
                labels: sensorData.map(d => new Date(d.timestamp).toLocaleTimeString()),
                datasets: [{
                    label: 'Pressure (hPa)',
                    data: sensorData.map(d => d.pressure),
                    borderColor: 'rgb(75, 192, 192)',
                    backgroundColor: 'rgba(75, 192, 192, 0.2)',
                    fill: true
                }]
            },
            options: {
                responsive: true,
                scales: {
                    y: {
                        title: { display: true, text: 'Pressure (hPa)' }
                    }
                }
            }
        });

        // Device Distribution Chart
        const deviceCtx = document.getElementById('deviceChart').getContext('2d');
        const deviceCounts = {};
        sensorData.forEach(d => {
            deviceCounts[d.device_id] = (deviceCounts[d.device_id] || 0) + 1;
        });
        new Chart(deviceCtx, {
            type: 'doughnut',
            data: {
                labels: Object.keys(deviceCounts),
                datasets: [{
                    data: Object.values(deviceCounts),
                    backgroundColor: [
                        'rgba(255, 99, 132, 0.8)',
                        'rgba(54, 162, 235, 0.8)',
                        'rgba(255, 206, 86, 0.8)',
                        'rgba(75, 192, 192, 0.8)',
                        'rgba(153, 102, 255, 0.8)'
                    ]
                }]
            },
            options: {
                responsive: true
            }
        });

        // Anomaly Chart
        const anomalyCtx = document.getElementById('anomalyChart').getContext('2d');
        const anomalyData = sensorData.map((d, index) => ({
            x: index,
            y: d.temperature,
            anomaly: d.anomaly,
            timestamp: new Date(d.timestamp).toLocaleTimeString()
        }));
        new Chart(anomalyCtx, {
            type: 'scatter',
            data: {
                datasets: [{
                    label: 'Normal',
                    data: anomalyData.filter(d => d.anomaly === 0).map(d => ({x: d.x, y: d.y})),
                    backgroundColor: 'rgba(54, 162, 235, 0.6)'
                }, {
                    label: 'Anomaly',
                    data: anomalyData.filter(d => d.anomaly === 1).map(d => ({x: d.x, y: d.y})),
                    backgroundColor: 'rgba(255, 99, 132, 0.6)'
                }]
            },
            options: {
                responsive: true,
                scales: {
                    x: {
                        type: 'linear',
                        title: { display: true, text: 'Reading Index' }
                    },
                    y: {
                        title: { display: true, text: 'Temperature (°C)' }
                    }
                }
            }
        });

        // Populate table
        const tableBody = document.getElementById('tableBody');
        sensorData.slice(0, 20).forEach(row => {
            const tr = document.createElement('tr');
            tr.innerHTML = `
                <td>${new Date(row.timestamp).toLocaleString()}</td>
                <td>${row.device_id}</td>
                <td>${row.temperature.toFixed(2)}</td>
                <td>${row.humidity.toFixed(2)}</td>
                <td>${row.pressure.toFixed(2)}</td>
                <td><span class="badge ${row.motion ? 'bg-success' : 'bg-secondary'}">${row.motion ? 'Yes' : 'No'}</span></td>
                <td><span class="badge ${row.anomaly ? 'bg-danger' : 'bg-success'}">${row.anomaly ? 'Yes' : 'No'}</span></td>
            `;
            tableBody.appendChild(tr);
        });
    </script>
</body>
</html>
585 lines•25.9 KB
markup

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