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c6da498 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | import gradio as gr
import random
def analyze_data(data_source, timeframe, metric):
data_points = random.randint(5000, 50000)
avg_value = round(random.uniform(20, 80), 2)
peak = round(random.uniform(80, 100), 2)
anomalies = random.randint(0, 15)
result = f"""### IoT Data Analysis Results
**Data Source**: {data_source}
**Timeframe**: {timeframe}
**Metric**: {metric}
📊 **Analysis Summary**:
- Total Data Points: {data_points:,}
- Average Value: {avg_value}
- Peak Value: {peak}
- Anomalies Detected: {anomalies}
- Data Quality Score: {round(random.uniform(85, 99), 1)}%
**Insights**: The IoT data shows {'consistent patterns' if anomalies < 5 else 'some irregularities'} over the {timeframe.lower()} period.
---
**Anktechsol** - IoT Analytics Platform
🔗 [Visit anktechsol.com](https://anktechsol.com)"""
return result
with gr.Blocks(title="IoT Data Analyzer") as demo:
gr.Markdown("# 📊 IoT Data Analytics Platform")
gr.Markdown("Advanced IoT data insights - **Anktechsol**")
with gr.Row():
with gr.Column():
source = gr.Dropdown(["Temperature Sensors", "Humidity Sensors", "Pressure Sensors", "Motion Detectors"], label="Data Source", value="Temperature Sensors")
time = gr.Radio(["Last Hour", "Last 24 Hours", "Last 7 Days", "Last 30 Days"], label="Timeframe", value="Last 24 Hours")
metric = gr.Dropdown(["Average", "Peak", "Trend Analysis", "Anomaly Detection"], label="Analysis Metric", value="Average")
btn = gr.Button("Analyze Data")
with gr.Column():
output = gr.Markdown()
btn.click(analyze_data, inputs=[source, time, metric], outputs=output)
gr.Markdown("""---
### Anktechsol - IoT Analytics Experts
Comprehensive IoT data solutions. [Contact us](https://anktechsol.com)""")
demo.launch() |