Create app.py

app.py

@@ -0,0 +1,50 @@
+import gradio as gr
+import random
+
+def simulate_edge(device_type, ai_model, edge_location):
+    latency = round(random.uniform(2, 25), 1)
+    accuracy = round(random.uniform(88, 99), 1)
+    power = round(random.uniform(2, 12), 1)
+    throughput = random.randint(15, 120)
+    
+    result = f"""### AIoT Edge Simulation Results
+
+**Device Type**: {device_type}  
+**AI Model**: {ai_model}  
+**Edge Location**: {edge_location}
+
+🎮 **Simulation Metrics**:
+- Inference Latency: {latency}ms
+- Model Accuracy: {accuracy}%
+- Power Consumption: {power}W
+- Throughput: {throughput} inferences/sec
+- Edge Processing: {'Enabled' if random.choice([True, False]) else 'Cloud Fallback'}
+
+**Status**: ✅ Simulation completed successfully
+
+---
+**Anktechsol** - AIoT & Edge AI Solutions  
+🔗 [Visit anktechsol.com](https://anktechsol.com)"""
+    return result
+
+with gr.Blocks(title="AIoT Edge Simulator") as demo:
+    gr.Markdown("# 🌐 AIoT & Edge AI Simulator")
+    gr.Markdown("Test AIoT deployments - **Anktechsol**")
+    
+    with gr.Row():
+        with gr.Column():
+            device = gr.Dropdown(["Raspberry Pi 4", "Jetson Nano", "AWS IoT Greengrass", "Azure IoT Edge"], label="Edge Device", value="Raspberry Pi 4")
+            model = gr.Dropdown(["Object Detection", "Image Classification", "Anomaly Detection", "Predictive Model"], label="AI Model", value="Object Detection")
+            location = gr.Radio(["Factory Floor", "Warehouse", "Retail Store", "Remote Site"], label="Deployment Location", value="Factory Floor")
+            btn = gr.Button("Run Simulation")
+        
+        with gr.Column():
+            output = gr.Markdown()
+    
+    btn.click(simulate_edge, inputs=[device, model, location], outputs=output)
+    
+    gr.Markdown("""---
+### Anktechsol - AIoT Specialists
+Edge AI deployment & AIoT consulting. [Get started](https://anktechsol.com)""")
+
+demo.launch()