diff --git a/android-project/app/src/main/java/com/photobooth/app/MainActivity.kt b/android-project/app/src/main/java/com/photobooth/app/MainActivity.kt
index 01988a6..7b70ac3 100644
--- a/android-project/app/src/main/java/com/photobooth/app/MainActivity.kt
+++ b/android-project/app/src/main/java/com/photobooth/app/MainActivity.kt
@@ -67,48 +67,79 @@ class MainActivity : AppCompatActivity() {
     private lateinit var backgroundOptions: List<BackgroundOption>
     private val aiInferenceLock = Any()
     private var imageSegmenter: ImageSegmenter? = null
+    private var isAiSupported = true
 
-    private fun getImageSegmenter(): ImageSegmenter {
+    private fun getImageSegmenter(): ImageSegmenter? {
         synchronized(aiInferenceLock) {
+            if (!isAiSupported) return null
             if (imageSegmenter == null) {
-                val baseOptions = BaseOptions.builder()
-                    .setModelAssetPath("models/multiclass_segmenter.tflite")
-                    .build()
+                try {
+                    val baseOptions = BaseOptions.builder()
+                        .setModelAssetPath("models/multiclass_segmenter.tflite")
+                        .build()
 
-                val options = ImageSegmenterOptions.builder()
-                    .setBaseOptions(baseOptions)
-                    .setOutputCategoryMask(true)
-                    .setOutputConfidenceMasks(false)
-                    .build()
+                    val options = ImageSegmenterOptions.builder()
+                        .setBaseOptions(baseOptions)
+                        .setOutputCategoryMask(true)
+                        .setOutputConfidenceMasks(false)
+                        .build()
 
-                imageSegmenter = ImageSegmenter.createFromOptions(this, options)
+                    imageSegmenter = ImageSegmenter.createFromOptions(this, options)
+                } catch (e: UnsatisfiedLinkError) {
+                    isAiSupported = false
+                    runOnUiThread {
+                        Toast.makeText(this, "Không hỗ trợ xử lý AI trên thiết bị/emulator này (thiếu thư viện Native JNI)", Toast.LENGTH_LONG).show()
+                    }
+                    return null
+                } catch (e: Exception) {
+                    isAiSupported = false
+                    runOnUiThread {
+                        Toast.makeText(this, "Lỗi khởi tạo AI Segmenter: ${e.message}", Toast.LENGTH_LONG).show()
+                    }
+                    return null
+                }
             }
-            return imageSegmenter!!
+            return imageSegmenter
         }
     }
 
     private var tfliteInterpreter: org.tensorflow.lite.Interpreter? = null
 
-    private fun getTfliteInterpreter(): org.tensorflow.lite.Interpreter {
+    private fun getTfliteInterpreter(): org.tensorflow.lite.Interpreter? {
         synchronized(aiInferenceLock) {
+            if (!isAiSupported) return null
             if (tfliteInterpreter == null) {
-                val assetFileDescriptor = assets.openFd("models/midas.tflite")
-                val inputStream = java.io.FileInputStream(assetFileDescriptor.fileDescriptor)
-                val fileChannel = inputStream.channel
-                val startOffset = assetFileDescriptor.startOffset
-                val declaredLength = assetFileDescriptor.declaredLength
-                val modelBuffer = fileChannel.map(java.nio.channels.FileChannel.MapMode.READ_ONLY, startOffset, declaredLength)
-                
-                val options = org.tensorflow.lite.Interpreter.Options()
-                options.setNumThreads(4)
-                tfliteInterpreter = org.tensorflow.lite.Interpreter(modelBuffer, options)
+                try {
+                    val assetFileDescriptor = assets.openFd("models/midas.tflite")
+                    val inputStream = java.io.FileInputStream(assetFileDescriptor.fileDescriptor)
+                    val fileChannel = inputStream.channel
+                    val startOffset = assetFileDescriptor.startOffset
+                    val declaredLength = assetFileDescriptor.declaredLength
+                    val modelBuffer = fileChannel.map(java.nio.channels.FileChannel.MapMode.READ_ONLY, startOffset, declaredLength)
+                    
+                    val options = org.tensorflow.lite.Interpreter.Options()
+                    options.setNumThreads(4)
+                    tfliteInterpreter = org.tensorflow.lite.Interpreter(modelBuffer, options)
+                } catch (e: UnsatisfiedLinkError) {
+                    isAiSupported = false
+                    runOnUiThread {
+                        Toast.makeText(this, "Không hỗ trợ xử lý Depth trên thiết bị/emulator này (thiếu thư viện Native JNI)", Toast.LENGTH_LONG).show()
+                    }
+                    return null
+                } catch (e: Exception) {
+                    isAiSupported = false
+                    runOnUiThread {
+                        Toast.makeText(this, "Lỗi khởi tạo Depth Interpreter: ${e.message}", Toast.LENGTH_LONG).show()
+                    }
+                    return null
+                }
             }
-            return tfliteInterpreter!!
+            return tfliteInterpreter
         }
     }
 
     private fun runDepthInference(bitmap: android.graphics.Bitmap): FloatArray {
-        val interpreter = getTfliteInterpreter()
+        val interpreter = getTfliteInterpreter() ?: return FloatArray(256 * 256)
         
         // Input: 256x256 RGB
         val scaled = android.graphics.Bitmap.createScaledBitmap(bitmap, 256, 256, true)
@@ -1712,12 +1743,30 @@ class MainActivity : AppCompatActivity() {
         if (!isBgActive) {
             return capturedImage
         }
+
+        if (!isAiSupported) {
+            if (blurIntensity > 0f) {
+                val radius = (25 * blurIntensity).toInt().coerceIn(1, 25)
+                return blurBitmap(capturedImage, radius)
+            }
+            return capturedImage
+        }
         
         try {
+            val segmenter = getImageSegmenter()
+            val interpreter = getTfliteInterpreter()
+            if (segmenter == null || interpreter == null) {
+                if (blurIntensity > 0f) {
+                    val radius = (25 * blurIntensity).toInt().coerceIn(1, 25)
+                    return blurBitmap(capturedImage, radius)
+                }
+                return capturedImage
+            }
+
             // 1. Run MediaPipe Multiclass Image Segmentation to locate subject
             val mpImage = com.google.mediapipe.framework.image.BitmapImageBuilder(capturedImage).build()
             val segmentationResult = synchronized(aiInferenceLock) {
-                getImageSegmenter().segment(mpImage)
+                segmenter.segment(mpImage)
             }
             val categoryMaskOptional = segmentationResult.categoryMask()
             if (!categoryMaskOptional.isPresent) {