diff --git a/backend/export_to_onnx.py b/backend/export_to_onnx.py
new file mode 100644
index 0000000..b38942b
--- /dev/null
+++ b/backend/export_to_onnx.py
@@ -0,0 +1,89 @@
+import os
+import json
+import torch
+import torch.nn as nn
+from torchvision import models
+
+BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+MODEL_DIR = os.path.join(BASE_DIR, "model")
+CLASS_NAMES_PATH = os.path.join(MODEL_DIR, "class_names.json")
+MODEL_PATH = os.path.join(MODEL_DIR, "plant_disease_resnet18.pth")
+
+# Output paths
+FRONTEND_PUBLIC_DIR = os.path.join(os.path.dirname(BASE_DIR), "frontend", "public")
+ONNX_MODEL_DIR = os.path.join(FRONTEND_PUBLIC_DIR, "model")
+os.makedirs(ONNX_MODEL_DIR, exist_ok=True)
+ONNX_PATH = os.path.join(ONNX_MODEL_DIR, "plant_disease_resnet18.onnx")
+
+def export_model():
+    # Load class names
+    with open(CLASS_NAMES_PATH, "r") as f:
+        class_names = json.load(f)
+    num_classes = len(class_names)
+
+    print(f"[INFO] Loaded {num_classes} class names from {CLASS_NAMES_PATH}")
+
+    # Instantiate the ResNet18 model
+    model = models.resnet18(weights=None)
+    model.fc = nn.Linear(model.fc.in_features, num_classes)
+
+    # Load local fine-tuned weights if available
+    if os.path.exists(MODEL_PATH) and os.path.getsize(MODEL_PATH) > 0:
+        print(f"[INFO] Loading fine-tuned weights from {MODEL_PATH}...")
+        try:
+            model.load_state_dict(torch.load(MODEL_PATH, map_location="cpu"))
+            print("[INFO] Weights loaded successfully.")
+        except Exception as e:
+            print(f"[ERROR] Failed to load model weights: {e}")
+            raise
+    else:
+        raise FileNotFoundError(
+            f"Fine-tuned model weights not found at {MODEL_PATH}. "
+            "Please ensure you have placed the trained ResNet18 model (.pth file) in the backend/model/ directory before exporting."
+        )
+
+    model.eval()
+
+    # Preprocessing dummy input matching ImageNet requirements: 1 image, 3 channels, 224x224 shape
+    dummy_input = torch.randn(1, 3, 224, 224, requires_grad=False)
+
+    print(f"[INFO] Exporting PyTorch model to ONNX format at {ONNX_PATH}...")
+    torch.onnx.export(
+        model,
+        dummy_input,
+        ONNX_PATH,
+        export_params=True,
+        opset_version=12,
+        do_constant_folding=True,
+        input_names=["input"],
+        output_names=["output"],
+        dynamic_axes={"input": {0: "batch_size"}, "output": {0: "batch_size"}},
+    )
+    print(f"[SUCCESS] ONNX model exported to {ONNX_PATH}")
+
+    # Apply 8-bit dynamic quantization if onnxruntime is available
+    try:
+        import onnxruntime
+        from onnxruntime.quantization import quantize_dynamic, QuantType
+        
+        QUANT_ONNX_PATH = os.path.join(ONNX_MODEL_DIR, "plant_disease_resnet18_quant.onnx")
+        print(f"[INFO] onnxruntime is installed. Performing 8-bit dynamic quantization to {QUANT_ONNX_PATH}...")
+        
+        quantize_dynamic(
+            model_input=ONNX_PATH,
+            model_output=QUANT_ONNX_PATH,
+            weight_type=QuantType.QUInt8
+        )
+        print("[SUCCESS] Quantization complete.")
+        
+        # Replace the larger float32 file with the quantized version to save space (46MB -> 11MB)
+        if os.path.exists(QUANT_ONNX_PATH) and os.path.getsize(QUANT_ONNX_PATH) > 0:
+            os.replace(QUANT_ONNX_PATH, ONNX_PATH)
+            print(f"[INFO] Replaced {ONNX_PATH} with the quantized model (~11.6MB).")
+    except ImportError:
+        print("[WARN] onnxruntime is not installed. Skipping dynamic quantization. The output model will be standard float32 (~46.8MB).")
+    except Exception as e:
+        print(f"[ERROR] Quantization failed: {e}")
+
+if __name__ == "__main__":
+    export_model()
diff --git a/frontend/next.config.mjs b/frontend/next.config.mjs
index 1cc8a95..b4d49dd 100644
--- a/frontend/next.config.mjs
+++ b/frontend/next.config.mjs
@@ -20,6 +20,21 @@ const withPWA = withPWAInit({
     // Runtime caching rules - these are added to the auto-generated Workbox SW
     // They tell the SW how to handle specific request types at runtime
     runtimeCaching: [
+      {
+        // Cache ONNX and WASM static assets (models and runtimes) for offline execution
+        urlPattern: ({ url }) => url.pathname.endsWith('.onnx') || url.pathname.endsWith('.wasm'),
+        handler: 'CacheFirst',
+        options: {
+          cacheName: 'agronavis-ml-assets-v1',
+          expiration: {
+            maxEntries: 10,
+            maxAgeSeconds: 30 * 24 * 60 * 60, // Cache for 30 days
+          },
+          cacheableResponse: {
+            statuses: [0, 200],
+          },
+        },
+      },
       {
         // Cache API responses for farms and crop-scans
         // Use matchCallback: Workbox tests RegExp against full URL, not just pathname
@@ -84,10 +99,17 @@ const nextConfig = {
     ],
     formats: ['image/webp', 'image/avif'],
   },
-  transpilePackages: ['react-leaflet', 'leaflet'],
+  transpilePackages: ['react-leaflet', 'leaflet', 'onnxruntime-web'],
   experimental: {
     optimizePackageImports: ['@supabase/supabase-js'],
   },
+  webpack: (config) => {
+    config.resolve.alias = {
+      ...config.resolve.alias,
+      'onnxruntime-web': path.resolve(process.cwd(), 'node_modules/onnxruntime-web/dist/ort.all.min.js'),
+    };
+    return config;
+  },
   env: {
     NEXT_PUBLIC_SUPABASE_URL: process.env.NEXT_PUBLIC_SUPABASE_URL,
     NEXT_PUBLIC_SUPABASE_ANON_KEY: process.env.NEXT_PUBLIC_SUPABASE_ANON_KEY,
diff --git a/frontend/package-lock.json b/frontend/package-lock.json
index 481a75c..da37faf 100644
--- a/frontend/package-lock.json
+++ b/frontend/package-lock.json
@@ -21,6 +21,7 @@
         "i18next-browser-languagedetector": "^8.2.0",
         "leaflet": "^1.9.4",
         "next": "^14.1.0",
+        "onnxruntime-web": "^1.26.0",
         "react": "^18.2.0",
         "react-dom": "^18.2.0",
         "react-hook-form": "^7.48.2",
@@ -3440,6 +3441,63 @@
         "url": "https://opencollective.com/pkgr"
       }
     },
+    "node_modules/@protobufjs/aspromise": {
+      "version": "1.1.2",
+      "resolved": "https://registry.npmjs.org/@protobufjs/aspromise/-/aspromise-1.1.2.tgz",
+      "integrity": "sha512-j+gKExEuLmKwvz3OgROXtrJ2UG2x8Ch2YZUxahh+s1F2HZ+wAceUNLkvy6zKCPVRkU++ZWQrdxsUeQXmcg4uoQ==",
+      "license": "BSD-3-Clause"
+    },
+    "node_modules/@protobufjs/base64": {
+      "version": "1.1.2",
+      "resolved": "https://registry.npmjs.org/@protobufjs/base64/-/base64-1.1.2.tgz",
+      "integrity": "sha512-AZkcAA5vnN/v4PDqKyMR5lx7hZttPDgClv83E//FMNhR2TMcLUhfRUBHCmSl0oi9zMgDDqRUJkSxO3wm85+XLg==",
+      "license": "BSD-3-Clause"
+    },
+    "node_modules/@protobufjs/codegen": {
+      "version": "2.0.5",
+      "resolved": "https://registry.npmjs.org/@protobufjs/codegen/-/codegen-2.0.5.tgz",
+      "integrity": "sha512-zgXFLzW3Ap33e6d0Wlj4MGIm6Ce8O89n/apUaGNB/jx+hw+ruWEp7EwGUshdLKVRCxZW12fp9r40E1mQrf/34g==",
+      "license": "BSD-3-Clause"
+    },
+    "node_modules/@protobufjs/eventemitter": {
+      "version": "1.1.1",
+      "resolved": "https://registry.npmjs.org/@protobufjs/eventemitter/-/eventemitter-1.1.1.tgz",
+      "integrity": "sha512-vW1GmwMZNnL+gMRaovlh9yZX74kc+TTU3FObkkurpMaRtBfLP3ldjS9KQWlwZgraRE0+dheEEoAxdzcJQ8eXZg==",
+      "license": "BSD-3-Clause"
+    },
+    "node_modules/@protobufjs/fetch": {
+      "version": "1.1.1",
+      "resolved": "https://registry.npmjs.org/@protobufjs/fetch/-/fetch-1.1.1.tgz",
+      "integrity": "sha512-GpptLrs57adMSuHi3VNj0mAF8dwh36LMaYF6XyJ6JMWlVsc+t42tm1HSEDmOs3A8fC9yyeisgLhsTVQokOZ0zw==",
+      "license": "BSD-3-Clause",
+      "dependencies": {
+        "@protobufjs/aspromise": "^1.1.1"
+      }
+    },
+    "node_modules/@protobufjs/float": {
+      "version": "1.0.2",
+      "resolved": "https://registry.npmjs.org/@protobufjs/float/-/float-1.0.2.tgz",
+      "integrity": "sha512-Ddb+kVXlXst9d+R9PfTIxh1EdNkgoRe5tOX6t01f1lYWOvJnSPDBlG241QLzcyPdoNTsblLUdujGSE4RzrTZGQ==",
+      "license": "BSD-3-Clause"
+    },
+    "node_modules/@protobufjs/path": {
+      "version": "1.1.2",
+      "resolved": "https://registry.npmjs.org/@protobufjs/path/-/path-1.1.2.tgz",
+      "integrity": "sha512-6JOcJ5Tm08dOHAbdR3GrvP+yUUfkjG5ePsHYczMFLq3ZmMkAD98cDgcT2iA1lJ9NVwFd4tH/iSSoe44YWkltEA==",
+      "license": "BSD-3-Clause"
+    },
+    "node_modules/@protobufjs/pool": {
+      "version": "1.1.0",
+      "resolved": "https://registry.npmjs.org/@protobufjs/pool/-/pool-1.1.0.tgz",
+      "integrity": "sha512-0kELaGSIDBKvcgS4zkjz1PeddatrjYcmMWOlAuAPwAeccUrPHdUqo/J6LiymHHEiJT5NrF1UVwxY14f+fy4WQw==",
+      "license": "BSD-3-Clause"
+    },
+    "node_modules/@protobufjs/utf8": {
+      "version": "1.1.1",
+      "resolved": "https://registry.npmjs.org/@protobufjs/utf8/-/utf8-1.1.1.tgz",
+      "integrity": "sha512-oOAWABowe8EAbMyWKM0tYDKi8Yaox52D+HWZhAIJqQXbqe0xI/GV7FhLWqlEKreMkfDjshR5FKgi3mnle0h6Eg==",
+      "license": "BSD-3-Clause"
+    },
     "node_modules/@react-leaflet/core": {
       "version": "2.1.0",
       "resolved": "https://registry.npmjs.org/@react-leaflet/core/-/core-2.1.0.tgz",
@@ -9635,6 +9693,12 @@
         "node": "^10.12.0 || >=12.0.0"
       }
     },
+    "node_modules/flatbuffers": {
+      "version": "25.9.23",
+      "resolved": "https://registry.npmjs.org/flatbuffers/-/flatbuffers-25.9.23.tgz",
+      "integrity": "sha512-MI1qs7Lo4Syw0EOzUl0xjs2lsoeqFku44KpngfIduHBYvzm8h2+7K8YMQh1JtVVVrUvhLpNwqVi4DERegUJhPQ==",
+      "license": "Apache-2.0"
+    },
     "node_modules/flatted": {
       "version": "3.3.3",
       "resolved": "https://registry.npmjs.org/flatted/-/flatted-3.3.3.tgz",
@@ -10093,6 +10157,12 @@
       "dev": true,
       "license": "MIT"
     },
+    "node_modules/guid-typescript": {
+      "version": "1.0.9",
+      "resolved": "https://registry.npmjs.org/guid-typescript/-/guid-typescript-1.0.9.tgz",
+      "integrity": "sha512-Y8T4vYhEfwJOTbouREvG+3XDsjr8E3kIr7uf+JZ0BYloFsttiHU0WfvANVsR7TxNUJa/WpCnw/Ino/p+DeBhBQ==",
+      "license": "ISC"
+    },
     "node_modules/has-bigints": {
       "version": "1.1.0",
       "resolved": "https://registry.npmjs.org/has-bigints/-/has-bigints-1.1.0.tgz",
@@ -12323,6 +12393,12 @@
       "integrity": "sha512-HDWXG8isMntAyRF5vZ7xKuEvOhT4AhlRt/3czTSjvGUxjYCBVRQY48ViDHyfYz9VIoBkW4TMGQNapx+l3RUwdA==",
       "license": "MIT"
     },
+    "node_modules/long": {
+      "version": "5.3.2",
+      "resolved": "https://registry.npmjs.org/long/-/long-5.3.2.tgz",
+      "integrity": "sha512-mNAgZ1GmyNhD7AuqnTG3/VQ26o760+ZYBPKjPvugO8+nLbYfX6TVpJPseBvopbdY+qpZ/lKUnmEc1LeZYS3QAA==",
+      "license": "Apache-2.0"
+    },
     "node_modules/longest-streak": {
       "version": "3.1.0",
       "resolved": "https://registry.npmjs.org/longest-streak/-/longest-streak-3.1.0.tgz",
@@ -13719,6 +13795,26 @@
         "url": "https://github.com/sponsors/sindresorhus"
       }
     },
+    "node_modules/onnxruntime-common": {
+      "version": "1.26.0",
+      "resolved": "https://registry.npmjs.org/onnxruntime-common/-/onnxruntime-common-1.26.0.tgz",
+      "integrity": "sha512-qVyMR4lcWgbkc4getFV+GQijsTnbg/siteoqcDwa3sI/LxbrMSNw4ePyvCq/ymdQaRomCA7YuWmhzsswxvymdw==",
+      "license": "MIT"
+    },
+    "node_modules/onnxruntime-web": {
+      "version": "1.26.0",
+      "resolved": "https://registry.npmjs.org/onnxruntime-web/-/onnxruntime-web-1.26.0.tgz",
+      "integrity": "sha512-LbRr/8zZt2xilI2smrVQGGKINo0U46i8qJp+UXyMBGfqN7KjnH1BiwCwLwyNIVV4i9CKFv7Sf4PwLKWnT8/bEA==",
+      "license": "MIT",
+      "dependencies": {
+        "flatbuffers": "^25.1.24",
+        "guid-typescript": "^1.0.9",
+        "long": "^5.2.3",
+        "onnxruntime-common": "1.26.0",
+        "platform": "^1.3.6",
+        "protobufjs": "^7.2.4"
+      }
+    },
     "node_modules/optionator": {
       "version": "0.9.4",
       "resolved": "https://registry.npmjs.org/optionator/-/optionator-0.9.4.tgz",
@@ -14028,6 +14124,12 @@
         "node": ">=8"
       }
     },
+    "node_modules/platform": {
+      "version": "1.3.6",
+      "resolved": "https://registry.npmjs.org/platform/-/platform-1.3.6.tgz",
+      "integrity": "sha512-fnWVljUchTro6RiCFvCXBbNhJc2NijN7oIQxbwsyL0buWJPG85v81ehlHI9fXrJsMNgTofEoWIQeClKpgxFLrg==",
+      "license": "MIT"
+    },
     "node_modules/point-in-polygon": {
       "version": "1.1.0",
       "resolved": "https://registry.npmjs.org/point-in-polygon/-/point-in-polygon-1.1.0.tgz",
@@ -14296,6 +14398,29 @@
         "url": "https://github.com/sponsors/wooorm"
       }
     },
+    "node_modules/protobufjs": {
+      "version": "7.6.4",
+      "resolved": "https://registry.npmjs.org/protobufjs/-/protobufjs-7.6.4.tgz",
+      "integrity": "sha512-RJJPTTpvFfHcWLkIa2JFWK4XvtSzS0yEWDmunqHXli1h3JlkbcQZXDZdcWxv+JK3Xsl5/UFDPZ0iGm7DAengYw==",
+      "hasInstallScript": true,
+      "license": "BSD-3-Clause",
+      "dependencies": {
+        "@protobufjs/aspromise": "^1.1.2",
+        "@protobufjs/base64": "^1.1.2",
+        "@protobufjs/codegen": "^2.0.5",
+        "@protobufjs/eventemitter": "^1.1.1",
+        "@protobufjs/fetch": "^1.1.1",
+        "@protobufjs/float": "^1.0.2",
+        "@protobufjs/path": "^1.1.2",
+        "@protobufjs/pool": "^1.1.0",
+        "@protobufjs/utf8": "^1.1.1",
+        "@types/node": ">=13.7.0",
+        "long": "^5.3.2"
+      },
+      "engines": {
+        "node": ">=12.0.0"
+      }
+    },
     "node_modules/proxy-from-env": {
       "version": "1.1.0",
       "resolved": "https://registry.npmjs.org/proxy-from-env/-/proxy-from-env-1.1.0.tgz",
diff --git a/frontend/package.json b/frontend/package.json
index 27e3998..cd90f52 100644
--- a/frontend/package.json
+++ b/frontend/package.json
@@ -7,7 +7,8 @@
     "build": "next build",
     "start": "next start",
     "lint": "next lint",
-    "test": "jest"
+    "test": "jest",
+    "postinstall": "node -e \"const fs=require('fs');const path=require('path');const src=path.join(__dirname,'node_modules','onnxruntime-web','dist');const dest=path.join(__dirname,'public','wasm');if(fs.existsSync(src)){fs.mkdirSync(dest,{recursive:true});fs.readdirSync(src).filter(f=>f.endsWith('.wasm')).forEach(f=>fs.copyFileSync(path.join(src,f),path.join(dest,f)));console.log('Copied onnxruntime-web WASM files to public/wasm')} else {console.error('Error: onnxruntime-web node_modules not found. WASM files are required for offline inference.');process.exit(1)}\""
   },
   "dependencies": {
     "@ducanh2912/next-pwa": "^10.2.9",
@@ -23,6 +24,7 @@
     "i18next-browser-languagedetector": "^8.2.0",
     "leaflet": "^1.9.4",
     "next": "^14.1.0",
+    "onnxruntime-web": "^1.26.0",
     "react": "^18.2.0",
     "react-dom": "^18.2.0",
     "react-hook-form": "^7.48.2",
diff --git a/frontend/public/wasm/ort-wasm-simd-threaded.asyncify.wasm b/frontend/public/wasm/ort-wasm-simd-threaded.asyncify.wasm
new file mode 100644
index 0000000..c7918f6
Binary files /dev/null and b/frontend/public/wasm/ort-wasm-simd-threaded.asyncify.wasm differ
diff --git a/frontend/public/wasm/ort-wasm-simd-threaded.jsep.wasm b/frontend/public/wasm/ort-wasm-simd-threaded.jsep.wasm
new file mode 100644
index 0000000..b2d8187
Binary files /dev/null and b/frontend/public/wasm/ort-wasm-simd-threaded.jsep.wasm differ
diff --git a/frontend/public/wasm/ort-wasm-simd-threaded.jspi.wasm b/frontend/public/wasm/ort-wasm-simd-threaded.jspi.wasm
new file mode 100644
index 0000000..70c6e69
Binary files /dev/null and b/frontend/public/wasm/ort-wasm-simd-threaded.jspi.wasm differ
diff --git a/frontend/public/wasm/ort-wasm-simd-threaded.wasm b/frontend/public/wasm/ort-wasm-simd-threaded.wasm
new file mode 100644
index 0000000..7ab49a2
Binary files /dev/null and b/frontend/public/wasm/ort-wasm-simd-threaded.wasm differ
diff --git a/frontend/src/components/CropScanTab.tsx b/frontend/src/components/CropScanTab.tsx
index dc64411..dd27de7 100644
--- a/frontend/src/components/CropScanTab.tsx
+++ b/frontend/src/components/CropScanTab.tsx
@@ -21,6 +21,8 @@ import {
   type CropScan,
 } from '../utils/cropScanApi'
 import { farmApi } from '../utils/farmApi'
+import { runLocalONNXInference } from '../utils/onnxInference'
+import { addOfflineCropScan } from '../lib/offlineStorage'
 
 // ── Icons (inline SVG) ────────────────────────────────────────────────────────
 
@@ -88,6 +90,7 @@ const CropScanTab: React.FC = () => {
   const [result, setResult] = useState<DiagnosisResult | null>(null)
   const [error, setError] = useState<string | null>(null)
   const [saved, setSaved] = useState(false)
+  const [scanSource, setScanSource] = useState<'on-device' | 'server' | null>(null)
 
   // History
   const [history, setHistory] = useState<CropScan[]>([])
@@ -168,20 +171,62 @@ const CropScanTab: React.FC = () => {
     setError(null)
     setResult(null)
     setSaved(false)
+    setScanSource(null)
+
+    let diagnosis: DiagnosisResult
+    let source: 'on-device' | 'server' = 'server'
+
     try {
-      const diagnosis = await diagnoseImage(
-        selectedFile,
-        selectedFarmId || undefined
-      )
-      setResult(diagnosis)
-      if (selectedFarmId) setSaved(true)
-      // Refresh history after scan
-      await loadHistory(selectedFarmId || undefined)
+      if (typeof window !== 'undefined' && navigator.onLine) {
+        // Attempt online server-side scan
+        diagnosis = await diagnoseImage(
+          selectedFile,
+          selectedFarmId || undefined
+        )
+        source = 'server'
+      } else {
+        throw new Error('Device is offline. Running local scanner.')
+      }
     } catch (err: any) {
-      setError(err.message || 'Scan failed. Make sure the Python backend is running.')
-    } finally {
-      setLoading(false)
+      console.log('Online scan failed or device is offline. Falling back to local ONNX inference:', err)
+      try {
+        const localResult = await runLocalONNXInference(selectedFile)
+        diagnosis = {
+          predicted_disease_name: localResult.predicted_disease_name,
+          confidence_score: localResult.confidence_score,
+          is_healthy: localResult.is_healthy,
+          crop_type: localResult.crop_type,
+          symptoms: localResult.symptoms,
+          recommended_action: localResult.recommended_action
+        }
+        source = 'on-device'
+
+        // Save scan result to IndexedDB local history if a farm is selected
+        if (selectedFarmId) {
+          const offlineScan = {
+            id: Math.random().toString(36).substring(2, 11) + Date.now().toString(),
+            farm_id: selectedFarmId,
+            detected_disease: diagnosis.predicted_disease_name,
+            confidence_score: diagnosis.confidence_score,
+            recommendation: diagnosis.recommended_action.join(' | '),
+            scan_date: new Date().toISOString()
+          }
+          await addOfflineCropScan(offlineScan)
+        }
+      } catch (localErr: any) {
+        setError(localErr.message || 'Scan failed. Local ONNX model couldn\'t be loaded or executed.')
+        setLoading(false)
+        return
+      }
     }
+
+    setResult(diagnosis)
+    setScanSource(source)
+    if (selectedFarmId) setSaved(true)
+
+    // Refresh history after scan
+    await loadHistory(selectedFarmId || undefined)
+    setLoading(false)
   }
 
   // ── Confidence colour ────────────────────────────────────────────────────
@@ -318,9 +363,14 @@ const CropScanTab: React.FC = () => {
                 </div>
                 <div className={styles.resultMeta}>
                   <div className={styles.resultName}>{result.predicted_disease_name}</div>
-                  {result.crop_type && (
-                    <div className={styles.resultCrop}>Crop: {result.crop_type}</div>
-                  )}
+                  <div className={styles.resultCrop}>
+                    {result.crop_type ? `Crop: ${result.crop_type}` : 'Crop: Unknown'}
+                    {scanSource && (
+                      <span style={{ marginLeft: 8, opacity: 0.85 }}>
+                        &middot; {scanSource === 'on-device' ? '⚡ On-Device' : '☁️ Server'}
+                      </span>
+                    )}
+                  </div>
                 </div>
                 <div className={styles.resultBadge}>{severityBadge}</div>
               </div>
diff --git a/frontend/src/lib/offlineStorage.ts b/frontend/src/lib/offlineStorage.ts
index fb78869..da0317a 100644
--- a/frontend/src/lib/offlineStorage.ts
+++ b/frontend/src/lib/offlineStorage.ts
@@ -208,4 +208,13 @@ export async function saveOfflineCropScans(scans: OfflineCropScan[], farmId?: st
   } catch (error) {
     console.error('Error saving offline crop scans:', error);
   }
+}
+
+export async function addOfflineCropScan(scan: OfflineCropScan): Promise<void> {
+  try {
+    const db = await getDB();
+    await db.put('crop-scans', scan);
+  } catch (error) {
+    console.error('Error adding single offline crop scan:', error);
+  }
 }
\ No newline at end of file
diff --git a/frontend/src/utils/diseaseData.ts b/frontend/src/utils/diseaseData.ts
new file mode 100644
index 0000000..4a499e4
--- /dev/null
+++ b/frontend/src/utils/diseaseData.ts
@@ -0,0 +1,272 @@
+// Crop disease symptoms and treatments database (mirrors backend/main.py)
+
+export const DISEASE_SYMPTOMS: Record<string, string[]> = {
+  "apple_apple_scab": ["Olive-green to black spots on leaves", "Crusty scabby lesions on fruit", "Premature leaf drop"],
+  "apple_black_rot": ["Brown circular leaf lesions with purple halos", "Black rot on fruit surface", "Cankers on branches"],
+  "apple_cedar_apple_rust": ["Bright orange-yellow spots on upper leaf surface", "Tube-like projections on leaf underside", "Premature defoliation"],
+  "bean_angular_leaf_spot": ["Angular water-soaked leaf spots", "Brown necrotic patches", "Pod discoloration"],
+  "bean_rust": ["Small reddish-brown pustules on leaves", "Yellow halos around pustules", "Leaf defoliation under heavy infection"],
+  "bell_pepper_bacterial_spot": ["Water-soaked lesions on leaves", "Brown necrotic spots with yellow halos", "Fruit scab lesions"],
+  "cherry_powdery_mildew": ["White powdery fungal growth on leaves", "Leaf curling and distortion", "Stunted shoot growth"],
+  "corn_cercospora_leaf_spot": ["Gray to tan rectangular lesions", "Lesions parallel to leaf veins", "Premature leaf dying"],
+  "corn_common_rust": ["Brick-red pustules scattered on both leaf surfaces", "Pustules darken with age", "Leaf yellowing"],
+  "corn_gray_leaf_spot": ["Rectangular gray to brown lesions", "Lesions delimited by leaf veins", "Severe blighting in humid conditions"],
+  "corn_northern_leaf_blight": ["Large cigar-shaped gray-green lesions", "Lesions 1-6 inches long", "Premature plant death in severe cases"],
+  "cotton_aphids": ["Distorted curled leaves", "Sticky honeydew on leaf surfaces", "Sooty mold growth"],
+  "cotton_army_worm": ["Ragged leaf edges from feeding", "Visible caterpillars on plants", "Defoliation in severe infestations"],
+  "cotton_bacterial_blight": ["Angular water-soaked leaf spots", "Brown lesions with yellow halos", "Boll rot and stem cankers"],
+  "cotton_powdery_mildew": ["White powdery coating on leaves", "Yellowing of affected tissue", "Stunted plant growth"],
+  "cotton_target_spot": ["Circular brown lesions with concentric rings", "Target-like appearance", "Premature leaf drop"],
+  "diseased_cucumber": ["Yellowing of leaves", "Water-soaked lesions on foliage", "Wilting and vine collapse"],
+  "diseased_rice": ["Discolored or spotted leaves", "Water-soaked leaf sheaths", "Stunted plant growth"],
+  "grape_black_rot": ["Brown circular lesions with black borders on leaves", "Mummified shriveled berries", "Black pycnidia dots in lesions"],
+  "grape_esca_black_measles": ["Interveinal chlorosis and necrosis", "Tiger-stripe pattern on leaves", "Internal wood discoloration"],
+  "grape_leaf_blight": ["Large irregular brown leaf lesions", "Lesions coalesce leading to defoliation", "Berry shriveling"],
+  "groundnut_early_leaf_spot": ["Circular dark brown spots on upper leaf surface", "Yellow halos around spots", "Premature defoliation"],
+  "groundnut_late_leaf_spot": ["Dark brown to black circular spots", "Spots appear more on lower leaf surface", "Severe defoliation"],
+  "groundnut_nutrition_deficiency": ["Interveinal yellowing", "Stunted growth", "Pale green to yellow leaf color"],
+  "groundnut_rosette": ["Stunted plant growth", "Mosaic pattern on leaves", "Leaf curling and bunching"],
+  "groundnut_rust": ["Orange-brown pustules on lower leaf surface", "Yellow spots on upper leaf surface", "Premature defoliation"],
+  "guava_fruit_fly": ["Puncture marks on fruit surface", "Rotting flesh inside fruit", "Premature fruit drop"],
+  "guava_stylosa_disease": ["Dark lesions on fruit and leaves", "Fruit cracking and decay", "Leaf spotting"],
+  "guava_wilt": ["Sudden wilting of leaves", "Yellowing starting from older leaves", "Root and stem rotting"],
+  "lemon_bacterial_blight": ["Water-soaked leaf spots turning brown", "Leaf yellowing and drop", "Twig dieback"],
+  "lemon_citrus_canker": ["Raised corky lesions on leaves, fruit, and stems", "Yellow halos around lesions", "Premature fruit drop"],
+  "lemon_dry_leaf": ["Dry and brittle leaves", "Marginal leaf scorch", "Twig dieback"],
+  "lemon_greening": ["Asymmetric mottling (blotchy mottle)", "Yellow shoots (lemon shoots)", "Small misshapen bitter fruit"],
+  "lemon_powdery_mildew": ["White powdery fungal growth on young leaves", "Leaf distortion and curling", "Premature leaf drop"],
+  "lemon_spider_mites": ["Fine webbing on leaf undersides", "Stippled yellowing of leaves", "Bronzing of leaf surface"],
+  "peach_bacterial_spot": ["Water-soaked angular leaf spots", "Dark brown lesions with yellow halos", "Fruit spotting and cracking"],
+  "potato_early_blight": ["Circular dark brown spots with concentric rings on older leaves", "Yellow halos around lesions", "Lesions start on lower older leaves"],
+  "potato_late_blight": ["Water-soaked pale green to dark brown lesions", "White fungal growth on leaf undersides", "Rapid destruction of foliage"],
+  "pumpkin_bacterial_leaf_spot": ["Water-soaked angular spots on leaves", "Brown dried lesions with yellow borders", "Fruit surface lesions"],
+  "pumpkin_downy_mildew": ["Yellow angular spots on upper leaf surface", "Gray-purple fuzzy growth on leaf underside", "Rapid leaf blighting"],
+  "pumpkin_powdery_mildew": ["White powdery spots on leaf surfaces", "Leaf yellowing and browning", "Premature aging of plant"],
+  "rice_bacterial_blight": ["Water-soaked wave-like lesions on leaf edges", "Lesions turn yellow then white", "Bacterial ooze in early morning"],
+  "strawberry_leaf_scorch": ["Purple to reddish-brown spots on leaves", "Spots coalesce leading to blighted appearance", "Leaf edges scorch and dry"],
+  "sugarcane_bacterial_blight": ["Water-soaked reddish stripe on leaves", "Leaf margins become necrotic", "Stalk rot in severe cases"],
+  "sugarcane_red_rot": ["Red discoloration of internal stalk tissue", "White patches with red margins in cross-section", "Plant wilting and death"],
+  "sugarcane_rust": ["Orange-brown pustules on leaf surfaces", "Yellow halos surrounding pustules", "Leaf drying in severe infections"],
+  "sugarcane_yellow_leaf_disease": ["Yellowing of midrib on lower leaf surface", "Leaf roll and wilting", "Stunted growth and reduced yield"],
+  "tomato_bacterial_spot": ["Small water-soaked lesions on leaves and fruit", "Dark brown spots with yellow halos", "Fruit spots with raised margins"],
+  "tomato_early_blight": ["Dark concentric ring lesions (bullseye pattern)", "Lesions start on older lower leaves", "Yellow area around lesions"],
+  "tomato_late_blight": ["Large water-soaked pale to dark green lesions", "White mold on undersides in humid weather", "Rapid plant collapse"],
+  "tomato_leaf_mold": ["Pale yellow spots on upper leaf surface", "Olive-green to gray mold on undersides", "Leaf drop under severe infection"],
+  "tomato_septoria_leaf_spot": ["Circular spots with dark margins and light centers", "Small black pycnidia inside spots", "Progressive yellowing and leaf drop"],
+  "tomato_spider_mites": ["Fine stippling and bronzing on leaves", "Fine webbing on undersides", "Leaf curling and drying"],
+  "tomato_target_spot": ["Circular brown spots with concentric rings", "Spots coalesce in wet conditions", "Premature defoliation"],
+  "tomato_tomato_mosaic_virus": ["Light-dark green mosaic pattern on leaves", "Leaf distortion and cupping", "Stunted plant growth"],
+  "tomato_tomato_yellow_leaf_curl_virus": ["Upward leaf curling and yellowing", "Stunted compact plant growth", "Flower drop and low fruit set"],
+  "wheat_black_rust": ["Dark brown to black pustules on stems and leaves", "Pustules rupture releasing dark spores", "Severe lodging in heavy infection"],
+  "wheat_blast": ["Bleached or light-colored ear (head)", "Partially filled grain", "Diamond-shaped lesions on leaves"],
+  "wheat_brown_rust": ["Orange-brown pustules on upper leaf surface", "Pustules circular and scattered", "Leaf yellowing in severe cases"],
+  "wheat_common_root_rot": ["Browning of roots and crown", "Reduced tillering and plant vigor", "Premature ripening (whiteheads)"],
+  "wheat_head_blight": ["Pink-salmon fungal growth on spikelets", "Bleached spikelets (Fusarium)", "Shriveled grain"],
+  "wheat_loose_smut": ["Grain replaced by powdery black mass of spores", "Smut head visible before other heads emerge", "Spores released at flowering"],
+  "wheat_mildew": ["White powdery fungal colonies on leaves and stems", "Yellowing of tissue under colonies", "Reduced photosynthesis"],
+  "wheat_mite": ["Silvery streaking on leaves", "Leaf curling and withering", "Stunted plant growth"],
+  "wheat_septoria": ["Irregular tan to brown lesions with dark borders", "Small black pycnidia inside lesions", "Lesions coalesce in wet weather"],
+  "wheat_stem_fly": ["Dead heart in young plants", "Stem discoloration inside", "Whiteheads at heading stage"],
+  "wheat_yellow_rust": ["Bright yellow pustules in stripes along leaf veins", "Cool-weather disease", "Severe early attack causes complete leaf yellowing"],
+};
+
+export const DISEASE_TREATMENTS: Record<string, string[]> = {
+  "apple_apple_scab": ["Apply preventive fungicides (captan, mancozeb) in spring", "Rake and destroy fallen leaves", "Plant resistant varieties"],
+  "apple_black_rot": ["Remove and destroy infected fruit and cankered wood", "Apply copper-based fungicides", "Improve air circulation through pruning"],
+  "apple_cedar_apple_rust": ["Remove nearby juniper/cedar trees if possible", "Apply fungicides from pink bud stage", "Use resistant apple varieties"],
+  "bean_angular_leaf_spot": ["Use certified disease-free seeds", "Apply copper-based bactericides", "Avoid overhead irrigation"],
+  "bean_rust": ["Apply mancozeb or triazole fungicides at first sign", "Improve plant spacing for air circulation", "Remove and destroy infected plant debris"],
+  "bell_pepper_bacterial_spot": ["Apply copper bactericides preventively", "Use disease-free transplants", "Avoid working in field when wet"],
+  "cherry_powdery_mildew": ["Apply sulfur or myclobutanil fungicides", "Prune to improve air circulation", "Avoid excess nitrogen fertilization"],
+  "corn_cercospora_leaf_spot": ["Plant resistant hybrids", "Apply strobilurin or triazole fungicides", "Rotate crops away from corn"],
+  "corn_common_rust": ["Plant resistant corn hybrids", "Apply foliar fungicides if infection is early and severe", "Scout fields regularly"],
+  "corn_gray_leaf_spot": ["Plant resistant hybrids", "Rotate crops", "Apply triazole or strobilurin fungicides"],
+  "corn_northern_leaf_blight": ["Use resistant hybrids", "Apply foliar fungicides at tasseling", "Practice crop rotation"],
+  "cotton_aphids": ["Release beneficial insects (ladybugs, lacewings)", "Apply insecticidal soap or neem oil", "Use systemic insecticides if severe"],
+  "cotton_army_worm": ["Apply Bt (Bacillus thuringiensis) or chemical insecticides", "Monitor with pheromone traps", "Practice crop rotation"],
+  "cotton_bacterial_blight": ["Use disease-free seeds", "Apply copper bactericides", "Remove and destroy infected plants"],
+  "cotton_powdery_mildew": ["Apply sulfur or myclobutanil fungicides", "Improve plant spacing", "Avoid high nitrogen levels"],
+  "cotton_target_spot": ["Apply triazole or strobilurin fungicides", "Remove crop debris after harvest", "Rotate crops"],
+  "diseased_cucumber": ["Identify specific disease and apply appropriate fungicide/bactericide", "Improve drainage and air circulation", "Remove infected plant parts"],
+  "diseased_rice": ["Identify specific disease; apply appropriate management", "Ensure proper water management", "Use resistant varieties"],
+  "grape_black_rot": ["Apply myclobutanil or mancozeb from budbreak", "Remove mummified berries and infected canes", "Improve air circulation through pruning"],
+  "grape_esca_black_measles": ["No complete cure; manage through pruning infected wood", "Protect pruning wounds with paste", "Maintain vine vigor with proper nutrition"],
+  "grape_leaf_blight": ["Apply copper fungicides preventively", "Remove and destroy infected leaves", "Ensure good vineyard sanitation"],
+  "groundnut_early_leaf_spot": ["Apply chlorothalonil or mancozeb fungicides", "Rotate crops with non-host plants", "Use resistant varieties"],
+  "groundnut_late_leaf_spot": ["Apply tebuconazole or chlorothalonil", "Maintain proper plant spacing", "Remove crop debris after harvest"],
+  "groundnut_nutrition_deficiency": ["Test soil and apply deficient nutrients", "Apply balanced NPK fertilizers", "Use foliar micronutrient sprays"],
+  "groundnut_rosette": ["Control aphid vectors with insecticides", "Use resistant varieties", "Remove and destroy infected plants early"],
+  "groundnut_rust": ["Apply mancozeb or triazole fungicides", "Plant early to avoid peak rust season", "Use resistant varieties"],
+  "guava_fruit_fly": ["Use protein bait traps", "Apply cover sprays of insecticide", "Bag fruits when young"],
+  "guava_stylosa_disease": ["Remove and destroy infected plant parts", "Apply copper-based fungicides", "Maintain tree vigor through proper nutrition"],
+  "guava_wilt": ["No effective cure; remove infected trees", "Improve soil drainage", "Plant resistant rootstocks"],
+  "lemon_bacterial_blight": ["Apply copper bactericides preventively", "Prune infected branches", "Avoid overhead irrigation"],
+  "lemon_citrus_canker": ["Apply copper bactericides", "Remove and destroy infected plant material", "Use certified disease-free nursery stock"],
+  "lemon_dry_leaf": ["Improve irrigation management", "Apply balanced fertilizers", "Check for root problems"],
+  "lemon_greening": ["Control Asian citrus psyllid vector with insecticides", "Remove infected trees immediately", "Use certified disease-free planting material"],
+  "lemon_powdery_mildew": ["Apply sulfur-based fungicides on new growth", "Improve air circulation", "Avoid excess nitrogen"],
+  "lemon_spider_mites": ["Apply miticides (abamectin, bifenazate)", "Encourage natural predators", "Use water sprays to reduce populations"],
+  "peach_bacterial_spot": ["Apply copper bactericides during dormancy", "Use resistant varieties", "Avoid overhead irrigation"],
+  "potato_early_blight": ["Apply mancozeb or chlorothalonil fungicides preventively", "Rotate crops", "Ensure proper plant nutrition especially potassium"],
+  "potato_late_blight": ["Apply metalaxyl + mancozeb or cymoxanil based fungicides", "Destroy infected volunteers and cull piles", "Plant certified disease-free seed"],
+  "pumpkin_bacterial_leaf_spot": ["Apply copper-based bactericides", "Use disease-free seeds", "Avoid overhead irrigation"],
+  "pumpkin_downy_mildew": ["Apply metalaxyl-based fungicides preventively", "Improve field drainage", "Use resistant varieties"],
+  "pumpkin_powdery_mildew": ["Apply sulfur or myclobutanil fungicides", "Improve air circulation", "Avoid excessive nitrogen"],
+  "rice_bacterial_blight": ["Use resistant varieties", "Apply copper bactericides", "Avoid excess nitrogen and flood water from infected areas"],
+  "strawberry_leaf_scorch": ["Apply captan or myclobutanil fungicides", "Remove infected leaves", "Improve plant spacing and air circulation"],
+  "sugarcane_bacterial_blight": ["Use disease-free setts for planting", "Apply copper bactericides", "Remove and destroy infected plant material"],
+  "sugarcane_red_rot": ["Plant resistant varieties", "Use disease-free setts", "Treat setts with fungicide before planting"],
+  "sugarcane_rust": ["Apply mancozeb or triadimefon fungicides", "Plant resistant varieties", "Scout fields regularly"],
+  "sugarcane_yellow_leaf_disease": ["Control aphid vectors", "Use clean planting material", "Remove and destroy infected plants"],
+  "tomato_bacterial_spot": ["Apply copper bactericides preventively", "Use disease-free transplants", "Avoid overhead irrigation"],
+  "tomato_early_blight": ["Apply chlorothalonil or mancozeb fungicides", "Remove lower infected leaves", "Maintain adequate plant nutrition"],
+  "tomato_late_blight": ["Apply metalaxyl + mancozeb or cymoxanil based fungicides immediately", "Remove and destroy infected plants", "Avoid overhead irrigation"],
+  "tomato_leaf_mold": ["Improve greenhouse ventilation", "Apply fungicides (chlorothalonil, mancozeb)", "Use resistant varieties"],
+  "tomato_septoria_leaf_spot": ["Apply chlorothalonil or mancozeb fungicides", "Remove infected lower leaves", "Avoid overhead irrigation"],
+  "tomato_spider_mites": ["Apply miticides (abamectin, spiromesifen)", "Use predatory mites for biological control", "Maintain plant water stress to minimum"],
+  "tomato_target_spot": ["Apply chlorothalonil or mancozeb fungicides", "Improve air circulation", "Remove plant debris"],
+  "tomato_tomato_mosaic_virus": ["Remove and destroy infected plants", "Control insect vectors", "Disinfect tools and hands frequently"],
+  "tomato_tomato_yellow_leaf_curl_virus": ["Control whitefly vectors with insecticides", "Use reflective mulches to deter whiteflies", "Plant resistant varieties"],
+  "wheat_black_rust": ["Apply triazole fungicides at first pustule appearance", "Plant resistant varieties", "Monitor fields regularly during warm humid weather"],
+  "wheat_blast": ["Apply tebuconazole at heading", "Use resistant varieties where available", "Avoid planting in areas with high disease pressure"],
+  "wheat_brown_rust": ["Apply triazole or strobulurin fungicides", "Plant resistant varieties", "Scout fields regularly"],
+  "wheat_common_root_rot": ["Seed treatment with fungicides (thiram, carboxin)", "Rotate crops", "Reduce soil compaction"],
+  "wheat_head_blight": ["Apply tebuconazole or metconazole at flowering", "Avoid planting after corn or in areas with high Fusarium", "Use resistant varieties"],
+  "wheat_loose_smut": ["Treat seeds with systemic fungicides (carboxin, tebuconazole)", "Use certified smut-free seeds", "Hot water seed treatment"],
+  "wheat_mildew": ["Apply triazole or sulfur-based fungicides", "Plant resistant varieties", "Avoid excess nitrogen fertilization"],
+  "wheat_mite": ["Apply miticides or acaricides", "Remove crop debris", "Monitor edges of fields first"],
+  "wheat_septoria": ["Apply triazole fungicides from GS31", "Use resistant varieties", "Avoid dense sowing"],
+  "wheat_stem_fly": ["Apply systemic insecticides at tillering", "Early sowing to escape peak infestation", "Remove and destroy stubble after harvest"],
+  "wheat_yellow_rust": ["Apply triazole fungicides immediately on detection", "Plant resistant varieties", "Scout fields regularly in cool wet spring weather"],
+};
+
+export const CLASS_NAMES: string[] = [
+  "apple_apple_scab",
+  "apple_black_rot",
+  "apple_cedar_apple_rust",
+  "bean_angular_leaf_spot",
+  "bean_rust",
+  "bell_pepper_bacterial_spot",
+  "cherry_powdery_mildew",
+  "corn_cercospora_leaf_spot",
+  "corn_common_rust",
+  "corn_gray_leaf_spot",
+  "corn_northern_leaf_blight",
+  "cotton_aphids",
+  "cotton_army_worm",
+  "cotton_bacterial_blight",
+  "cotton_powdery_mildew",
+  "cotton_target_spot",
+  "diseased_cucumber",
+  "diseased_rice",
+  "grape_black_rot",
+  "grape_esca_black_measles",
+  "grape_leaf_blight",
+  "groundnut_early_leaf_spot",
+  "groundnut_late_leaf_spot",
+  "groundnut_nutrition_deficiency",
+  "groundnut_rosette",
+  "groundnut_rust",
+  "guava_fruit_fly",
+  "guava_stylosa_disease",
+  "guava_wilt",
+  "healthy_apple",
+  "healthy_bean",
+  "healthy_cherry",
+  "healthy_corn",
+  "healthy_cotton",
+  "healthy_cucumber",
+  "healthy_grapes",
+  "healthy_groundnut",
+  "healthy_guava",
+  "healthy_lemon",
+  "healthy_peach",
+  "healthy_pepper",
+  "healthy_potato",
+  "healthy_pumpkin",
+  "healthy_rice",
+  "healthy_strawberry",
+  "healthy_sugarcane",
+  "healthy_tomato",
+  "healthy_wheat",
+  "lemon_bacterial_blight",
+  "lemon_citrus_canker",
+  "lemon_dry_leaf",
+  "lemon_greening",
+  "lemon_powdery_mildew",
+  "lemon_spider_mites",
+  "peach_bacterial_spot",
+  "potato_early_blight",
+  "potato_late_blight",
+  "pumpkin_bacterial_leaf_spot",
+  "pumpkin_downy_mildew",
+  "pumpkin_powdery_mildew",
+  "rice_bacterial_blight",
+  "strawberry_leaf_scorch",
+  "sugarcane_bacterial_blight",
+  "sugarcane_red_rot",
+  "sugarcane_rust",
+  "sugarcane_yellow_leaf_disease",
+  "tomato_bacterial_spot",
+  "tomato_early_blight",
+  "tomato_late_blight",
+  "tomato_leaf_mold",
+  "tomato_septoria_leaf_spot",
+  "tomato_spider_mites",
+  "tomato_target_spot",
+  "tomato_tomato_mosaic_virus",
+  "tomato_tomato_yellow_leaf_curl_virus",
+  "wheat_black_rust",
+  "wheat_blast",
+  "wheat_brown_rust",
+  "wheat_common_root_rot",
+  "wheat_head_blight",
+  "wheat_loose_smut",
+  "wheat_mildew",
+  "wheat_mite",
+  "wheat_septoria",
+  "wheat_stem_fly",
+  "wheat_yellow_rust"
+];
+
+export function formatClassName(raw: string): string {
+  return raw.replace(/_/g, " ").replace(/\b\w/g, c => c.toUpperCase());
+}
+
+export function extractCropType(className: string): string {
+  // Strip common prefixes
+  let cleanName = className;
+  if (className.startsWith("healthy_")) {
+    cleanName = className.substring(8);
+  } else if (className.startsWith("diseased_")) {
+    cleanName = className.substring(9);
+  }
+
+  // Handle multi-word crop names (e.g. bell_pepper)
+  let cropRaw = "";
+  if (cleanName.startsWith("bell_pepper_")) {
+    cropRaw = "bell_pepper";
+  } else {
+    // Standard crops: first segment before underscore
+    cropRaw = cleanName.split("_")[0] || "Unknown";
+  }
+
+  // Capitalize each token and format
+  return cropRaw
+    .replace(/_/g, " ")
+    .replace(/\b\w/g, c => c.toUpperCase());
+}
+
+export function getSymptoms(className: string): string[] {
+  if (className.startsWith("healthy_")) {
+    return ["No disease symptoms detected", "Plant appears healthy"];
+  }
+  return DISEASE_SYMPTOMS[className] || [`Consult an agronomist for ${formatClassName(className)} symptoms`];
+}
+
+export function getTreatments(className: string): string[] {
+  if (className.startsWith("healthy_")) {
+    return ["Continue current management practices", "Monitor regularly for early disease signs"];
+  }
+  return DISEASE_TREATMENTS[className] || [`Consult an agronomist for ${formatClassName(className)} treatment`];
+}
diff --git a/frontend/src/utils/onnxInference.ts b/frontend/src/utils/onnxInference.ts
new file mode 100644
index 0000000..e0ae8f7
--- /dev/null
+++ b/frontend/src/utils/onnxInference.ts
@@ -0,0 +1,210 @@
+import {
+  formatClassName,
+  extractCropType,
+  getSymptoms,
+  getTreatments,
+  CLASS_NAMES
+} from './diseaseData';
+
+export interface LocalDiagnosisResult {
+  predicted_disease_name: string;
+  confidence_score: number;
+  is_healthy: boolean;
+  crop_type?: string;
+  symptoms: string[];
+  recommended_action: string[];
+}
+
+let session: any = null;
+let sessionPromise: Promise<any> | null = null;
+
+/**
+ * Lazy loads and returns the ONNX runtime session.
+ * Configures the WebAssembly binary runtime paths to point locally to /wasm/
+ * to ensure that the app can run fully offline inside the service worker cache.
+ * Uses a cached promise to prevent race conditions during concurrent startup calls.
+ */
+async function getInferenceSession(): Promise<any> {
+  if (session) {
+    return session;
+  }
+  if (sessionPromise) {
+    return sessionPromise;
+  }
+
+  if (typeof window === 'undefined') {
+    throw new Error('ONNX Runtime Web is only supported in browser environments.');
+  }
+
+  sessionPromise = (async () => {
+    try {
+      const ort = await import('onnxruntime-web');
+      
+      // Crucial: Set WASM path locally for PWA offline support
+      ort.env.wasm.wasmPaths = '/wasm/';
+      
+      // Load model from public folder
+      const activeSession = await ort.InferenceSession.create('/model/plant_disease_resnet18.onnx', {
+        executionProviders: ['wasm']
+      });
+      session = activeSession;
+      console.log('[LocalInference] ONNX Inference Session loaded successfully.');
+      return session;
+    } catch (error) {
+      sessionPromise = null; // Clear cached promise on failure to allow retry
+      console.error('[LocalInference] Failed to load ONNX session:', error);
+      throw new Error('Could not initialize the local disease scanner model.');
+    }
+  })();
+
+  return sessionPromise;
+}
+
+/**
+ * Converts a browser File object to an HTMLImageElement
+ */
+function fileToImage(file: File): Promise<HTMLImageElement> {
+  return new Promise((resolve, reject) => {
+    const reader = new FileReader();
+    reader.onload = (e) => {
+      const img = new Image();
+      img.onload = () => resolve(img);
+      img.onerror = () => reject(new Error('Failed to load image element'));
+      img.src = e.target?.result as string;
+    };
+    reader.onerror = () => reject(new Error('Failed to read image file'));
+    reader.readAsDataURL(file);
+  });
+}
+
+/**
+ * Resizes the input image element to 224x224 using an offscreen canvas
+ */
+function resizeImageToCanvas(img: HTMLImageElement): HTMLCanvasElement {
+  const canvas = document.createElement('canvas');
+  canvas.width = 224;
+  canvas.height = 224;
+  const ctx = canvas.getContext('2d');
+  if (!ctx) {
+    throw new Error('Failed to get 2D canvas context for resizing');
+  }
+
+  // Draw image scaled to 224x224
+  ctx.drawImage(img, 0, 0, 224, 224);
+  return canvas;
+}
+
+/**
+ * Extracts raw RGBA pixels from canvas, normalizes using ImageNet stats,
+ * and converts to a planar CHW Float32Array format expected by the model.
+ */
+function preprocessCanvasToFlatArray(canvas: HTMLCanvasElement): Float32Array {
+  const ctx = canvas.getContext('2d');
+  if (!ctx) {
+    throw new Error('Failed to get 2D canvas context for pixel extraction');
+  }
+
+  const imgData = ctx.getImageData(0, 0, 224, 224);
+  const data = imgData.data; // Uint8ClampedArray: R,G,B,A,R,G,B,A...
+
+  const mean = [0.485, 0.456, 0.406];
+  const std = [0.229, 0.224, 0.225];
+  
+  // Allocate space for 3 channels * 224 width * 224 height
+  const floatArray = new Float32Array(3 * 224 * 224);
+
+  // Convert interleaved RGBA to planar RGB and normalize
+  for (let i = 0; i < 224 * 224; i++) {
+    const r = data[i * 4];
+    const g = data[i * 4 + 1];
+    const b = data[i * 4 + 2];
+
+    // Compute standard ImageNet normalization: (x / 255.0 - mean) / std
+    floatArray[i] = (r / 255.0 - mean[0]) / std[0]; // Red plane
+    floatArray[224 * 224 + i] = (g / 255.0 - mean[1]) / std[1]; // Green plane
+    floatArray[2 * 224 * 224 + i] = (b / 255.0 - mean[2]) / std[2]; // Blue plane
+  }
+
+  return floatArray;
+}
+
+/**
+ * Performs client-side machine learning inference on an uploaded plant image file.
+ * Returns a standardized DiagnosisResult locally with zero network requests.
+ */
+export async function runLocalONNXInference(file: File): Promise<LocalDiagnosisResult> {
+  try {
+    const ort = await import('onnxruntime-web');
+    const activeSession = await getInferenceSession();
+
+    // 1. Process image file
+    const img = await fileToImage(file);
+    const canvas = resizeImageToCanvas(img);
+    const floatArray = preprocessCanvasToFlatArray(canvas);
+
+    // 2. Create multi-dimensional ONNX tensor [1, 3, 224, 224]
+    const inputTensor = new ort.Tensor('float32', floatArray, [1, 3, 224, 224]);
+
+    // 3. Execute inference using WASM execution provider with dynamic input/output names
+    const inputName = activeSession.inputNames[0] || 'input';
+    const outputName = activeSession.outputNames[0] || 'output';
+
+    const feeds = { [inputName]: inputTensor };
+    const results = await activeSession.run(feeds);
+
+    // 4. Retrieve logits output tensor dynamically
+    const outputTensor = results[outputName];
+    if (!outputTensor || !outputTensor.data) {
+      throw new Error('Model inference returned an empty output tensor.');
+    }
+    const output = outputTensor.data as Float32Array;
+
+    // Assert that logits output size matches the local CLASS_NAMES database size
+    if (output.length !== CLASS_NAMES.length) {
+      throw new Error(
+        `ONNX model output shape mismatch: got logits length of ${output.length}, ` +
+        `but expected ${CLASS_NAMES.length} classes based on local database.`
+      );
+    }
+
+    // 5. Postprocess: Argmax + numerically stable Softmax
+    let maxLogit = -Infinity;
+    let maxIdx = 0;
+
+    for (let i = 0; i < output.length; i++) {
+      if (output[i] > maxLogit) {
+        maxLogit = output[i];
+        maxIdx = i;
+      }
+    }
+
+    let sumExp = 0.0;
+    const exps = new Float32Array(output.length);
+    for (let i = 0; i < output.length; i++) {
+      exps[i] = Math.exp(output[i] - maxLogit);
+      sumExp += exps[i];
+    }
+
+    const confidence = (exps[maxIdx] / sumExp) * 100.0;
+
+    // 6. Map predictions to local classes
+    const className = CLASS_NAMES[maxIdx];
+    if (!className) {
+      throw new Error(`Inference returned class index ${maxIdx} which is out of bounds.`);
+    }
+
+    const isHealthy = className.startsWith('healthy_');
+
+    return {
+      predicted_disease_name: formatClassName(className),
+      confidence_score: parseFloat(confidence.toFixed(2)),
+      is_healthy: isHealthy,
+      crop_type: extractCropType(className),
+      symptoms: getSymptoms(className),
+      recommended_action: getTreatments(className)
+    };
+  } catch (error) {
+    console.error('[LocalInference] Error during on-device inference:', error);
+    throw error;
+  }
+}