feat: introduce FixMate Flutter app and React dashboard

- Add Flutter app shell (FixMateApp/MainScreen) with tabs: Report, Map,
  My Reports, Settings
- Implement capture and review flow (image_picker, geolocator, deterministic
  mock AI), and local storage (SharedPreferences + photo files on mobile)
- Build Map screen with flutter_map, marker clustering, filters, legend,
  marker details, and external maps deeplink
- Add My Reports list (view details, cycle status, delete) and Settings
  (language toggle via Provider, diagnostics, clear all data)
- Introduce JSON i18n loader and LocaleProvider; add EN/BM assets
- Define models (Report, enums) and UI badges (severity, status)

- Add static React dashboard (Leaflet map with clustering, heatmap toggle,
  filters incl. date range, queue, detail drawer), i18n (EN/BM), and
  demo data

- Update build/config and platform setup:
  - Extend pubspec with required packages and register i18n assets
  - Android: add CAMERA and location permissions; pin NDK version
  - iOS: add usage descriptions for camera, photo library, location
  - Gradle properties tuned for Windows/UNC stability
  - Register desktop plugins (Linux/macOS/Windows)
  - .gitignore: ignore .kilocode
  - Overhaul README and replace sample widget test

lib/services/mock_ai.dart

@@ -0,0 +1,116 @@
+import 'dart:math';
+import 'package:flutter/foundation.dart' hide Category;
+import '../models/enums.dart';
+import '../models/report.dart';
+
+/// Service for generating deterministic AI suggestions for reports
+class MockAIService {
+  /// Generate a deterministic seed based on report parameters
+  static int _generateSeed(String id, String createdAt, double lat, double lng, int? photoSizeBytes) {
+    final combined = '$id$createdAt$lat$lng${photoSizeBytes ?? 0}';
+    var hash = 0;
+    for (var i = 0; i < combined.length; i++) {
+      hash = ((hash << 5) - hash) + combined.codeUnitAt(i);
+      hash = hash & hash; // Convert to 32-bit integer
+    }
+    return hash.abs();
+  }
+
+  /// Generate AI suggestion for a report
+  static AISuggestion generateSuggestion({
+    required String id,
+    required String createdAt,
+    required double lat,
+    required double lng,
+    int? photoSizeBytes,
+  }) {
+    final seed = _generateSeed(id, createdAt, lat, lng, photoSizeBytes);
+    final random = Random(seed);
+
+    // Category selection with weighted probabilities
+    final categoryWeights = {
+      Category.pothole: 0.35,
+      Category.trash: 0.25,
+      Category.streetlight: 0.15,
+      Category.signage: 0.10,
+      Category.drainage: 0.10,
+      Category.other: 0.05,
+    };
+
+    // Apply heuristics based on image dimensions (if available)
+    final aspectRatio = photoSizeBytes != null ? (random.nextDouble() * 2) : 1.0;
+    if (aspectRatio > 1.2) {
+      // Wide image - likely signage
+      categoryWeights[Category.signage] = categoryWeights[Category.signage]! * 2;
+      categoryWeights[Category.pothole] = categoryWeights[Category.pothole]! * 0.5;
+    }
+
+    // Select category based on weights
+    final categoryRand = random.nextDouble();
+    double cumulative = 0.0;
+    Category selectedCategory = Category.pothole;
+
+    for (final entry in categoryWeights.entries) {
+      cumulative += entry.value;
+      if (categoryRand <= cumulative) {
+        selectedCategory = entry.key;
+        break;
+      }
+    }
+
+    // Severity selection with weighted probabilities
+    final severityWeights = {
+      Severity.medium: 0.45,
+      Severity.high: 0.30,
+      Severity.low: 0.25,
+    };
+
+    // Apply location accuracy heuristic
+    final accuracy = random.nextDouble() * 50; // Simulate accuracy 0-50m
+    final isNight = random.nextBool(); // Simulate night time
+
+    if (accuracy <= 10 && isNight) {
+      // High accuracy at night - bump high severity
+      severityWeights[Severity.high] = severityWeights[Severity.high]! * 1.5;
+      severityWeights[Severity.medium] = severityWeights[Severity.medium]! * 0.8;
+    }
+
+    // Select severity based on weights
+    final severityRand = random.nextDouble();
+    cumulative = 0.0;
+    Severity selectedSeverity = Severity.medium;
+
+    for (final entry in severityWeights.entries) {
+      cumulative += entry.value;
+      if (severityRand <= cumulative) {
+        selectedSeverity = entry.key;
+        break;
+      }
+    }
+
+    // Generate confidence score (0.6 - 0.9)
+    final confidence = 0.6 + (random.nextDouble() * 0.3);
+
+    return AISuggestion(
+      category: selectedCategory,
+      severity: selectedSeverity,
+      confidence: confidence,
+    );
+  }
+
+  /// Check if the AI suggestion is reliable enough to use
+  static bool isSuggestionReliable(AISuggestion suggestion) {
+    return suggestion.confidence >= 0.7;
+  }
+
+  /// Get confidence level description
+  static String getConfidenceDescription(double confidence) {
+    if (confidence >= 0.8) {
+      return 'High confidence';
+    } else if (confidence >= 0.7) {
+      return 'Medium confidence';
+    } else {
+      return 'Low confidence';
+    }
+  }
+}