WIA-DEF-018

import { MilitaryAI } from '@wia/def-018';

// Initialize military AI system with ethical constraints
const ai = new MilitaryAI({
  domain: 'TACTICAL_OPERATIONS',
  humanOversight: 'REQUIRED',
  ethicalFramework: 'INTERNATIONAL_HUMANITARIAN_LAW',
  classification: 'SECRET'
});

// Load target recognition model
const targetRecognition = await ai.loadModel({
  modelId: 'YOLOv8-Military-v3',
  task: 'OBJECT_DETECTION',
  classes: ['tank', 'apc', 'artillery', 'aircraft', 'soldier'],
  accuracy: 0.999,
  hardwareAcceleration: 'NVIDIA_JETSON_AGX'
});

// Process real-time video feed from UAV
const videoStream = await ai.connectSensor({
  type: 'EO_IR_CAMERA',
  resolution: '4K',
  frameRate: 30,
  source: 'UAV-REAPER-042'
});

// Run target detection
videoStream.on('frame', async (frame) => {
  const detections = await targetRecognition.detect({
    image: frame,
    confidenceThreshold: 0.95,
    nmsThreshold: 0.4
  });

  detections.forEach(detection => {
    console.log(`Detected: ${detection.class}`);
    console.log(`Confidence: ${(detection.confidence * 100).toFixed(2)}%`);
    console.log(`Location: (${detection.bbox.x}, ${detection.bbox.y})`);
    console.log(`Size: ${detection.bbox.width}x${detection.bbox.height}`);
  });

  // Threat assessment using decision support AI
  const threatAnalysis = await ai.assessThreat({
    detections: detections,
    context: {
      location: { lat: 33.3152, lon: 44.3661 },
      friendlyForces: await ai.getFriendlyPositions(),
      rules_of_engagement: 'DEFENSIVE_ONLY'
    }
  });

  console.log('Threat Level:', threatAnalysis.level); // LOW, MEDIUM, HIGH, CRITICAL
  console.log('Recommended Action:', threatAnalysis.recommendation);
  console.log('Confidence:', threatAnalysis.confidence);

  // Request human authorization for lethal action
  if (threatAnalysis.level === 'CRITICAL') {
    const authorization = await ai.requestHumanAuthorization({
      threat: threatAnalysis,
      proposedAction: 'KINETIC_STRIKE',
      timeWindow: 300 // 5 minutes
    });

    if (authorization.approved) {
      console.log('Authorization granted by:', authorization.approver);
      console.log('Authorization code:', authorization.code);
      // Execute only with human approval
    }
  }
});

// Predictive intelligence for enemy movements
const prediction = await ai.predict({
  model: 'ENEMY_MOVEMENT_FORECAST',
  inputs: {
    historical_positions: enemyPositions,
    terrain_data: terrainMap,
    weather: currentWeather,
    intelligence_reports: recentIntel
  },
  horizon: '24_HOURS'
});

console.log('Predicted enemy positions:');
prediction.forecasts.forEach((forecast, hour) => {
  console.log(`Hour ${hour}: Lat ${forecast.lat}, Lon ${forecast.lon}`);
  console.log(`Confidence: ${(forecast.confidence * 100).toFixed(1)}%`);
});

// Natural language intelligence processing
const nlp = await ai.loadModel({
  modelId: 'MILITARY_NLP_v2',
  task: 'TRANSLATION_AND_ANALYSIS',
  languages: ['ar', 'ru', 'zh', 'fa', 'ko']
});

const interceptedMessage = `قواتنا ستتحرك عند الفجر`;
const analysis = await nlp.analyze({
  text: interceptedMessage,
  sourceLang: 'ar',
  targetLang: 'en',
  tasks: ['TRANSLATION', 'SENTIMENT', 'ENTITY_EXTRACTION', 'THREAT_DETECTION']
});

console.log('Translation:', analysis.translation);
// "Our forces will move at dawn"
console.log('Sentiment:', analysis.sentiment); // HOSTILE, NEUTRAL, FRIENDLY
console.log('Entities:', analysis.entities);
// [{type: 'ORGANIZATION', text: 'our forces'}, {type: 'TIME', text: 'dawn'}]
console.log('Threat Assessment:', analysis.threatScore); // 0-100

// Explainability and transparency
const explanation = await targetRecognition.explain({
  detection: detections[0],
  method: 'GRAD_CAM' // Gradient-weighted Class Activation Mapping
});

console.log('Decision factors:');
explanation.factors.forEach(factor => {
  console.log(`- ${factor.feature}: ${factor.importance.toFixed(3)}`);
});
// Visual heatmap showing which image regions influenced decision

// Model monitoring and adversarial robustness
const robustnessTest = await ai.testRobustness({
  model: targetRecognition,
  attacks: ['FGSM', 'PGD', 'C&W'],
  perturbationBudget: 0.05
});

console.log('Adversarial robustness:', robustnessTest.accuracy);
console.log('Certified radius:', robustnessTest.certifiedRadius);