SPECTRUM ENFORCEMENT

# Casualty tracking data structures

@dataclass

class CasualtyReport:

    “””Real-time casualty tracking for Glass visualization”””

    id: str

    timestamp: float

    latitude: float

    longitude: float

    altitude: float  # meters above sea level

    casualty_type: str  # “blood_detected”, “vitals_critical”, “movement_ceased”, “rf_biomarker_anomaly”

    severity: int  # 1-5, with 5 being most critical

    confidence: float  # 0.0-1.0 confidence in detection

    source: str  # Detection source (smartphone_rf, standoff_detection, etc.)

    vitals: Optional[Dict[str, Any]] = None  # Heart rate, respiration if available

    metadata: Dict[str, Any] = None

DOMA-Glass Visualization Integration

# Import DOMA and Signal Intelligence

try:

    from SignalIntelligence.core import (

        SignalIntelligenceSystem,

        DOMASignalTracker,

        RFTrajectoryPoint

    )

    SIGNAL_INTELLIGENCE_AVAILABLE = True

except ImportError as e:

    logger.error(f”Signal Intelligence not available: {e}”)

    SIGNAL_INTELLIGENCE_AVAILABLE = False

# Import Glass Visualization

try:

    from GlassVisualization.core import (

        GlassVisualizationSystem,

        CasualtyReport,

        GeospatialCasualtyCluster

    )

    GLASS_VISUALIZATION_AVAILABLE = True

except ImportError as e:

    logger.error(f”Glass Visualization not available: {e}”)

    GLASS_VISUALIZATION_AVAILABLE = False

@dataclass

class RFTargetTrack:

    “””RF signal target track with motion predictions for Glass display”””

    track_id: str

    signal_id: str

    timestamp: float

    current_position: Tuple[float, float, float]  # lat, lon, alt

    predicted_positions: List[Tuple[float, float, float]]  # Future positions

    velocity: Tuple[float, float, float]  # m/s in x, y, z

    acceleration: Tuple[float, float, float]  # m/s² in x, y, z

    frequency: float  # Hz

    signal_strength: float  # dBm

    motion_type: str  # “linear”, “circular”, “zigzag”, “stationary”, “erratic”

    threat_level: int  # 1-5 (1=minimal, 5=critical)

    confidence: float  # 0.0-1.0

    source_type: str  # “drone”, “aircraft”, “ground_vehicle”, “personnel”, “unknown”

    track_quality: float  # Track quality metric 0.0-1.0

    metadata: Dict[str, Any] = None

Google Glass Real-Time Casualty Visualization

RF biomarker detection with geolocated casualty tracking

for tactical situational awareness and K9 unit replacement.

def _handle_standoff_detection(self, data):

        “””Handle standoff detection”””

        if data.get(“violence_detected”):

            casualty_data = {

                “gps_location”: data.get(“target_location”, {“lat”: 38.8719, “lon”: -77.0563}),

                “blood_detected”: False,

                “confidence”: data.get(“confidence”, 0.8)

            }

            casualty = self.casualty_tracker.process_rf_biomarker_detection(casualty_data)

            casualty[“casualty_type”] = “violence_detected”

            casualty[“source”] = “standoff_detection”

            casualty[“severity”] = data.get(“threat_level”, 3)

            self._display_glass_casualty_alert(casualty)

    def _display_glass_casualty_alert(self, casualty):

        “””Display Glass casualty alert”””

        print(f”\\n🥽 GOOGLE GLASS ALERT 🥽”)

        print(f”═══════════════════════════”)

        print(f”📍 Casualty ID: {casualty[‘id’]}”)

        print(f”🩸 Type: {casualty[‘casualty_type’].replace(‘_’, ‘ ‘).title()}”)

        print(f”📊 Severity: {casualty[‘severity’]}/5″)

        print(f”🎯 Confidence: {casualty[‘confidence’]:.1%}”)

        print(f”📡 Source: {casualty[‘source’].replace(‘_’, ‘ ‘).title()}”)

        print(f”🌍 Location: {casualty[‘latitude’]:.6f}, {casualty[‘longitude’]:.6f}”)

        print(f”⏰ Time: {time.strftime(‘%H:%M:%S’, time.localtime(casualty[‘timestamp’]))}”)

        # Glass UI simulation

        severity_colors = {5: “🔴 CRITICAL”, 4: “🟠 SEVERE”, 3: “🟡 MODERATE”, 2: “🟢 MINOR”, 1: “⚪ MINIMAL”}

        print(f”🎨 Glass Display: {severity_colors.get(casualty[‘severity’], ‘⚫ UNKNOWN’)}”)

        if casualty[‘severity’] >= 4:

            print(f”🚨 IMMEDIATE MEDICAL RESPONSE REQUIRED”)

        elif casualty[‘severity’] >= 3:

            print(f”⚠️ Medical evaluation recommended”)

SCYTHE Tech Demos

************************************

Linux Terminal-based Visualization for Testing the Glass Visualization System

Advanced Glass display interface for real-time RF tracking, casualty visualization,

and tactical overlay capabilities. Provides comprehensive situational awareness

through augmented reality displays.

Features:

– Real-time RF signal tracking overlays

– Casualty detection and medical triage visualization

– Motion prediction paths and threat assessment

– Tactical information display with military-grade precision

– Audio and haptic feedback for critical alerts

class GlassDisplayElement:

    “””Single display element for Glass overlay”””

    element_id: str

    element_type: str  # “track”, “casualty”, “prediction”, “alert”, “info”

    position: Tuple[float, float]  # Screen coordinates (0.0-1.0)

    content: Dict[str, Any]

    priority: int  # 1-10, 10 = highest

    color: Tuple[int, int, int]  # RGB color

    size: str  # “small”, “medium”, “large”

    visibility: float  # 0.0-1.0 opacity

    duration: Optional[float] = None  # Auto-hide after seconds

    timestamp: float = None

    def __post_init__(self):

        if self.timestamp is None:

            self.timestamp = time.time()

    def to_display_json(self) -> Dict[str, Any]:

        “””Convert to Glass-compatible display format”””

        return {

            “id”: self.element_id,

            “type”: self.element_type,

            “x”: self.position[0],

            “y”: self.position[1],

            “content”: self.content,

            “priority”: self.priority,

            “color”: {“r”: self.color[0], “g”: self.color[1], “b”: self.color[2]},

            “size”: self.size,

            “opacity”: self.visibility,

            “duration”: self.duration,

            “timestamp”: self.timestamp

        }