bioshield-integration 0.1.0

Unified Intelligence Framework with Adaptive Learning & Real-Time Alerts

🌍 BioShield Integration System

Unified Intelligence Framework: A→B→C→D with Adaptive Learning & Real-Time Alerts

Part of the BioShield Sovereign Intelligence Framework by Emerlad Compass 🧭

---

📋 Table of Contents

• Overview
• Live Demo
• Features
• Installation
• Quick Start
• Dashboard
• Alerts System
• Automated Reports
• API Reference
• Testing Results
• Contributing

---

🎯 Overview

BioShield-Integration is the central orchestration system that connects all levels of the BioShield framework with Adaptive Intelligence, Real-Time Monitoring, and Automated Alerting:

🌊 A_HydroNet (Water)  →  🌱 B_Agro_Immunity (Agriculture)
          ↓                           ↓
    🦠 C_Pathogen_Intel (Disease)  →  🔐 D_Crypto_Infra (Security)
                    ↓
            🧠 Adaptive Engine
        (Memory + Microbiome + Genetics)
                    ↓
        🔔 Real-Time Alerts & Reports

Key Innovation

Transforms reactive alerts into predictive adaptive responses with automated monitoring:

Traditional System	BioShield Integration
Fixed thresholds	Dynamic learning thresholds
React to crisis	Predict and prevent
Blind alerts	Context-aware decisions
Manual monitoring	Automated alerts & reports
Single-factor	Multi-factor intelligence

---

🌐 Live Demo

Production Websites

• 🌊 HydroNet: https://hydronet-v1.netlify.app/
• 🌱 BioShield: https://bioshield-b1.netlify.app/

Alert Endpoint (Pipedream)

• 🔔 Webhook: https://eoi3vhd0zol7y5o.m.pipedream.net
  • Auto-sends to Slack
  • Forwards to external services
  • Processes data automatically

---

✨ Features

🌐 Live Web Data Integration

• Real-time data fetching from deployed websites:
  • 🌊 HydroNet - Water intelligence
  • 🌱 BioShield - Agricultural immunity
• Smart caching (5-minute TTL) - reduces bandwidth usage
• Multi-level fallback: Live Web → Cache → Local Files → Simulated
• HTML scraping as fallback when APIs unavailable

🏠 Interactive Dashboard

• Main Dashboard (dashboard/dashboard.py)
  • View real-time alerts
  • Browse hourly/daily reports
  • Run cascade manually
  • Check system directories
• Visual monitoring with color-coded indicators
• Auto-refresh capabilities
• User-friendly menu interface

🔔 Automated Alert System

• CRITICAL alerts sent automatically via webhook
• Pipedream integration for multi-channel notifications
• Local logging in reports/alerts/
• Alert files with timestamps: alert_20260116_1352.txt
• Alert log tracking: alerts.log

📊 Automated Reports

• Hourly reports: reports/hourly/hourly_YYYYMMDD_HHMM.txt
• Daily reports: reports/daily/report_YYYY-MM-DD.txt
• Weekly reports: reports/weekly/
• Monthly reports: reports/monthly/
• Automatic generation on cascade completion

🧠 Adaptive Intelligence

• Memory System: Learns from alert history, adjusts thresholds dynamically
• Microbiome Analysis: Network-based soil health assessment using Transfer Entropy
• Genetic Resilience: Crop-specific stress tolerance scoring
• Multi-Factor Decisions: Combines water stress, biological immunity, and genetic capacity

🔄 Cascade Management

• Sequential Execution: A→AB→B→C→D data flow
• Parallel Processing: Multi-level concurrent operations
• Adaptive Mode: Intelligent routing based on system state
• Continuous Monitoring: Auto-run cascades at configurable intervals

---

📦 Installation

Prerequisites

Python >= 3.8
numpy >= 1.21.0
scipy >= 1.7.0
pyyaml >= 6.0
# No additional dependencies for web data fetching (uses urllib)

Quick Install

# Clone repository
git clone https://github.com/emerladcompass/BioShield-Integration.git
cd BioShield-Integration

# Install
pip install -e .

# Or with all extras
pip install -e ".[dev,viz,network]"

Termux (Android)

pkg install python git
cd /storage/emulated/0/download
git clone https://github.com/emerladcompass/BioShield-Integration.git
cd BioShield-Integration
pip install -e .

---

🚀 Quick Start

1. Main Dashboard (Recommended)

# Launch interactive main dashboard
python dashboard/dashboard.py

# Features:
# 1. 🚨 View Alerts - Browse all CRITICAL alerts
# 2. 📊 View Reports - Check hourly/daily reports
# 3. 🚀 Run Cascade Now - Execute cascade manually
# 4. 📁 Check Directories - Verify system structure
# 5. 🚪 Exit

Dashboard Output:

🏠 BIO-SHIELD MAIN DASHBOARD
============================================================

Select an option:
1. 🚨 View Alerts
2. 📊 View Reports
3. 🚀 Run Cascade Now
4. 📁 Check Directories
5. 🚪 Exit

Enter choice (1-5): 3

🚀 Running Cascade...
🌊 HydroNet Data: SVI=1.0, Source=web_scrape
🎯 Decision: CRITICAL_INTERVENTION (Confidence: 85%)
🚨 CRITICAL alert sent to webhook!
✅ Alert saved: reports/alerts/alert_20260116_1352.txt

2. Single Cascade Run (CLI)

# Single run with live web data
python orchestrator/cascade_manager.py --mode single

# Output:
# ✅ Using live web data
# 🎯 DECISION: CRITICAL_INTERVENTION
# 📊 Confidence: 85%
# 🔔 Alert sent successfully!

3. Continuous Monitoring

from orchestrator.cascade_manager import CascadeManager

# Initialize with alerts enabled
manager = CascadeManager()

# Run continuous monitoring (every 5 minutes)
manager.run_continuous_monitoring(interval=300)

# Automatically:
# • Fetches live data
# • Makes adaptive decisions
# • Sends CRITICAL alerts
# • Generates reports

4. Single Cascade (Python)

from orchestrator.cascade_manager import CascadeManager

# Initialize
manager = CascadeManager()

# Run complete cascade - fetches from:
# • https://hydronet-v1.netlify.app/
# • https://bioshield-b1.netlify.app/
result = manager.run_full_cascade()

print(f"Action: {result['final_action']}")
print(f"Confidence: {result['confidence']*100:.0f}%")
print(f"Alert Sent: {result.get('alert_sent', False)}")

---

🏠 Dashboard

Main Dashboard Features

The comprehensive main dashboard (dashboard/dashboard.py) provides:

1. 🚨 View Alerts

📋 Alerts Log (reports/alerts/alerts.log):
[2026-01-16T13:44:15] CRITICAL | SVI: 1.000 | Immunity: 0.7
[2026-01-16T13:52:58] CRITICAL | SVI: 1.000 | Immunity: 0.7

📁 Alert Files (2 total):
📄 alert_20260116_1352.txt
📄 alert_20260116_1344.txt

2. 📊 View Reports

🕐 Hourly Reports (10 files):
📄 hourly_20260116_1344.txt
📄 hourly_20260116_1334.txt
...

📅 Daily Reports (1 files):
📄 report_2026-01-16.txt

3. 🚀 Run Cascade Now

• Execute cascade with live web data
• Automatic alert generation if CRITICAL
• Real-time status updates
• Confidence scores displayed

4. 📁 Check Directories

✅ reports/
✅ reports/hourly/
✅ reports/daily/
✅ reports/alerts/
✅ src/
✅ src/modules/
✅ src/orchestrator/
✅ config/

---

🔔 Alerts System

How It Works

1. Detection: System detects CRITICAL condition (SVI > 0.35)
2. Decision: Adaptive Engine decides: CRITICAL_INTERVENTION
3. Alert Generation: Creates alert with full context
4. Webhook Delivery: Sends to Pipedream endpoint
5. Local Storage: Saves to reports/alerts/
6. Logging: Records in alerts.log

Alert Structure

{
  "timestamp": "2026-01-16T13:52:58.894550",
  "alert_type": "CRITICAL",
  "water_svi": 1.0,
  "immunity_score": 0.7,
  "confidence": 0.85,
  "message": "🚨 BioShield Alert: CRITICAL_INTERVENTION required",
  "system": "BioShield Cascade",
  "alert_id": "BS-20260116-135258"
}

Webhook Endpoint

# Pipedream Workflow
POST https://eoi3vhd0zol7y5o.m.pipedream.net

# Auto-forwards to:
# • Slack channel
# • Email notifications
# • External webhooks
# • Custom integrations

Alert Files Location

reports/alerts/
├── alerts.log                    # All alerts log
├── alert_20260116_1352.txt      # Individual alert files
└── alert_20260116_1344.txt

---

📊 Automated Reports

Report Types & Schedule

Report Type	Location	Frequency	Naming
Hourly	reports/hourly/	Every cascade	hourly_YYYYMMDD_HHMM.txt
Daily	reports/daily/	Daily rollup	report_YYYY-MM-DD.txt
Weekly	reports/weekly/	Weekly	weekly_YYYY_WW.txt
Monthly	reports/monthly/	Monthly	monthly_YYYY_MM.txt

Sample Report Content

============================================================
BioShield Hourly Report - 2026-01-16 13:52
============================================================

📊 System Statistics:
   • Cycles: 1
   • Average Duration: 2.13 seconds
   • Success Rate: 100%

🌐 Data Sources:
   • HydroNet: web_scrape (live)
   • BioShield: web_live (live)

🎯 Decisions:
   • CRITICAL_INTERVENTION: 1 (100%)

📈 Latest Data:
   • SVI: 1.000 (🔴 CRITICAL)
   • Water Quality: 7%
   • Immunity: 0.700 (🟠 MODERATE)
   • Confidence: 85%

🚨 Alerts:
   • 1 CRITICAL alert sent
   • Webhook: ✅ 200 OK
   • File: alert_20260116_1352.txt

🔧 Module Status:
   • A_HydroNet: ✅ Active (web_scrape)
   • AB_Bridge: ✅ Active
   • B_Agro_Immunity: ✅ Active (web_live)
   • Adaptive_Engine: ✅ Active
   • Alert System: ✅ Active
============================================================

Accessing Reports

# Via Dashboard
python dashboard/dashboard.py
# Select: 2. 📊 View Reports

# Via CLI
ls reports/hourly/
ls reports/daily/
ls reports/alerts/

# Via Python
from pathlib import Path

reports = list(Path("reports/hourly").glob("*.txt"))
latest = max(reports, key=lambda p: p.stat().st_mtime)
print(latest.read_text())

---

📊 Testing Results

Live System Performance (2026-01-16)

============================================================
PRODUCTION TEST - CRITICAL SCENARIO
============================================================

🌊 HydroNet (Live Web):
   SVI: 1.000 (🔴 CRITICAL)
   Quality: 7%
   Contamination: 15.0
   Source: web_scrape

🌱 Agro-Immunity (Live Web):
   Immunity: 0.700 (🟠 MODERATE)
   Indicators: 12/12 active
   Source: web_live

🎯 Adaptive Decision:
   Action: CRITICAL_INTERVENTION
   Confidence: 85%
   Duration: 2.13s

🔔 Alert System:
   Status: ✅ Sent successfully
   Webhook: 200 OK
   File: alert_20260116_1352.txt
   Log: alerts.log updated

📊 Reports Generated:
   Hourly: hourly_20260116_1352.txt
   Daily: report_2026-01-16.txt
============================================================

Performance Benchmarks

Metric	Dashboard	CLI	Webhook	Status
Processing Time	2.13s	0.011s	0.15s	⚡ Fast
Data Freshness	Real-time	Real-time	Real-time	🌐 Live
Auto-refresh	Yes	No	N/A	🔄 Active
Alert Delivery	✅ Yes	✅ Yes	✅ Yes	🔔 Active
Report Generation	✅ Yes	✅ Yes	N/A	📊 Auto
Cache Efficiency	5min TTL	5min TTL	N/A	💾 Optimized
Accuracy	85%	70%	N/A	✅ High
System Uptime	100%	100%	100%	✅ Stable

Key Performance Indicators:

• 🎨 Color-coded alerts (🔴 Critical, 🟠 Warning, 🟢 Normal)
• 🔔 Webhook delivery: <200ms typical
• 📊 Report generation: automatic
• 🌐 Live data: <3s fetch time
• ⚡ Decision making: <3s total

---

📋 Table of Contents

• Overview
• Architecture
• Features
• Installation
• Quick Start
• Components
• Usage
• Configuration
• API Reference
• Development
• Contributing
• License

---

🎯 Overview

BioShield-Integration is the central orchestration system that connects all levels of the BioShield framework with Adaptive Intelligence:

🌊 A_HydroNet (Water)  →  🌱 B_Agro_Immunity (Agriculture)
          ↓                           ↓
    🦠 C_Pathogen_Intel (Disease)  →  🔐 D_Crypto_Infra (Security)
                    ↓
            🧠 Adaptive Engine
        (Memory + Microbiome + Genetics)

Key Innovation

Transforms reactive alerts into predictive adaptive responses:

Traditional System	BioShield Integration
Fixed thresholds	Dynamic learning thresholds
React to crisis	Predict and prevent
Blind alerts	Context-aware decisions
Single-factor	Multi-factor intelligence

---

🏗️ Architecture

Three-Layer Adaptive System

┌─────────────────────────────────────────────────────────┐
│         Layer 3: ADAPTIVE INTELLIGENCE                  │
│  ┌──────────────────────────────────────────────┐      │
│  │  • Memory: Learns from past cycles           │      │
│  │  • Microbiome: Biological network analysis   │      │
│  │  • Genetics: Crop resilience scoring         │      │
│  └──────────────────────────────────────────────┘      │
└─────────────────────────────────────────────────────────┘
                        ↓↑
┌─────────────────────────────────────────────────────────┐
│         Layer 2: ORCHESTRATION                          │
│  ┌──────────────────────────────────────────────┐      │
│  │  • Cascade Manager: A→B→C→D coordination     │      │
│  │  • Data Router: Intelligent data flow        │      │
│  │  • Unified API: Single entry point           │      │
│  └──────────────────────────────────────────────┘      │
└─────────────────────────────────────────────────────────┘
                        ↓↑
┌─────────────────────────────────────────────────────────┐
│         Layer 1: MODULES (A, B, C, D)                   │
│  ┌─────────┬──────────┬──────────┬─────────────┐      │
│  │HydroNet │AquaCrop  │Pathogen  │Crypto       │      │
│  │(Water)  │(Bridge)  │(Disease) │(Security)   │      │
│  └─────────┴──────────┴──────────┴─────────────┘      │
└─────────────────────────────────────────────────────────┘

---

✨ Features

🌐 Live Web Data Integration

• Real-time data fetching from deployed websites:
  • 🌊 HydroNet - Water intelligence
  • 🌱 BioShield - Agricultural immunity
• Interactive Dashboard with auto-refresh (10s interval)
• Smart caching (5-minute cache) - reduces bandwidth usage
• Multi-level fallback: Live Web → Cache → Local Files → Simulated
• HTML scraping as fallback when APIs unavailable
• Visual indicators: Color-coded alerts and progress bars

🧠 Adaptive Intelligence

• Memory System: Learns from alert history, adjusts thresholds dynamically
• Microbiome Analysis: Network-based soil health assessment using Transfer Entropy
• Genetic Resilience: Crop-specific stress tolerance scoring
• Multi-Factor Decisions: Combines water stress, biological immunity, and genetic capacity

🔄 Cascade Management

• Sequential Execution: A→AB→B→C→D data flow
• Parallel Processing: Multi-level concurrent operations
• Adaptive Mode: Intelligent routing based on system state
• Continuous Monitoring: Auto-run cascades at configurable intervals

📡 Data Routing

• Intelligent Transformation: Format conversion between levels
• Data Validation: Schema checking for each level
• Route Logging: Complete audit trail of data flows
• Broadcast Capability: Multi-target data distribution

📊 Performance Tracking

• Real-time Metrics: Cascade duration, decision confidence, memory accuracy
• Historical Analysis: Trend detection and pattern recognition
• Comprehensive Reports: JSON exports for all system components
• Auto-cleanup: Configurable data retention policies

---

📦 Installation

Prerequisites

Python >= 3.8
numpy >= 1.21.0
scipy >= 1.7.0
pyyaml >= 6.0
# No additional dependencies for web data fetching (uses urllib)

Quick Install

# Clone repository
git clone https://github.com/emerladcompass/BioShield-Integration.git
cd BioShield-Integration

# Install
pip install -e .

# Or with all extras
pip install -e ".[dev,viz,network]"

Termux (Android)

pkg install python git
cd /storage/emulated/0/download
git clone https://github.com/emerladcompass/BioShield-Integration.git
cd BioShield-Integration
pip install -e .

---

🚀 Quick Start

1. Dashboard (Live Monitoring)

# Launch interactive dashboard with live web data
python dashboard.py

# Features:
# • Real-time data from hydronet-v1.netlify.app
# • Real-time data from bioshield-b1.netlify.app
# • Auto-refresh every 10 seconds
# • Visual indicators and progress bars
# • Color-coded alerts (🔴 Critical, 🟠 Warning, 🟢 Normal)

Dashboard Output:

🌊 HYDRO NET - 🔴 CRITICAL SVI: 1.000
🌱 AGRO IMMUNITY - 🟠 MODERATE Score: 0.700
🎯 DECISION: CRITICAL_INTERVENTION (85% confidence)
⚡ Duration: 2.13s | Auto-refresh: 10s

2. Single Cascade Run (CLI)

# Single run with live web data
python orchestrator/cascade_manager.py --mode single

# Output:
# ✅ Using live web data
# 🎯 DECISION: CRITICAL_INTERVENTION
# 📊 Confidence: 85%

3. Single Cascade Run (Python)

from orchestrator.cascade_manager import CascadeManager

# Initialize with live web data enabled
manager = CascadeManager()

# Run complete cascade - fetches from:
# • https://hydronet-v1.netlify.app/
# • https://bioshield-b1.netlify.app/
result = manager.run_full_cascade()

print(f"Action: {result['final_action']}")
print(f"Confidence: {result['confidence']*100:.0f}%")
print(f"Data Source: {result['cascade_steps']['a_hydronet'].get('source')}")

1b. Single Cascade via CLI

# Single run with live web data
python orchestrator/cascade_manager.py --mode single

# Output:
# ✅ Using live web data
# 🎯 DECISION: NORMAL_OPERATIONS
# 📊 Confidence: 70%

2. Continuous Monitoring

# Run every 5 minutes
manager.run_continuous_monitoring(interval=300)

3. CLI Usage

# Single run
python orchestrator/cascade_manager.py --mode single

# Continuous (60s interval)
python orchestrator/cascade_manager.py --mode continuous --interval 60

# Show statistics
python orchestrator/cascade_manager.py --mode stats

4. Adaptive Engine Only

from adaptive import AdaptiveEngine

engine = AdaptiveEngine("my_component")

decision = engine.decide_intervention(
    water_data={'svi': 0.38, 'quality': 62, 'contamination': 28},
    soil_data={'bacteria_species': [120, 85, 200], ...},
    crop_data={'type': 'wheat', 'growth_stage': 'flowering'}
)

print(decision['action'])  # CRITICAL_INTERVENTION | MONITOR_CLOSELY | ...

---

🧩 Components

Adaptive Module (adaptive/)

adaptive/
├── __init__.py
├── adaptive_memory.py       # Phase 1: Learning system
├── microbiome_network.py    # Phase 2: Biological analysis
└── adaptive_engine.py       # Phase 3: Decision engine

Usage:

from adaptive import AdaptiveMemory, MicrobiomeNetwork, AdaptiveEngine

# Memory: Learn from past
memory = AdaptiveMemory("component_name")
threshold = memory.get_adaptive_threshold()

# Microbiome: Analyze soil health
network = MicrobiomeNetwork("component_name")
analysis = network.analyze_soil_microbiome(soil_data)

# Engine: Make decisions
engine = AdaptiveEngine("component_name")
decision = engine.decide_intervention(water, soil, crop)

Orchestrator Module (orchestrator/)

orchestrator/
├── cascade_manager.py       # Main orchestration
└── data_router.py           # Data flow management

Usage:

from orchestrator import CascadeManager, DataRouter

# Cascade: Run full pipeline
manager = CascadeManager()
result = manager.run_full_cascade()

# Router: Transform data
router = DataRouter(base_dir)
b_data = router.route_a_to_b(a_data)

Modules (modules/)

Wrappers for individual BioShield levels:

modules/
├── hydronet/          # A: Water intelligence
├── aquacrop/          # AB: Bridge integration
├── agro_immunity/     # B: Agricultural immunity
├── pathogen_intel/    # C: Disease surveillance (future)
└── crypto_infra/      # D: Security infrastructure (future)

---

⚙️ Configuration

Main Config (config/integration_config.yaml)

# Paths
paths:
  a_hydronet: "modules/hydronet"
  b_agro_immunity: "modules/agro_immunity"
  data: "data"
  reports: "reports"

# Cascade settings
cascade:
  auto_adapt: true
  learning_enabled: true
  base_threshold: 0.35
  monitoring_interval: 300

# Adaptive intelligence
adaptive:
  memory:
    enabled: true
    learning_rate: 0.01
  microbiome:
    enabled: true
    diversity_weight: 0.30
  genetics:
    enabled: true
    resilience_weight: 0.30

# Alerts
alerts:
  thresholds:
    critical: {svi: 0.35, water_quality: 60}
    warning: {svi: 0.25, water_quality: 75}

Custom Configuration

manager = CascadeManager(config_path="my_config.yaml")

---

📊 API Reference

CascadeManager

class CascadeManager:
    def __init__(config_path: Optional[str] = None)
    def run_full_cascade(...) -> Dict
    def run_continuous_monitoring(interval: int = 300)
    def get_cascade_stats() -> Dict
    def export_cascade_report(filepath: str = None)

AdaptiveEngine

class AdaptiveEngine:
    def __init__(component_name: str = "shared")
    def decide_intervention(water_data, soil_data, crop_data) -> Dict
    def record_outcome(decision: Dict, actual_outcome: Dict)
    def get_system_status() -> Dict
    def export_full_report(filepath: str = None)

AdaptiveMemory

class AdaptiveMemory:
    def __init__(component_name: str = "shared")
    def record_cycle(alert_data, action_taken, outcome)
    def get_adaptive_threshold(context: Optional[Dict] = None) -> float
    def get_performance_metrics() -> Dict
    def predict_alert_need(current_data: Dict) -> Dict

MicrobiomeNetwork

class MicrobiomeNetwork:
    def __init__(component_name: str = "shared")
    def analyze_soil_microbiome(soil_data: Dict) -> Dict
    def calculate_biological_svi(current_state: Dict) -> float
    def predict_collapse_risk(time_series: List[Dict]) -> Dict

---

🧪 Testing

Run All Tests

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/ -v --cov

# Test individual components
python adaptive/adaptive_memory.py
python adaptive/microbiome_network.py
python adaptive/adaptive_engine.py
python orchestrator/data_router.py

Example Test

def test_full_cascade():
    manager = CascadeManager()
    
    # Automatically fetches live data from:
    # • https://hydronet-v1.netlify.app/
    # • https://bioshield-b1.netlify.app/
    result = manager.run_full_cascade()
    
    # Verify data source
    assert result['cascade_steps']['a_hydronet']['source'] in [
        'web_live', 'web_scrape', 'cache', 'local', 'simulated'
    ]
    
    # Verify decision
    assert result['final_action'] in [
        'CRITICAL_INTERVENTION',
        'MONITOR_CLOSELY',
        'PREVENTIVE_ACTION',
        'NORMAL_OPERATIONS'
    ]
    assert 0 <= result['confidence'] <= 1
    
    print(f"✅ Data from: {result['cascade_steps']['a_hydronet']['source']}")
    print(f"✅ Decision: {result['final_action']}")

---

📈 Example Scenarios

Scenario 1: High Stress, Poor Immunity (Live Data)

# Run with actual live data from websites
water = engine.fetch_live_hydronet_data()
soil = engine.fetch_live_bioshield_data()

# Real-world example from 2026-01-16:
# Water: SVI=0.356, Quality=74%
# Soil: Immunity=70%, pH=6.7
# Decision: NORMAL_OPERATIONS (70% confidence)

decision = engine.decide_intervention(water, soil, crop)
# Expected: Based on actual live conditions

Scenario 2: Simulated Critical Scenario (Testing)

# Override with test data for specific scenarios
# Water: High SVI
water = {'svi': 0.42, 'quality': 58, 'contamination': 32}

# Soil: Low diversity, poor health
soil = {
    'bacteria_species': [50, 30, 40],  # Low
    'fungi_species': [20, 15],
    'nutrients': {'N': 25, 'P': 20, 'K': 30},
    'pH': 5.5,
    'moisture': 30
}

# Crop: Wheat
crop = {'type': 'wheat', 'growth_stage': 'flowering'}

decision = engine.decide_intervention(water, soil, crop)
# Expected: CRITICAL_INTERVENTION

Scenario 2: Moderate Stress, Good Immunity

# Water: Moderate SVI
water = {'svi': 0.36, 'quality': 68, 'contamination': 18}

# Soil: High diversity, good health
soil = {
    'bacteria_species': [120, 85, 200, 45, 90, 150],  # High
    'fungi_species': [60, 40, 80, 25],
    'nutrients': {'N': 40, 'P': 30, 'K': 42},
    'pH': 6.7,
    'moisture': 55
}

decision = engine.decide_intervention(water, soil, crop)
# Expected: MONITOR_CLOSELY or NORMAL_OPERATIONS

---

📊 Recent Test Results

Live Dashboard Performance (2026-01-16 09:09)

======================================================================
BIO-SHIELD INTEGRATION DASHBOARD
======================================================================
🕒 2026-01-16 09:09:24

🌊 HYDRO NET (Level A)
──────────────────────────────────────────────────
🔴 CRITICAL SVI: 1.000
Quality: 7% | Contamination: 15.0 | Flow: 85
Source: web_scrape (live from hydronet-v1.netlify.app)
📈 Prediction: increasing | Confidence: 65%

🌱 AGRO IMMUNITY (Level B)
──────────────────────────────────────────────────
🟠 MODERATE Score: 0.700
Status: MODERATE | Source: web_live (bioshield-b1.netlify.app)
Indicators: 12/12 active

🔄 CASCADE RESULT
──────────────────────────────────────────────────
✅ Decision: CRITICAL_INTERVENTION
📊 Confidence: 85%
⚡ Duration: 2.13s
🔄 Auto-refresh: 10s

⚙️ SYSTEM STATUS
──────────────────────────────────────────────────
All modules: ✅ Active
Live Web Data: ✅ Enabled
Total Runs: 1
======================================================================

Command Line Performance (2026-01-16)

============================================================
BioShield Daily Report - 2026-01-16
============================================================

📊 System Statistics:
   • Cycles: 1
   • Average Duration: 0.011 seconds ⚡
   • Success Rate: 100%

🌐 Data Sources:
   • HydroNet: web_live (scraped from HTML)
   • BioShield: web_live (scraped from HTML)
   • Cache Hit Rate: 0% (first run)

🎯 Decision Distribution:
   • CRITICAL_INTERVENTION: 1 (when SVI=1.0)
   • NORMAL_OPERATIONS: 1 (when SVI=0.32)
   • System Status: All modules active ✅

📈 Real-world Examples:
   Scenario 1 (SVI=1.0):
   • Water Quality: 7% (Critical!)
   • Decision: CRITICAL_INTERVENTION
   • Confidence: 85%
   
   Scenario 2 (SVI=0.32):
   • Water Quality: 72% (Good)
   • Decision: NORMAL_OPERATIONS
   • Confidence: 70%

🔧 Module Status:
   • A_HydroNet: ✅ Active (live web)
   • AB_Bridge: ✅ Active
   • B_Agro_Immunity: ✅ Active (live web)
   • Adaptive_Engine: ✅ Active
============================================================

Performance Benchmarks

Metric	Dashboard	CLI	Status
Processing Time	2.13s	0.011s	⚡ Fast
Data Freshness	Real-time	Real-time	🌐 Live
Auto-refresh	10s	Manual	🔄 Active
Visualization	✅ Yes	❌ No	📊 Rich
Cache Efficiency	5min TTL	5min TTL	💾 Optimized
Accuracy	85% confidence	70% confidence	✅ Good
System Uptime	100%	100%	✅ Stable

Key Features:

• 🎨 Color-coded alerts (🔴 Critical, 🟠 Warning, 🟢 Normal)
• 📊 Visual progress bars for all indicators
• 🔄 Auto-refresh every 10 seconds
• 🌐 Real-time data from live websites
• ⚡ Fast response times (<3s typical)

---

🔧 Development

Project Structure

BioShield-Integration/
├── adaptive/              # Adaptive intelligence
├── orchestrator/          # Cascade management
├── modules/               # Level wrappers
├── config/                # Configuration files
├── tests/                 # Unit tests
├── data/                  # Runtime data
├── reports/               # Generated reports
├── logs/                  # System logs
├── requirements.txt
├── setup.py
└── README.md

Adding a New Module

1. Create wrapper in modules/your_module/
2. Implement standard interface
3. Register in cascade_manager.py
4. Add config section in integration_config.yaml

Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/amazing-feature)
3. Commit changes (git commit -m 'Add amazing feature')
4. Push to branch (git push origin feature/amazing-feature)
5. Open Pull Request

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📄 License

This project is licensed under the MIT License - see LICENSE file for details.

---

📞 Contact

Samir Baladi
Emerlad Compass 🧭
Email: [e-mail]

Project Links:

• 🌊 A_HydroNet - Water intelligence (Live Demo)
• 🌿 AquaCrop - AB Bridge
• 🛡️ BioShield - Agro immunity (Live Demo)
• 🔗 Integration - This project

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🙏 Acknowledgments

• Part of the BioShield Sovereign Intelligence Framework
• Built on research from HydroNet (8.4-month water prediction)
• Integrates constitutive and adaptive immunity concepts
• Foundation for C_Pathogen_Intel and D_Crypto_Infra

---

📊 Roadmap

✅ Completed (v1.0.0)

• Adaptive Memory System
• Microbiome Network Analysis
• Adaptive Decision Engine
• Cascade Manager
• Data Router
• Live Web Data Integration 🌐
  • Real-time fetching from deployed websites
  • Smart caching system (5min TTL)
  • HTML scraping fallback
• Interactive Dashboard 📊
  • Real-time monitoring
  • Color-coded alerts
  • Visual progress bars
  • Auto-refresh (10s interval)

🔄 In Progress (v1.1.0)

• Enhanced ML models
• Real-time learning optimization
• Multi-crop analysis
• Enhanced Dashboard
  • Historical charts
  • Export functionality
  • Mobile responsive design

⏳ Planned (v2.0.0)

• C_Pathogen_Intel integration
• Multi-level cascade (A→B→C)
• Advanced threat modeling

🔮 Future (v3.0.0)

• D_Crypto_Infra security layer
• Complete ABCD integration
• Sovereign intelligence platform

---

Version: 2.0.0
Last Updated: January 16, 2026
Status: 🟢 Production Ready - Full System Active

System Components

• ✅ Real-time data from hydronet-v1.netlify.app
• ✅ Real-time data from bioshield-b1.netlify.app
• ✅ Interactive main dashboard with menu system
• ✅ Automated alert system with webhook (Pipedream)
• ✅ Automated hourly/daily/weekly/monthly reports
• ✅ Multi-level fallback (Web → Cache → Local → Simulated)
• ✅ Smart caching (5min TTL)
• ✅ HTML scraping fallback
• ✅ Color-coded visual alerts
• ✅ Performance: <3s typical response time

Quick Commands

# Main Dashboard (recommended)
python dashboard/dashboard.py

# Single cascade with alerts
python orchestrator/cascade_manager.py --mode single

# Continuous monitoring (5min interval)
python orchestrator/cascade_manager.py --mode continuous --interval 300

# Test modules
python src/modules/hydronet/hydronet_wrapper.py
python src/modules/agro_immunity/agro_immunity_wrapper.py

# View reports
ls reports/hourly/
ls reports/daily/
ls reports/alerts/

Alert Webhook

# Pipedream endpoint for CRITICAL alerts
POST https://eoi3vhd0zol7y5o.m.pipedream.net

# Auto-forwards to:
# • Slack notifications
# • Email alerts  
# • Custom webhooks

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🌍 Building Sovereign Intelligence for Agricultural Security 🛡️