Aquashield

License: MIT

FHIR

IEEE

Model Context Protocol

AquaShield MCP is an autonomous Model Context Protocol (MCP) surveillance network connecting urban freshwater bioassay telemetry directly to IEEE 11073 and HL7 FHIR v4.0.1 digital health standards for municipal early-warning outbreak response.

Built for the OneAquaHealth IEEE Global Hackathon 2026 (Track 7: Digital Health Standards & Track 3: AI-Supported Assessment).

📺 Video Walkthrough & Live Runtime Demo

AquaShield MCP Video Walkthrough

Watch the complete 2-minute architectural demonstration, live dual-stream terminal execution, canonical FHIR schema dereferencing, and edge JSON-RPC 2.0 tool calls:
👉 Watch Live Video Walkthrough

Key Features

• 4PL Non-Linear BioAssay Regression: Computes chemical and microplastic cell viability curves using the 4-Parameter Logistic Hill equation.
• National Sanitation Foundation (NSF) WQI: Geometric weighted indexing of DO, pH, turbidity, and water temperature.
• HL7 FHIR v4.0.1 Conformance: Transforms raw water sensor streams into valid DiagnosticReport and Observation bundles with LOINC (41852-5, 56475-7) and SNOMED-CT (264353000) identifiers.
• Canonical Edge Provenance: Backed by a canonical FHIR StructureDefinition at https://developers.seosiri.com/fhir/extensions/edge-provenance.
• EU GDPR Privacy Interlocks: Automatic SHA-256 geolocation salting for citizen science monitoring.

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Quickstart

# Clone the repository
git clone https://github.com/SEOSiri-Official/aquashield-mcp.git

cd aquashield-mcp

# Install dependencies
pip install -r requirements.txt

# Run the autonomous surveillance pipeline
python aquashield_mcp.py

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AquaShield MCP Benchmark Suite

An automated diagnostic, efficiency, and micro-benchmark framework for the AquaShield Model Context Protocol (MCP) toolset. This module executes stress tests against the foundational environmental engineering, toxicology, and medical-informatics functions to verify latency, floating-point precision, data privacy sanitizers, and HL7 FHIR compliance.

Repository Source: SEOSiri-Official/aquashield-mcp

Benchmark Specifications & Tools Evaluated

The benchmark script rigorously stress-tests 4 primary functional domains within the AquaShield ecosystem over thousands of iterations:

1. 4PL Toxicology Model (compute_4pl)

• Purpose: Evaluates the mathematical limits of the Four-Parameter Logistic regression curve used for toxicity and eco-dose response tracking.
• Verification Targets:
  • Latency tracking per mathematical calculation loop.
  • Boundary Precision validation at precisely EC₅₀ (theoretical target: 50.000000%).
  • Floating-point numerical drift prevention (< 1e-9 zero-divergence threshold).

2. NSF Water Quality Index (compute_wqi)

• Purpose: Validates multi-metric sub-index aggregation algorithms for Dissolved Oxygen (DO), pH, and Turbidity.
• Verification Targets:
  • Dynamic Range evaluation across polar extremes (Pristine vs Hazard).
  • Hardened sub-index multiplier integrity check:
    • DO (0.40) + pH (0.35) + Turbidity (0.25) ≡ 1.00.

3. GDPR Citizen Privacy Sanitizer (sanitize_geo)

• Purpose: Measures telemetry anonymization through 64-bit truncated SHA-256 cryptographic masking.
• Verification Targets:
  • High-throughput processing speeds for citizen geographic tracking payloads.
  • Idempotency checking to ensure zero-collision tracking with a deterministic framework.

4. HL7 FHIR v4.0.1 Transaction Engine (build_fhir_bundle)

• Purpose: Validates generation mechanics for clinical transactional bundles tying water safety data straight to Electronic Health Record (EHR) schemas.
• Verification Targets:
  • Real-time generation throughput for structured JSON payloads.
  • Strict terminology binding validation for:
    • LOINC Codes: 41852-5 (Microbiology) & 56475-7 (E. Coli Observation)
    • SNOMED CT: 264353000 (Environmental Contamination Hazard)
  • URI mapping compliance via developers.seosiri.com.

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Running the Audit Suite

To execute the micro-benchmarks directly and output performance telemetry, run:

python benchmark_audit.py

Verified Runtime Output

======================================================================
 AQUASHIELD MCP: TOOL EFFICIENCY, STRENGTH & BENCHMARK AUDIT
======================================================================

[TOOL 1: 4PL Toxicity Model]

 • Latency per call : 0.0074 ms (~134,423 ops/sec)
 • Boundary Precision: Response at EC50 = 50.000000% (Theoretical: 50.000000%)
 • Numerical Drift   : < 1e-9 (Zero floating-point divergence)

[TOOL 2: NSF Water Quality Index (WQI)]

 • Latency per call : 0.0195 ms (~51,191 ops/sec)
 • Dynamic Range    : Pristine = 98.0 (EXCELLENT) | Hazard = 26.85 (POOR)
 • Weights Verified : DO(0.40) + pH(0.35) + Turbidity(0.25) == 1.00

[TOOL 3: GDPR Citizen Privacy Sanitizer]

 • Latency per call : 0.1249 ms (~8,009 ops/sec)
 • Collision Safety : SHA-256 with 16-hex truncation (64-bit entropy)
 • Determinism Check: 100% Idempotent (Deterministic salt preserves analytical aggregation)

[TOOL 4: HL7 FHIR v4.0.1 Transaction Engine]

 • Bundle Generation: 0.3753 ms (~2,664 bundles/sec)
 • LOINC Codes      : 41852-5 (Microbiology), 56475-7 (E. Coli Observation)
 • SNOMED CT        : 264353000 (Environmental Contamination Hazard)
 • Canonical URI    : https://developers.seosiri.com/fhir/extensions/edge-provenance

======================================================================
 BENCHMARK SUMMARY: SUB-MILLISECOND LATENCY & 0% FLOATING-POINT DRIFT
======================================================================

Architecture & Ecosystem

AquaShield MCP is engineered as part of the SEOSiri Open-Source MCP Infrastructure.

• Master Portal: https://developers.seosiri.com
• Lead Systems Architect: Momenul Ahmad ([email protected] / [email protected])