AM-AV OCC System Research Project

Advancing aviation safety through AI-driven compliance, intelligent crew scheduling, and automated Operations Manual enforcement

Aviation AICompliance EngineNLPOperations Research

Research Overview

Project Mission

The AM-AV OCC System research project aims to revolutionize aviation operations management through artificial intelligence, focusing on zero-tolerance enforcement of safety regulations while optimizing crew satisfaction and operational efficiency. Our research explores the intersection of natural language processing, operations research, and aviation domain expertise to create systems that enhance safety without compromising operational flexibility.

Key Objectives

  • Develop AI-driven compliance engines that parse and enforce aviation regulations from Operations Manuals
  • Create intelligent scheduling algorithms that balance regulatory requirements with crew preferences
  • Build multi-tenant architectures supporting operator-specific rule sets and customizations
  • Advance real-time operations monitoring with predictive analytics and anomaly detection

Research Areas

AI Compliance Engine

Research into natural language processing techniques for parsing aviation regulatory text, extracting rules and constraints, and converting them into executable validation logic. Focus on handling ambiguous language, context-dependent rules, and hierarchical regulation structures.

Key Topics:

  • • Transformer-based NLP for regulatory text
  • • Rule extraction and codification
  • • Zero-tolerance enforcement mechanisms
  • • Audit trail generation

Intelligent Scheduling

Investigation of optimization algorithms for crew rostering that balance multiple objectives: regulatory compliance, operational requirements, crew preferences, and fairness constraints. Exploration of reinforcement learning for adaptive scheduling strategies.

Key Topics:

  • • Multi-objective optimization
  • • Preference-based scheduling
  • • Reinforcement learning for rostering
  • • Fairness and equity metrics

Operations Manual Integration

Development of automated systems for ingesting, parsing, and enforcing ICAO Operations Manuals (OM-A through OM-G). Research into version control, change tracking, and impact analysis when regulations are updated.

Key Topics:

  • • Document parsing and OCR
  • • Regulatory knowledge graphs
  • • Version control and change management
  • • Operator-specific customization

Technical Architecture

System Components

NLP Module

Transformer-based language models (BERT, GPT) fine-tuned on aviation regulatory corpus

Technologies: PyTorch, Hugging Face Transformers, spaCy

Rule Engine

Graph-based rule representation with priority ordering and conflict resolution

Technologies: Neo4j, Drools, Custom DSL

Scheduling Engine

Constraint satisfaction and optimization algorithms for crew rostering

Technologies: OR-Tools, Gurobi, Custom Heuristics

Research Infrastructure

Data Pipeline

Automated ingestion of Operations Manuals, flight schedules, and crew data

Technologies: Apache Airflow, Kafka, PostgreSQL

Evaluation Framework

Metrics for compliance accuracy, scheduling quality, and operational efficiency

Technologies: MLflow, Weights & Biases, Custom Dashboards

Deployment Platform

Cloud-native architecture with multi-tenant isolation and scalability

Technologies: Kubernetes, Docker, AWS/Azure

Collaboration Opportunities

For Researchers

We welcome collaboration with academic researchers in AI, operations research, and aviation safety. Opportunities include:

  • Joint publications in top-tier conferences and journals
  • Access to real-world aviation operations data (anonymized)
  • Funding for PhD students and postdoctoral researchers
  • Internship programs and industry placements

For Industry Partners

Airlines, aviation authorities, and technology companies can participate through:

  • Pilot deployments and field trials of AM-AV OCC System
  • Data sharing agreements for research purposes
  • Co-development of operator-specific features
  • Early access to research findings and prototypes

Publications & Resources

Technical Documentation

Comprehensive system architecture, API references, and implementation guides

Open Source Components

Selected modules and tools released under permissive licenses for community use

Research Papers

Peer-reviewed publications on AI compliance, scheduling algorithms, and aviation safety