Logistics Event Protocol

The Logistics Event Protocol is a machine-readable operational framework designed to model transportation, moving, freight, warehousing, technology relocation, and logistics activities as standardized events.

Rather than treating logistics operations as static records, the protocol represents operational reality as a continuous stream of events that describe changes occurring throughout a transportation lifecycle.

This approach supports event sourcing, state projection, knowledge graph construction, operational analytics, artificial intelligence systems, logistics automation, and future autonomous transportation platforms.

Protocol Objective

The primary objective of the Logistics Event Protocol is to create a common operational language that can be interpreted consistently by humans, software systems, graph databases, search engines, retrieval systems, AI agents, and transportation platforms.

Every operational action becomes an event.

Job Created
    ↓
Estimate Generated
    ↓
Crew Assigned
    ↓
Vehicle Assigned
    ↓
Pickup Started
    ↓
In Transit
    ↓
Delivery Completed

Core Principle: Events Are the Source of Truth

The protocol follows an event-driven architecture.

Instead of storing only the current status of a shipment or move, the system records every significant event that occurred throughout the lifecycle of the operation.

This creates:

• Operational history
• Auditable workflows
• Knowledge graph inputs
• State reconstruction
• AI reasoning context
• Business intelligence capabilities

Event Structure

Every event follows a standardized format.

{
  "event_id":"uuid",
  "event_type":"JOB_CREATED",
  "timestamp":"2026-06-09T14:00:00Z",
  "entity_type":"shipment",
  "entity_id":"SHIP-10001",
  "payload":{}
}

Core Event Categories

Customer Events

• CUSTOMER_CREATED
• CUSTOMER_UPDATED
• CUSTOMER_VERIFIED
• CUSTOMER_ARCHIVED

Estimate Events

• ESTIMATE_GENERATED
• ESTIMATE_SENT
• ESTIMATE_ACCEPTED
• ESTIMATE_REJECTED

Job Events

• JOB_CREATED
• JOB_SCHEDULED
• JOB_MODIFIED
• JOB_CANCELLED
• JOB_COMPLETED

Dispatch Events

• CREW_ASSIGNED
• VEHICLE_ASSIGNED
• EQUIPMENT_ASSIGNED
• ROUTE_GENERATED

Operational Events

• PICKUP_STARTED
• LOADING_STARTED
• IN_TRANSIT
• UNLOADING_STARTED
• DELIVERY_COMPLETED

Risk Events

• DAMAGE_REPORTED
• DELAY_REPORTED
• SAFETY_INCIDENT_REPORTED
• CLAIM_CREATED

State Machine Architecture

The protocol uses state transitions to model operational progress.

CREATED
   ↓
SCHEDULED
   ↓
ASSIGNED
   ↓
IN_PROGRESS
   ↓
IN_TRANSIT
   ↓
DELIVERED
   ↓
COMPLETED

Each event causes a state transition.

Event Processing Layer

The protocol is designed to be consumed by event processing engines.

Examples:

• project_state.py
• event_router.py
• state_store.py
• graph_sync.py

These processors consume events and produce operational state.

State Projection Model

Events represent historical truth.

State projections represent current reality.

Event History
        ↓
State Reducer
        ↓
Current Operational State

Example:

JOB_CREATED
CREW_ASSIGNED
VEHICLE_ASSIGNED
PICKUP_STARTED

Produces:

{
  "status":"pickup_started",
  "crew":"CREW-7",
  "vehicle":"TRUCK-12"
}

Knowledge Graph Integration

Every event can generate graph mutations.

Examples:

(Customer)
    ↓ REQUESTED
(Service)
(Job)
    ↓ ASSIGNED_TO
(Vehicle)
(Job)
    ↓ HANDLED_BY
(Crew)

This allows events to become graph relationships.

JSON-LD Integration

The protocol supports machine-readable exports through JSON-LD.

These exports can be consumed by:

• Search engines
• Knowledge graphs
• Retrieval systems
• GraphRAG systems
• Enterprise AI platforms

Neo4j Integration

Event streams can be projected directly into graph databases.

Supported graph entities include:

• Customers
• Jobs
• Shipments
• Vehicles
• Crews
• Equipment
• Locations

Artificial Intelligence Integration

The Logistics Event Protocol provides structured context for AI systems.

Supported AI capabilities include:

• Dispatch optimization
• Pricing analysis
• Route optimization
• Risk detection
• Delay prediction
• Workload balancing
• Operational simulation

Future Applications

• Autonomous dispatch systems
• AI-powered logistics operations
• Predictive transportation planning
• Knowledge graph reasoning
• Operational digital twins
• Infrastructure intelligence systems

Protocol Summary

The Logistics Event Protocol establishes a machine-readable operational language that converts logistics activities into events, state transitions, graph relationships, and actionable intelligence.

This protocol serves as the foundation for future transportation automation, logistics knowledge graphs, AI agents, retrieval systems, and event-driven logistics operating environments.