TırGöz — Loading session intelligence and route optimization

Real-Time Intelligence for Every Loading Dock.

This project aims to develop a logistics monitoring and optimization platform that integrates computer vision and vehicle routing optimization to enhance efficiency in loading docks and distribution centers. The system processes live video streams from cameras to automatically detect anomalies and damages during cargo loading, track goods entering and exiting inventory, validate loading-session constraints, and perform real-time route optimization based on dynamic conditions.

Meet the Team Access Documents
CAM-04 / LOADING DOCK B REC
Anomaly 0.91
Inventory +12
Session ETA 18m
Loading Session

Dock B / Session 18

Tracks boxes entering the truck, flags wrong-item events, and keeps the session manifest in sync.

Inventory Event

Goods Added / Goods Exited

Updates inventory movement when goods enter or leave the warehouse flow and checks quantity constraints.

Constraint Check

Split Order Warning

Detects loading-session rule breaks such as split orders, wrong destination groups, or unsafe sequencing.

Key Objectives

Key Objectives

1- Loading Anomaly & Damage Detection

Detect crushed boxes, torn packaging, misplacement, wrong-item loading, and unsafe stacking during loading sessions through live video using deep learning models.

2- Inventory Management

Track goods entering and exiting inventory, update loading-session manifests, and check item, quantity, and destination constraints through object detection.

3- Dynamic Route Optimization

Optimize delivery plans using multi-depot vehicle routing with capacity and time constraints, re-planning based on real-time loading-session CV events.

0 Core Team Members
0 Deliverables
0 Loading Intelligence Modules
0 Real-Time Loading Sessions

Demo Videos

Project Demonstration

Live demonstrations of the loading-session computer vision modules in action.

Wrong Item Detection

YOLO-based monitoring for detecting item-level loading-session anomalies.

Split Order Detection

Computer vision workflow demonstration for identifying split-order loading issues and constraint violations.

Team

Meet The Team