Datasheet for Baggage Handling System Optimization

Introduction

 

About this datasheet

We hope that this datasheet can answer your questions, but should you have any further questions please refer to the DeepAtom support page on our website: www.deepatom.ai/support or reach out to us directly at support@deepatom.ai.

The purpose of this document is to provide a description of DeepAtom’s computer vision system and to describe the correct way to install, integrate and run the system successfully. 

Please read this datasheet thoroughly before operating your new computer vision system for the first time. Please follow all instructions and observe the warnings. 

This document is subject to change without notice. 

“Odd bag problem”

This datasheet focuses entirely on applying our intelligent camera system to solve the “Odd bag problem” to optimize airports Baggage Handling Systems. 

Baggage Handling Systems are continuously faced with a large number of jam-sensitive odd shaped bags that are not compatible with all parts of the intricate conveyor and sortation system. These bags can fall off or get stuck in the system which can severely damage the system and they have been identified as the primary root cause for critical incidents where 100s and sometimes even 1000s of bags get delayed (Newsworthy example: "Holiday flight chaos as Heathrow baggage system breaks down").

In 2017 around 22.7 million bags were delayed, lost or damaged globally due to issues relating to the Baggage Handling System and its operation. And although the criteria that make up jam-sensitive non-compatible bags and bag configurations are well understood by airports and their operators they are not always implemented in practice by the Check-in Agents and Baggage Handling Agents. 

Our cutting-edge computer vision system enhances the effectiveness of the Baggage Handling System by automatically classifying and filtering out jam-sensitive non-compatible bags. 

About DeepAtom

DeepAtom aims to digitize, connect and optimize industrial environments by developing specialized Artificial Intelligence (AI) driven solutions that are intuitively embedded into the operational processes, mechanical infrastructure and software infrastructure through a simple user-centric interface, a light-weight design and a hybrid Internet of Things (IoT) architecture.

DeepAtom’s computer vision systems find use in many industrial applications, such as airport Baggage Handling System (BHS) optimization, visual quality control for manufacturing and condition monitoring for maintenance schedule optimization.

Contact DeepAtom

Website: www.deepatom.ai

Support: support@deepatom.ai

Head office:  Berlin, Germany

About Photon

We have developed a cutting-edge industrial grade high speed computer vision system with outstanding features powered by highly optimized deep neural networks. The Photon is built with the most compact and sophisticated specialized edge computing device for deep learning algorithms allowing us to run the core computer vision system locally which is ideal for industrial low latency applications with high security requirements. 

Our intelligent camera system is the most advanced for this application and combines consistent visual classification with unparalleled traceability and consistency.

Advantages

Table 1.  Description of the advantages of implementing our computer vision solution

Features

Table 2.  Description of the features of our computer vision solution

Certifications

Our Photon computer vision system is a configuration for parts that meet the following certifications.

Table 3.  List of  of the certifications

Operation

 

For proper operation of our DeepAtom camera system there are certain requirements that have to be met. You will read more about these requirements in the following chapters, as well as a description of how to use a DeepAtom camera system.

Hardware requirements

Mechanical frame

It’s important to consider the following factors when designing and installing the mechanical frame when installing the computer vision system to your system.

Table 4. Description of the key factors

TOP VIEW

Drawing 1. Top view showing the position of the Photon in the middle of the conveyor leading up to the sorter

SIDE VIEW

Drawing 2. Side view showing the position of the Photon above the conveyor leading up to the sorter

REAR VIEW

Drawing 3. Rear view showing the position of the Photon above the conveyor leading up to the sorter

LAN & power cables

Each frame needs to be be fitted with a LAN cable and power supply for each camera system.

The LAN cables need to connected the the server infrastructure so that an integration with the SCADA system is possible.

The  power cables need to supply a AC 220 V at 50 Hz with up to 3.5 A per plug with socket type F.

Environmental operating conditions

To ensure reliable operation and performance, the computer vision system should operate in the following environment:

Table 5. Description of the optimal environmental conditions

Software requirements

Dashboard

The Photon web-based dashboard serves as the remote monitoring tool of live system and can be accessed via the DeepAtom websites member section and is compatible with the following browsers: 

  • Google Chrome

  • Mozilla Firefox 

  • Safari

  • Internet Explorer

The dashboard retrieves the information from the DeepAtom API. This data could alternatively be integrated into existing dashboards that are able to display the following:

  • Numbers

  • Charts

  • Videos

SCADA integration

The DeepAtom REST API can be used for custom real-time system integrations and data streaming to the SCADA system.

More information coming soon.  

Data requirements

 

The number of delayed and missing bags are critical KPI's of the BHS and will serve as the performance metrics for the Photon. To get this data multiple date sources need to be merged into one.  To minimize the load on your IT infrastructure we recommend that data requests for the tracking and routing data are made from a historical database at the same frequency as the reporting is required i.e. daily, weekly or monthly, at times when the load is at its minimum.

Layout of the BHS

The layout of the BHS will help with determining the following:

  • Position of all the entry points to the sorter

  • Position of each ID-reader

  • Position of other critical components of the system

Tracking data

Since the IATA Resolution 753 has come into effect in 2018 most airports have made a significant effort to track bags and manage their tracking data more effectively to be in compliance with this new standard. 

The data points required from each bag ID-reader are:

  • ID-reader label

  • Bag ID

  • Timestamp

Routing data

The routing data contains the information about planned journey through the BHS. The data points required are:

  • Bag ID

  • List of expected checkpoint / route labels for each bag

Safety instructions and precautions

This chapter describes the safety instructions and precautions valid for DeepAtom camera systems. In order to avoid harm or damage your DeepAtom camera system, please handle it like described in this datasheet, paying special attention to the cautions in the following sections: 

Heat dissipation

DeepAtom strives to offer the smallest AI-powered computer vision systems with the highest performance. Although the camera systems are first in terms of power efficiency, the high packing density of components can lead to elevated temperatures, and an adequate dissipation of this heat must be ensured. The cameras rely on adequate ventilation so do not cover the cooling holes.

Disassembling

Do not disassemble the computer vision system. There are no switches or parts inside the cameras that requires any kind of mechanical adjustment so do not open the camera housing.​​

Mounting / screwing

Use only the designated threaded holes for mounting the camera. 

Connections

Use only recommended connectors and cables.

Caution: ensure that the cables are connected to the correct ports.

More information coming soon.

Power supply

Use only the recommended electrical power supply.

Caution: Do not attempt to power the board by connecting it to your computer.

Environment / protect against water

Use camera system in acceptable environment only, please note the descriptions in ‘Environmental operating conditions’.

Protect the camera system against contact with water. Do not let camera get wet. 

Damages may be caused by: 

  • Overheating 

  • Contact with water 

  • Operation in an environment with condensing humidity 

  • Mechanical load / shock

Recommended light conditions

Do not expose the camera to light sources with intense energy, e.g. laser beams or X-ray. Light intensity or exposure time exceeding the saturation of the sensor may damage the sensor irreparably. This may occur e.g. in the following situations: 

  • High-energy laser light hitting the sensor directly 

  • Bright light sources hitting the sensor directly (burn-in) 

  • Camera is exposed to X-rays 

Protect the optical components

Do not touch the optical components with hard or abrasive objects. When handling the camera system, avoid touching the lenses and filter glasses. Fingerprints or other impurities may affect the image quality and may damage the surfaces. Keep the camera system in dust free environments at all times. Do not use compressed air as this could push dust into the camera (and lenses). 

Mechanical loads

Avoid excessive shaking, throwing, dropping or any kind of mishandling of the device. 

Camera / lens cleaning

Please follow instructions described below. 

  • Use only optical quality tissue / cloth (dry cotton) a standard camera lens cleaning kit, if you must clean a lens or filter. Do not apply excessive force. 

  • Use only optics cleaner (e.g. 60% ethyl alcohol, 40% ether). Never use aggressive cleaners like gasoline or spirits. Such cleaners may destroy the surface. 

  • Do not use compressed air.