AI

FOR MINING

OVERLAND CONVEYOR UPTIME OPTIMIZATION

PIXEL 576 COMPUTER VISION SOLUTION

 

CASE STUDY: 

OVERLAND CONVEYOR UPTIME OPTIMIZATION


 

About Deepatom:

Deepatom aims to digitize, connect and optimize the physical reality by developing specialized AI solutions for industry that are intuitively embedded into the system and the operational processes through a hybrid IoT infrastructure and a simple user-centric interface.

 

Problem:

Airport baggage handling systems typically have a throughput efficiency of 65%. These systems are continuously faced with a large number of odd bags that are not compatible with all parts of the system. To try to fix this operators intervene manually and this prevents the system of working at maximum capacity.

The odd bags also lead to an increased amount of bags that miss the flight they are supposed to be on with its departing passenger. In 2017 around 22.7 million bags were mishandled globally due to issues relating to the baggage handling system and its operation.
 

Solution:

Deepatom has developed a cutting-edge computer vision system called Pixel 576 that enhances the effectiveness of human baggage handling system operators. Pixel 576 automatically identifies and filters out odd bags that would lead to problems. Pixel 576 can be trained by baggage system experts and improves continually. Pixel 576 is powered by state of the art deep learning powered software that combines consistent visual classification with unparalleled traceability and consistency. Pixel 576 can be seamlessly integrated into your system and processes to optimize the performance of your baggage handling system.
 

Impact:

  1. Increase system throughput capacity.

  2. Decrease the number of delayed bags.

  3. Quantify the efficiency of your system and automate the reporting.

  • Automate & accelerate your quality control

  • Digitize quality reports