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Shenzhen COOS Science & Technology Development Co., Ltd. is an Internet, Internet of Things, blockchain and artificial intelligence integrated cloud platform and technology solutions provider, provide customers with competitive products and solutions through the fusion of cutting-edge technology.

COOS.AI and the Hong Kong Polytechnic University joint R&D “Big Data-Driven Airport Resource Management (BigARM) Engine and Application Tools” project

2019-01-08 21:06:45 By COOS

As the main R&D and technical support provider, COOS.AI will jointly R&D next generation resource scheduling system for Hong Kong airport, with MongoDB, Hong Kong Airport, Hong Kong Logistics and Supply Chain Management Application R&D Center, Hong Kong Innovation and Technology Commission and big data analysis lab (UBDA) of Hong Kong Polytechnic University. This system will bring a significant improvement to airport’s operational efficiency and passenger travel experience.

The project was approved by Innovation and Technology Fund (ITF) of Hong Kong Innovation and Technology Commission and received R&D funding.

The project link of Hong Kong Innovation and Technology Commission:  Click To View

BIGARM is an airport resource management system dominated by big data and artificial intelligence to improve efficiency and intelligence of airport resource management, including the allocation of baggage conveyor belts. The airport handles 500 inbound flights a day, and the average and efficient distribution and use of baggage belts is a big challenge.

The efficiency of baggage belts distribution is affected by a number of factors, including the actual arrival time of flight, the number of incoming baggage, the arrival time of ground baggage handling equipment, the tarmac traffic, the speed at which baggage is unloaded, the length of time the baggage will stay in conveyor belt, etc. The current phase of project will focus on the development of an intelligent application software that, after analyzing the factors mentioned above, makes suggestions to improve baggage belts distribution with the objective of making real-time changes as required.