This research proposes the development of a next generation airline reservation system that incorporates the Cloud microservices, distributed artificial intelligence modules and the blockchain technology to improve on the efficiency, safety and customer satisfaction. The traditional reservation systems encounter issues related to the expansion of the systems, the integrity of the data provided and the level of service offered to the customers, which is the main focus of this architecture through the modular and data centric design approaches. This will allow different operations such as reservations, payments, and customer data management among others to be performed separately thereby facilitating high availability of the system by 30% and enhancing performance of the system by 40% on its scalability. Such systems contain AI driven modules that utilize the past booking patterns along with the profile of the customer to estimate the demand and make recommendations, which increases to 25 % of customer engagement. Moreover, blockchain is effective in engaging an incorruptible ledger system for the all transactions therefore mitigating fraud incidences and increasing the clarity by 20%. The system was subjected to analysis using a simulator and using machine learning evaluations that rated it against other conventional systems. The results show that there were clear enhancements in the speed of transactions where the rates of secure data processing rose by 35%, and the system response time by 15 %. The system can also be used for other high transaction industries like logistics and hospitality. This structural design is indicative of how the use of advanced technologies will revolutionize the airline reservation sector. The implications are growing effectiveness, improvement in security and greater customer contentment.
Abstract One of the main objectives of the European Commission (EC) since the 70s has been to coordinate research policies and to enhance the transnational cooperation in order to reach efficiency in terms of funding and to match with Europe’s economic ambitions. It has been addressed through a centralized approach managed by the EC and a decentralized approach through the cooperation of member states. Regarding the aviation sector, the centralized financing has been successfully implemented under the EU Research & Innovation Framework Programmes, while the decentralized approach has been less successful through the initiative Air Transport Net (AirTN) ERA-NET. The intention of this paper is to analyse the AirTN case study and its methodology to launch transnational calls, the results, and the reasons why it was not completely successful. Following the identification of these main barriers, we provide a list of suggestions that could have been implemented for a more successful outcome.
Blockchain is the foundational technology of various cryptocurrencies. It has features such as nontempering, decentralization, security, anonymity, etc. Its distributed ledger technology has received broad research and industry attention. Cryptography, hash functions, peer-to-peer (P2P) consensus and smart contracts are being used in a wide variety of applications across industries to solve various problems. Supply chain finance is a model in which various financial institutions connect with stakeholders in the supply chain to optimize working capital and liquidity invested in supply chain processes and transactions. The Air Cargo industry is one of the essential parts of various global supply chains. Consisting of multiple nodes, the complexity in its structure makes it difficult for credit risk analysis for the creditors. Information asymmetry leads to a lack of trust between companies and creditors. Frauds and disruptions in the Air Cargo industry make it vulnerable from the perspective of Financial Institutions. A platform for Air Cargo Financing using Blockchain (ACFB) is proposed in this study to solve these problems; this would make a supply chain more transparent, trustworthy, and efficient for all the stakeholders and financial institutions.
We propose and implement a decentralized, intelligent air traffic flow management (ATFM) solution to improve the efficiency of air transportation in the ASEAN region as a whole. Our system, named BlockAgent, leverages the inherent synergy between multi-agent reinforcement learning (RL) for air traffic flow optimization; and the rising blockchain technology for a secure, transparent and decentralized coordination platform. As a result, BlockAgent does not require a centralized authority for effective ATFM operations. We have implemented several novel distributed coordination approaches for RL in BlockAgent. Empirical experiments with real air traffic data concerning regional airports have demonstrated the feasibility and effectiveness of our approach. To the best of our knowledge, this is the first work that considers blockchain-based, distributed RL for ATFM.