Revolutionizing food safety in the airline industry: AI-powered smart solutions

Abstract

Background

Ensuring food safety in the airline industry is a complex challenge due to the global supply chain, long-distance transport, and the need for real-time monitoring. Traditional practices often fail to address inefficiencies, leading to foodborne illnesses, waste, and regulatory breaches. AI offers revolutionary potential by addressing these issues with cutting-edge technologies like IoT sensors, blockchain, and predictive analytics.

Scope and approach

This review explores the integration of AI in enhancing airline food safety. It examines AI-driven solutions across supply chain management, real-time monitoring, and predictive maintenance. Specific applications like automating compliance, mitigating risks in transport, and enhancing transparency through traceability are discussed. The paper highlights the role of AI in reducing food waste by up to 30 % through precise demand forecasting and controlling losses attributed to transport inefficiencies, which globally cause 20 % of food spoilage.

Key findings and conclusions

AI enhances operational efficiency by enabling real-time risk detection, optimizing inventory, and ensuring compliance with international safety standards. For instance, machine learning and IoT sensors significantly improve traceability and reduce spoilage costs, potentially lowering operational expenses by 15–20 %. Despite initial challenges like implementation costs and data security concerns, phased integration and cross-industry collaboration can overcome barriers. This paper concludes that AI-driven solutions are indispensable for ensuring long-term sustainability, reducing food waste, and meeting evolving regulatory and consumer expectations in airline food safety.