Abstract
Based on the constant need for safety and operational cost optimization, the air-cargo industry is continually evolving in the context of Industry 4.0. Used wisely, data can help the industry to provide critical resilience that will allow authorities to take proper measures/actions in response to unexpected disasters and secure societal protection. The “INTELLICONT” project combines state-of-the-art technologies blended with novel solutions to improve the loading/unloading time, the structural status awareness, and the safety and security of the air-cargo related operations (prior to, during, and after the flight), as well as to enhance their capabilities related to the execution of their duties. The suggested system is contextually aligned and harmonized with the existing international and EU regulations. In the present work, the remote monitoring and control system for intelligent aircraft cargo containers have been presented from the software perspective. The intelligent containers integrate three types of sensors, Structural Health Monitoring, fire suppression, and locking status indication. The focus has been given to the design and development of a Human Machine Interface (HMI) capable to visualize all related data for better and safer control of the aircraft cargo. It is shown that the system can contribute to making the air transportations safer, environmentally friendlier, faster and with the lowest possible cost.
Highlights
While different definitions have been introduced by many authors from the concept of the smart city, its description by [1] as a large conglomeration of citizens, businesses, institutions, and agencies working towards a continually improving quality of life, is one of the most illustrative
In our previous work we focused on the description of a novel intelligent Remote Monitoring System that is capable of receiving a feed from sensors in real-time and performing a preliminary analysis of sensor data and data from other sources
Being the upper layer of the onboard architecture at this level, two tasks will be performed: (a) the execution of ML and AI algorithms for early warning reasoning, (b) Real-Time Visualization via Augmented Reality alerting of all outcomes; Through Human Machine Interface (HMI), data from the collector network on each of the Unit Load Devices (ULDs) are delivered to the robotic platforms
Summary
While different definitions have been introduced by many authors from the concept of the smart city, its description by [1] as a large conglomeration of citizens, businesses, institutions, and agencies working towards a continually improving quality of life, is one of the most illustrative. Smart Cities 2021, 4 practically the only removable aircraft part that is handled by other than the operating crew members, ULDs have a strong impact on in-flight safety. In our previous work (under evaluation) we focused on the description of a novel intelligent Remote Monitoring System that is capable of receiving a feed from sensors in real-time and performing a preliminary analysis of sensor data and data from other sources (e.g., battery status). Preliminary analysis of sensorthe data and data from other sources (e.g., which enables adaptive smart working for air cargo operations crews, battery status). Whichand enables smart working environment air cargo are (a) the crews, novel visualization tool, (b) data fusion (c) the standardized operations considering restrictions and needsarchitecture, of the harshand environment.
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