# Artificial Intelligence of Things as New Paradigm in Aviation Health Monitoring Systems
## 3 Results
### Advanced AIoT Integration in Aviation on the Base of WDAR and FMDE Synergy  
The aircraft communication architecture depicted in Figure 5 represents a significant advancement in the application of AIoT to aviation health monitoring systems. This enhanced architecture, which incorporates both the WDAR and the FMDE unit, exemplifies the potential for comprehensive data collection, transmission, and analyses in modern aviation. At the core of this architecture are two complementary systems:  
1. The WDAR, an optional system used to transmit flight data for analysis;
2. The FMDE, another optional unit that combines full aircraft interface device (AID) capabilities into a single hardware, software, and connectivity solution [63]. The integration of these two systems creates a powerful AIoT framework that significantly enhances the depth and breadth of aircraft health monitoring capabilities. One of the most striking features of this enhanced architecture is the massive increase in data collection capacity. Based on proprietary aircraft manufacturer documentation, the WDAR typically collects approximately 400 parameters, while the addition of the FMDE can expand this to more than 20,000 parameters in advanced aircraft models [62]. This fifty-fold increase in data points represents a quantum leap in the potential for detailed aircraft health monitoring and predictive maintenance. The sheer volume of data collected embodies the \"Internet of Things\" aspect of AIoT, with thousands of sensors and systems continuously reporting their status. The communication infrastructure supporting this expanded data collection is equally advanced:  
1. 4G channel [64]. The FMDE utilizes a 4G connection for data transmission when the aircraft is on the ground. This faster connection, compared to the 2G/3G used by the WDAR, allows for more efficient transfer of the vastly increased data volume. However, it is worth noting that this still depends on airport location and infrastructure, highlighting the importance of ground-based network improvements in realizing the full potential of AIoT in aviation. 2. 2G/3G channel. The WDAR continues to use this channel as a backup or in locations where 4G is not available, ensuring data transmission even in less technologically advanced airports. 3. VHF and HF radio channels. These continue to provide voice and data communication capabilities, essential for air traffic control and long-range communication. This multi-layered communication approach ensures robust and flexible data transmission, a crucial aspect of any IoT system. The collected data are transmitted to two distinct analytical systems:  
* The airline analytical system, as an internal system, likely handles immediate operational needs and airline-specific analyses. * The external analytical IT system as additional system suggests the potential for more advanced or specialized analyses, possibly leveraging cloud computing or shared industry resources. The effectiveness of this external system depends on the arrangement of data transfer, indicating the need for secure and efficient data sharing protocols. The inclusion of an external analytical system points to the potential for industry-wide collaboration and the application of more sophisticated AI algorithms that may be beyond the capabilities of individual airlines to develop or maintain. Figure 5: Advanced AIoT integration in aviation. This enhanced architecture offers several key advantages in the context of AIoT:  
* With over 20,000 parameters being monitored [62], the potential for detecting subtle precursors to equipment failure or performance issues is greatly increased. * The vast amount of data collected allows for more sophisticated AI models, potentially leading to more accurate and earlier predictions of maintenance needs or potential failures. * By combining flight data (WDAR) with maintenance-specific information (FMDE), a more complete picture of aircraft health can be formed.