# Secure and Privacy-Protected Bioinformation Implementation in Air Passenger Transport Based on DLT
## 6 Discussion and Future Work  
In the first scenario, the advantages of using facial recognition for baggage claim over other methods are clear. Passengers do not need to discretely hold onto their boarding passes for verification, and the scenario avoid the use of QR codes and other methods that may be inconvenient for the elderly, the young, and the disabled. For these vulnerable  
Figure 5: Passenger information sharing sequence diagram. Figure 6: Passenger information sharing CorDapp. groups, the method can be matched with current airline regulations, i.e., the baggage belonging to the actual owner (e.g., a child) can be identified through facial recognition, allowing an assistant (e.g., a parent) to drop off or collect the baggage. Facial recognition is also the easiest to apply and implement instead of other biometric methods. Passengers are also more willing to accept this method than information such as fingerprint or iris. In the second scenario, the facial recognition information has complemented the previous gap in real-time bioinformation. Sending facial recognition information in advance to the border inspection system has a number of practical benefits, with significant advantages for strengthening international border security, increasing inspection efficiency, and improving the passenger experience. Firstly, sending facial recognition information in advance allows for more accurate and efficient identity verification. By capturing travelers' face data in advance, the border inspection system is able to start processing identification before the aircraft lands, thereby reducing the waiting time for travelers at the border checkpoint. This not only improves the efficiency of the entire border clearance process but also reduces the burden on human resources. Secondly, this advance dispatch helps enhance border security. When the aircraft is about to arrive, the system already has the face data of the passengers and can perform identity matching and background checks before the arrival of the passengers. This advanced identity verification measure helps detect potential risks and anomalies in a timely manner and improves the security of international borders. In addition, sending facial recognition information in advance can help improve the traveler experience. By reducing clearance time, travelers are able to complete the border inspection process more quickly and easily, thereby improving the overall travel experience. This is a positive for business travelers, tourists and airlines, helping to promote international tourism and commerce. Taken together, sending facial recognition information in advance to the border inspection system not only improves security and efficiency, but also improves the passenger experience, and is an important step in the overall optimization of international border management. Further, the scenario proposed in this study is also significant in other scenarios. For example, real-time facial information is a secure enough way to verify identity during security checks or boarding checks. Passengers do not need to check their documents again. It brings convenience to travelers. Two scenarios demonstrate different ways of using facial information. In the first scenario, the facial information is assigned and stored in the passenger baggage information data packet. When the passenger collects luggage, the real-time facial features are compared with the previously stored facial features. The goal is to check whether the information matches consistently between the two times. In the second scenario, the passenger's facial information is sent to the border control agency's database to be matched against the blacklist, a process that involves more searching and matching in the database than in the previous scenario. This involves a different format for storing facial information. There are various data formats for storing facial feature information. This research uses the form of hash values, in addition to which it can also be stored in the form of feature vectors [36; 37].