1
United Airlines In-Flight Wi-Fi Health Management:
Revolutionizing Aircraft Connectivity through Real-time Prognostics
and Big Data Analysis
Ehsan Rahimi
1
, Shuang Ling
2
, Luis Mesen
3
1,2,3
Technical Operations Data Analytics (TODA), United Airlines, Chicago, Illinois, 60606, United States of America
ehsan.rahimi@united.com
shuang.ling@united.com
luis.mesen@united.com
ABSTRACT
This paper highlights an innovative initiative, focusing on
Prognostics and Health Management (PHM) to enhance in-
flight Wi-Fi performance by proactively identifying aircraft
component failures. We propose a novel metric, the
Normalized Wi-Fi Health Score (NWiHS), alongside a
corresponding alerting mechanism, which together represents
a significant advancement in the evaluation and improvement
of in-flight Wi-Fi connectivity. To achieve this goal, we
utilized big data consisting of millions of historical Wi-Fi
heartbeats (HBs) received from each aircraft over the past
three years. These HBs refer to periodic data packet
transmissions sent from United’s aircraft to ground stations,
providing crucial real-time insights into the Wi-Fi system’s
status. Leveraging that data, we utilized advanced statistical
methods to estimate a NWiHS - a robust indicator of aircraft-
level connectivity performance, which quantifies the percent
of missing Wi-Fi HBs normalized to exclude the effect of Wi-
Fi provider performance and global coverage.
1. INTRODUCTION
Monitoring internet connectivity in ground-based systems,
like home internet, is quite distinct from doing so in in-flight
systems due to various environmental and technological
factors. As highlighted by Rula et al. (2018), ground-based
systems typically benefit from stable, wired, or wireless
networks with limited mobility, leading to lower latency and
greater reliability. On the other hand, in-flight connectivity
must function at high altitudes and speeds, often relying on
satellite connections or air-to-ground communication. These
conditions cause increased latency and lower bandwidth
compared to ground networks.
In the rapidly evolving field of commercial aviation,
maintaining reliable in-flight Wi-Fi connectivity poses
unique challenges. These include the dynamic nature of
aircraft environments, the complexity of onboard systems,
and the need for uninterrupted service amidst variable
coverage areas. Our research addresses these challenges by
applying PHM strategies specifically to In-Flight
Connectivity (IFC) systems, utilizing advanced analytics to
predict and prevent Wi-Fi system failures. In modern
aviation, the integration of onboard Wi-Fi in aircraft stands
as a groundbreaking leap, transforming the inflight passenger
experience while fostering seamless data communication. As
it is defined by Zio (2022), PHM is a data-driven approach
that integrates physical insights, information, and operational
data of structures, systems, and components to facilitate the
identification of abnormalities, diagnose faults, and assess
the degradation of equipment and processes. A research study
conducted by Kordestani et al. (2023) highlights the
importance of PHM in managing the complexities and
interconnected subsystems of aircraft. This study emphasizes
the need for advanced prognostic strategies to maintain
aircraft safety and reliability.
In the context of IFC systems, the application of PHM
strategies is pivotal. These systems are critical for enabling
onboard internet access, real-time communication, and
entertainment services. Therefore, it would be required to
have robust monitoring and maintenance to ensure
uninterrupted service. While specific research directly
linking PHM and IFC systems in commercial aviation is
scarce, the key principles of PHM applied in aviation can be
extrapolated to manage the health and performance of IFC
