Democratizing business intelligence and machine learning for air traffic management safety

Application of smart visualisation in the analysis of Hungarian Agriculture ICT

“…Key-influencer visualisation, decomposition tree, and anomaly detection are the three different types of AI visualisation in Power BI. In this research, we will use decomposition trees (Ehrenmueller, 2020, Patriarca et al, 2022.…”

“…Implementing machine learning techniques often requires a thorough understanding of mathematics and computer science; however, due to the high level of expertise required, ML is difficult to use. A self-service framework ML can therefore be used by analysts with less technical knowledge (Patriarca et al, 2022). Numerous research papers have addressed the self-service deployment of machine learning for business intelligence using Microsoft Power BI (Patriarca et al, 2022;Aspin, 2021Aspin, , 2022.…”

“…A self-service framework ML can therefore be used by analysts with less technical knowledge (Patriarca et al, 2022). Numerous research papers have addressed the self-service deployment of machine learning for business intelligence using Microsoft Power BI (Patriarca et al, 2022;Aspin, 2021Aspin, , 2022.…”

Aviation Accident and Incident Forecasting Combining Occurrence Investigation and Meteorological Data Using Machine Learning

“…A review of the literature indicates that a significant volume of historical data is commonly used to predict future recurrences. However, in the case presented by Patriarca et al (2022), the authors recommend the internal adoption of business intelligence and machine learning solutions by air navigation service providers (ANSPs), and using available data in a self-service safety intelligence approach, which the authors consider as democratizing safety intelligence in aviation. According to the authors, ANSPs must continually develop business intelligence and machine learning applications from traditional databases, which can be improved from the identified solutions.…”

“…Several examples of AI applications in aviation can be identified from recent literature in which machine learning techniques have been used to develop algorithms for forecasting and preventing aeronautical accidents (Patriarca et al, 2022); detecting normality or anomalies in operations from flight data Stogsdill et al, 2021;Xu et al, 2020); providing support for airport pavement maintenance (Barua & Zou, 2021); forecasting take-off times (Dalmau et al, 2021); predicting the true air and ground speeds during aircraft touchdown ; and defining airport capacity (Choi & Kim, 2021), airport congestion, and arrival delays (Rodríguez-Sanz et al, 2019). However, it is noted that such studies predict occurrences based on target variables that may influence operational flight safety and do not consider real data from accidents or incidents, such as meteorological conditions that can affect such accidents or incidents.…”