Data is like altitude—the more we get, the better we can see what’s below.
That’s the fundamental reasoning behind ASIAS, formally known as Aviation Safety Information Analysis and Sharing. In the rotorcraft community specifically, we call it R-ASIAS. It’s a complicated acronym, but it’s purpose simple: By gathering data from as many operators and sources as possible; we can see common threads and threats and then develop interventions to reduce risk.
R-ASIAS currently has 17 large and small operators signed up and contributing data voluntarily. We can always use more. And it’s not just for big operators—there’s immense value in everyone participating, from a single-pilot pleasure flyers to massive oil and gas operators.
When participating in R-ASIAS, an operator can see their own data in great detail, including dashboards and graphical depictions of exceedances and other parameters of interest, but can also see how they compare to other contributors, whose data is deidentified. Data protection is one of the top priorities for all of ASIAS and is governed by agreements that must be put in place before an operator starts contributing.
Using the broad collection of deidentified data in R-ASIAS, the USHST, through its various working groups, is able to take a broad look at issues that affect the entire community. These studies are typically driven by the rotorcraft fatal accident pareto, which is dominated by loss of control (LOC) first and unintended flight into meteorological conditions (UIMC) second. Prevention often comes in the form of communications to this community. One example is the USHST’s “56 Seconds to Live” video series.
A great example of the power of aggregated deidentified data is the ongoing USHST study on unintended flight into instrument meteorological conditions (UIMC). Safety analysis teams working under the auspices of the USHST have spent several years deep into deidentified R-ASIAS data to gain a greater understanding of the issue and come up with interventions.
In R-ASIAS we have the capability to overlay flight tracking data, terrain and weather data, and other information to try to better understand where and how often—and for how long—rotorcraft under visual flight rules (VFR) may be entering instrument meteorological conditions (IMC). While it is impossible to determine if the pilots involved had actually lost sight of the ground, the data as a whole is an indicator of how often this may be occurring.
As an example, the UIMC algorithm developed by the R-ASIAS team detected a UIMC event on January 26, 2020, that showed a good correlation with the conditions as defined in the NTSB in the Kobe Bryant accident report (see Figure 1).
One of the benefits of having the data and processing algorithms is that analysts can build dashboards to check the status of certain hazardous events, like UIMC, from the data we receive from operators combined with other publicly available sources gathered by ASIAS.
The aggregate data can be shown on a dashboard for near real-time updates on certain issues, like UIMC. The dashboard below shows that for 18,494 rotorcraft flight tracks pulled from R-ASIAS, there may have been an average to two instances during each flight where the aircraft entered IMC. Other details include which helicopter models were noted most often, and the geographical “hot spots” where the most events are occurring.
If you would like to learn more about the benefits of contributing your data, please contact us, John Walberg (john.walberg@faa.gov) or Ed Stockhausen (estockhausen@metroaviation.com). We hope to hear from you soon.
Happy Flying.