When airlines and ANSPs come together

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The SafeClouds.eu project team came together for the last Consortium Meeting on November 6th and 7th in Majorca. Big thanks to Air Europa who supported and hosted the meeting.

For two days, five airlines (namely Air Europa, Iberia, Norwegian, Pegasus and Vueling) met with the 3 ANSPs participating in the project (Austrocontrol, ENAIRE and LFV), along with Eurocontrol, AESA and EASA (Spanish and European Safety Authority respectively). The last meeting was to collaboratively discuss their broad experience in safety. The group combination of airspace users, including pilots, ATCOs, FDM safety analysts, and safety authorities representatives provided a very inspiring and clear overview of present-day aviation safety analysis, its challenges and opportunities on the transition from event-driven to data-driven safety intelligence. These meetings provide critical insight for data scientists and are key to support the users-driven approach adopted for the project since its conception. The users have defined relevant safety scenarios where data science and ML techniques can provide an added value over the incident-analysis tools they currently have. The scenarios, Runway performance, unstable approaches, group proximity, and airprox drive the descriptive and predictive analytics for SafeClouds.eu. The consortium meetings are an important to present results from the data analysis and discuss and capture their requirements (both individually and in groups) for future work. As the final users of the data analysis work performed within SafeClouds.eu, it is key to ensure this alignment so their visualization dashboards provides relevant and usable ML tools.

SafeClouds is currently immersed in running the analytics based on three years of FDM data, which is merged with traffic data from Eurocontrol, weather data and surface radar data, among other data sources as required by the use case. This comes after investing the first months of the project to develop the legal and technical framework for securely managing and protecting the data. Considering this, the DataBeacon development, a data infrastructure that through several security layers and applying innovative cryptographic techniques, enables the data protection and merging while preserving its confidentiality. This Aviation ML platform, and the different implemented features and applications, enables data analysts to perform their analysis over various aviation data sources without actually having access to the databases. In all, this provides the necessary level of trust to the users and data owners.

With these developments, SafeClouds.eu is going one step further by providing breakthrough analytics on safety precursors based on ML techniques. This analysis will combine airline FDM data with traffic, ADS-B and METEO data, providing improved information on the scenario that individual airspace users cannot otherwise access. This provides airlines, ANSPs and airports an enhanced understanding on the main causes that influence a safety incident which can support decision making for developing customized mitigation actions. Interested in more details on the techniques and results? A follow-up post will be published soon.

ANSPs, how changes on fuel price affect your airspace revenues?

AUTHOR: Luis Delgado

Vista allows to analyse complex scenarios with interactions between metrics of different stakeholders.

Flight plan generation and route selection

When airlines select their flight plans between a given origin and destination many different factors need to be considered, such as possible routes available, weather, aircraft performance or time required. Vista uses a data-driven approach analysing historical flight plans, routes between airports and aircraft performances to estimate the cost of operating those different routes.

As shown in the above diagram, the historical analysis of data allow us to generate a pool of two dimensional routes, probability distributions for cruise wind, speed and flight level request and length and duration of climb and descent phases. With this information, for each possible route we can estimate the 4D trajectories that the airline will plan and estimate the total operating cost of these possibilities.

A given flight will, of course, follow only one of the possibilities, so at pre-tactical level, the different flight plans options are prioritised considering their expected direct operating costs (as a function of flight time, fuel and en-route airspace charges). This selection is not deterministic as airlines not always will follow the apparent lest cost route and in Vista we are interested on reproducing realistic flight plan selections options, not the best option!

 

What if we change the cost of fuel?

Vista is a great tool to analyse the impact of changes of parameters such as fuel cost on the behaviour of the stakeholders in the system. In some areas of Europe, airlines face the possibility of selecting different routes which might incur on different airspace en-route charges and different fuel consumptions and flying time. This leads to trade-offs that can be captured by Vista. An example of one of those regions is western Europe and flights to-from the UK and the Canary Islands. As shown in this image, airlines can select more direct routes using the airspace of France, Spain and Portugal or operate longer routes which benefit from the low airspace usage cost of the Oceanic airspace.

The trade-offs between different metrics for the airlines can be explicitly computed by Vista as shown in the image below for different fuel price scenarios. With higher fuel cost, shorter routes tend to be selected leading to lower fuel usage but higher airspace en-route charges.

As Vista considers multiple stakeholders it is possible to assess the impact of these changes on the demand and expected revenue obtained by the different ANSPs as shown in the following images:

Expected revenue due to en-route charges variation for GCTS - EGKK flights

Expected revenue due to en-route charges variation for all of ECAC flights

The figure above shows the expected changes on revenues for the different ANSPs across Europe if changes of fuel price are produced. This illustrates how different parameters are interconnected for different stakeholders in subtle manners that can be captured by Vista: changes on fuel prices represent variations on routes preferences which might have an impact on airspace usage and revenues of the ANSPs!

Vista tactical model – Mercury: because passengers matter

Over the next decades, EU mobility is expected to progressively evolve from the gate-to-gate focus currently prevalent in the aviation and ATM industry towards a seamless and efficient door-to-door-orientated vision.  The paradigm shift from gate-to-gate (hence aircraft centered) to door-to-door (passenger-oriented) is present at virtually all strategic research documents and agendas. The paradigm shift is here to stay. From a passenger perspective, which of the following scenarios create more impact?:

  • Scenario A): a 8 minute delay in an aircraft arrival time with no connecting passengers
  • Scenario B): a 5 minute one that prevents a significant number of passengers doing a connection in that airport and subsequently expand their door-to-door trip in more than 10 hours

How can that impact be predicted in terms of time and cost? One of the very first research exercises was the POEM project (SESAR 1- WPE) etc. This project was the original seed of Mercury. Mercury has been afterwards improved, validated and completed in other reseach initiatives for SESAR and European Commission, reaching its current door-to-door status.

What is mercury?

Mercury is a modelling and simulator tool - a framework capable of measuring the performance of the air transport network. It provides a wide range of performance and mobility metrics, capable of describing in detail different air transport scenarios.

Mercury draws on extensive data, drawn from a wide range of industry sources, including airlines, airports and air navigation service providers. Mercury's data models have been demonstrated through over 5 years of research and development, plus industry consultation.

How passenger matter in mercury?

Mercury is the first air transportation network simulator that puts passengers in the centre. Each day of simulation the itineraries of more than 3 million passengers are reproduced. Each passenger has its individual profile, ticket and decisions to make. According to EU regulation 261/2004 passengers are compensated by delay and cancellations. Extended delays, aborted journeys, overnight stays there are all part of the Mercury simulator.

Of course airlines play a major role as well, Mercury incorporates costs models for canonical airline categories. Each of the airline decision of waiting for certain passengers, cancel a flight or even board the passengers and send a ready message even when a ATFCM slot was assigned is taken according to each airline rational cost model.

The secret ingedient: a spice of randomness

There is no way one could develop a simulator like Mercury taking into account every detail in the air transportation system. Some process are just too complex or simply put we do not understand yet. Whilst others are just exogenous factors far beyond the reach of the air transportation system. 

But what if we could use a different approach. In Mercury each day of operations is repeated, introducing small variations representing everyday uncertainty and exogenous factors.

Ultimately, small changes lead to completely different day of operations, delays and cancellations. Just similarly to what happens with some chaotic systems, the sensitivity to the initial conditions allow to explore overall trends and stable status, in some cases called emergence.

Interested in reading further info about Mercury? Click here to visit the website.

Author: Samuel Cristóbal (Innaxis)

FDM Raw Data: Why Binary Data and How to Decode It?

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Authors: Lukas Höhndorf & Javensius Sembiring (TU Munich)

SafeClouds.eu gathers 16 partners for research collaboration with a wide and diverse group of users, including air navigation services providers, airlines and safety agencies. SafeClouds.eu encourages active involvement from users, as the project aims to apply data science techniques to improve aviation safety. SafeClouds.eu is unique as it involves data combination and collaboration from ANSPs, airlines and authorities in order to improve our knowledge on safety risks, all while maintaining the confidentiality of the data. This safety analysis requires comprehensive understanding of various data sources, and supports the use case analysis as selected by the users.
The basics of the FDM data, as one of the main data sources for the project, is outlined in this post.

Onboard Recording

A large amount of data is recorded during civil aircraft flights. Apart from the “Flight Data Recorder” that is mainly used for accident investigations (widely known as “Black Box”), there are also recorders for regular operations. These recorders are often called “Quick Access Recorders” (QAR). QAR data is analysed in terms of safety, efficiency and other aspects in Flight Data Monitoring activities for airlines and is furthermore an integral part of the research project SafeClouds.eu.
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Figure 1: Example for a QAR (Source: https://www.safran-electronics-defense.com/aerospace/commercial-aircraft/information-system/aircraft-condition-monitoring-system-acms)

Aircraft are very complex systems with a large number of sensors constantly recording measurements. Important parameters regarding the aircraft state, including position, altitude, speed, engine characteristics and many others are recorded by the QAR. Depending on the aircraft type and airline, the number of recorded parameters can reach several thousand.

As a digital device, the recording uses binary format. In other words, if we look at the QAR data we would only see a bit stream, i.e. a sequence of 0 and 1. In order to use the data and investigate, for example the aircraft position, two additional components are necessary. First, logic is needed to determine how the data is written into the bit stream. This is given by an ARINC standard and two versions are presently used: ARINC 717 standard is used for older aircraft types and the ARINC 767 is used for newer aircraft types. Second, a detailed description of the location of any considered parameter in the bit stream is needed. This is given by a “dataframe” which is a text document of up to several hundreds of pages.

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Figure 2: Overview (Source: “Flight Data Decoding used for Generating En-Route Information based on Binary Quick Access Recorder Data”, Master thesis, Nils Mohr, Technical University of Munich)

File Formats

One of the advantages of data stored in binary format is storage efficiency. The size of the same flight data file stored in binary format compared to being stored in engineering values (e.g. in a CSV file) might be ten times smaller. Considering the research project SafeClouds.eu or the shared framework for flight data such as ASIAS of the FAA, FDX of IATA or Data4Safety of EASA which collects millions of flight data, an efficient storage is obviously needed.

However, storing flight data in binary format then requires an efficient way to transfer the binary data into engineering values. Considering the bit stream logic, two parts are necessary. First, the bit stream logic (provided by the ARINC standard) needs to be represented in a decoding algorithm. Second, the dataframe information, i.e. which parameter can be found in which part of the bit stream needs to be accessible to the decoding algorithm.

Decoding

Recorded parameters have different characteristics. For example, they can be numeric, alphanumeric or characters. Depending on these characteristics, different decoding rules have to be applied. As an example, a temperature recording of 36.5 °C with a linear conversion rule is considered in the following figure.

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Figure 3: Simple Decoding Example (Source: “Flight Data Decoding used for Generating En-Route Information based on Binary Quick Access Recorder Data”, Master thesis, Nils Mohr, Technical University of Munich)

Starting from the bit stream, just specific binary values are relevant for the temperature recording. As mentioned above, this information can be found in the dataframe. The combination of all bits leads to a number in the binary system, which can then be transferred into the associated decimal value. Applying the conversion rule for linear parameters gives the result 36.5. Information about these rules as well as the unit, in this case degree Celsius, can be found in the dataframe.

Summary

The data that is recorded by civilian aircraft in their daily operation contains valuable information that can be used for airline safety analyses. Due to the nature of the recording, the data is generated in binary format. To make the data accessible and readable for the analysts, a decoding algorithm is applied. For the development of this algorithm, information about the recording logic and for all the considered parameters must be available.

Author: Lukas Höhndorf (TU Munich)

Augmented reality and data visualization (in aviation)

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Present-day technology is so powerful that the perception of reality can be easily and realistically modified with IT tools, providing users withan experience beyond “simple” reality. This is achievable by mixing real-world environment elements supplemented and/or augmented by computer-generated inputs. The current post unpacks this topic, focusing specifically on the data visualization aspects. In brief, augmented reality can take two approaches:

  • First, inventing totally new scenarios, in which the user becomes part of a “parallel universe”. Supplementing the real-world environment with an unreal one; either a virtual place (video game) or a different location (i.e. another real location). This is the case of futuristic 90’s and early 2000’s alike head-mounted displays with users’ eyes looking at full screens recreating other places. The ergonomics aspects are usually modest for most of the applications due to the head-mounted displays weight and size.

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  • The second, and closer to “data visualization” area is the so called “mediated reality”. The real-world environment enhanced by virtual elements displayed in glasses, windscreens etc. In them, additional information/data is provided. The real challenges is to decide what, how and when to display the information, without requiring users to look away from their usual viewpoints, while providing extra value. The integration and user experience is much more natural and enjoyable than the fully immersive systems.
Research project Augmented Reality - contact-analogue Head-Up Display (10/2011)

Research project Augmented Reality – contact-analogue Head-Up Display (10/2011)

In this context, one of the very early examples of head-up displays can be found precisely in aviation, almost 80 years ago. In 1937, the German ReviC12/A fighter aircraft included a basic reflector sight indicating some basic aircraft magnitudes such as speed and turn rate, to reduce the (visual) workload of pilots in case of extreme maneuvering
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Nowadays virtually all modern fighters (F18, F16, Eurofighter) use head-up displays. The most modern versions (F35) do not have head-up displays, and instead include helmet mounted displays, ensuring the proper orientation of the user’s head, for all circumstances.
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One of the trending topics of augmented reality within aviation is its usage in air traffic control (ATC), particularly in Tower environments. Below are two common approaches:

  • Visual information is enhanced to ease identification and tracking of aircraft. This includes tools similar to head-up displays and/or helmets-displays that enhance the information (providing for instance, aircraft ID, scheduled times, etc). This approach could be extremely useful in low visibility conditions by facilitating the tower ATCOs tasks. It also avoids dividing attention between the primary visual field (the window) and the auxiliary tools (surface radar, strips etc).

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  • The extreme version is a complete virtual control tower, the so called “remote tower”. ATC would have remote control rooms with video-sensors on-site, including augmented reality enhancements. The synthetic augmentation of vision increases the situational awareness at the airport, especially during poor visibility conditions, or blocked line-of-sight areas due to airport geometry. It additionally provides benefits in terms of cost saving (no need to build and maintain control tower facilities) and a more efficient use of human resources (potentially serving multiple airports with low traffic events from a centralised location). Research in this field started in FP6 project “ART” and is now being progressed by SESAR WP6. In fact, Örnsköldsvik/Gideå airport is the first on the world deployment of remote tower, in late 2015, by the Swedish LFV. In US, Fort Collins-Loveland Municipal Airport was the first approved and tested airport with a remote tower in 2016.

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For the air passenger and mobility context, augmented reality and the wide range of solutions providing additional real-time information to passengers is taking off as well. (No pun intended.)
These technological innovations include indoor location tracking, real-time information on boarding gates, real-time updates on flight delays, and information on airport facilities and shops. This is also being expanded to knowing the number and location of available parking spaces to facilitate the passenger experience in the (sometimes not so easy) airport processes. For example, Copenhagen airport, in collaboration with SITA, created the very first augmented reality indoor app in 2012. Now there is an endless list of both airlines and airports with similar apps.
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Do you think augmented reality together with innovative data visualization can have a significant impact in future aviation?
What are its challenges and potential benefits?
We’re interested in hearing your thoughts and ideas.

SafeClouds at EASA 2016 annual event and European Commission newsletter

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SafeClouds.eu, the most advanced project to improve aviation safety through data analysis, was presented at the EASA 2016 Annual Safety Conference, held in Bratislava last November.
Carlos Alvarez, President of Innaxis, participated in the panel “Sharing and processing safety data: a vital step forward for safety?”. Carlos laid out the main goals of the project as well as our priorities for the next month, strengthening the importance of an integrated data pipeline, from low level raw data management to embedded analytics, driven by user operational questions. The integrated approach will be capable of developing data science solutions to provide all-new capabilities for safety improvements to aviation stakeholders.
You can watch the video of the session:
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In parallel, SafeClouds.eu was also selected for the INEA/European Commission newsletter. This newsletter highlighted just 6 out of the hundreds projects recently awarded within the EU H2020 programme. As it is pointed in the newsletter “The (SafeClouds) project will develop a novel data mining approach for aviation safety and design innovative representations of the results in order to effectively transfer the gained to such users as airlines and air navigation service providers”

SafeClouds kick off meeting

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SafeClouds.eu, a H2020 big data for safety project, coordinated by Innaxis, kicked off earlier this month.

SafeClouds is the recently launched H2020 aviation-safety project. It is coordinated by Innaxis, with 15 additional entities (including airlines, ANSPs, EASA, Eurocontrol, various research entities, etc) from 8 different countries.
The aim of SafeClouds is to improve aviation safety by developing state-of-art big data and data analysis tools. The consortium will build a coordinated platform to combine and share data among different aviation actors.
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DATASET2050 presentation at Data Science in Aviation Workshop (EASA, Cologne-Germany)

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The annual event exploring Data Science in Aviation (ComplexWorld funded; organized by Innaxis) has recently celebrated its fourth edition this past September 8th 2016. The event was hosted on the EASA premises in Cologne, Germany . This year it highlighted a presentation of the DATASET2050 project, “Data Science for Mobility”, by project coordinator Samuel Cristobal (Innaxis).

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On the Data Science In Aviation event:

Previous editions of the Data Science in Aviation event were hosted in Madrid 2013, Paris 2014 and Brussels 2015. The popular event usually draws attendance from more than 80 individuals from top European and worldwide aviation entities (including Airbus, Eurocontrol, Boeing, EASA, Airlines, Airports, ANSPs, SESAR , Universities, etc) along with ICT and data-related entities (including CERN researchers, Fraunhofer, Infrastructure-related, and various universities). Notable presenters from the 2016 edition included EASA, Innaxis, NATS, Eurocontrol, Boeing, ENAC and Fraunhofer.

In terms of the event agenda and content, the presentations has traditionally outlined how data science is understood as a useful set of fundamental principles that support and guide the principled extraction of information and knowledge from aviation data. Furthermore, the discipline leans on well-known data-mining techniques, and goes far beyond these techniques with successful data-science paradigms which provide specific applications in various air transport areas (safety, performance, mobility etc).

 

On DATASET2050 Samuel’s presentation:

The event also highlighted a key presentation from Innaxis project coordinator, Samuel Cristobal. Samuel presented five different points on data science in aviation.

  • First, he explained how some of the data science tools, techniques and concepts have been used in the mobility context, specifically using the DATASET2050 project as a case example.
  • Second, Samuel explained the different door to door phases under analysis (door-kerb; kerb-gate; gate-gate; kerb-door), which helps to delve deeper in the different data science components within aviation phases.
  • Third, Samuel outlined the different links between project objectives and overall Flightpath2050 goals.
  • The fourth point explored mobility data in Europe, and the value of the DATASET approach in this context.
  • The presentation concluded with a fifth and final point announcing the next communication actions. The full presentation can be accessed here: https://www.dropbox.com/s/91julyl8gsij2k9/DATASET_SC_v1.pdf?dl=0

 

In sum, the fourth edition of the Data Science in Aviation event was an excellent opportunity for dissemination of DATASET2050. This was in conjunction with a fruitful exchange of ideas with other aviation data scientists, some of whom working with similar tools in other sub-areas far from mobility. We hope to continue this momentum of knowledge exchange and look forward to a potential fifth edition of the popular event.

 

You can watch DATASET2050 Samuel’s presentation here, and the rest of the event videos at Innaxis’ Vimeo channel.

Mobility presentation at Data Science In Aviation workshop (EASA, 2016)

The annual event exploring Data Science in Aviation (ComplexWorld funded; organized by Innaxis) has recently celebrated its fourth edition this past September 8th 2016. The event was hosted on the EASA premises in Cologne, Germany . This year it highlighted a presentation of the DATASET2050 project, “Data Science for Mobility”, by project coordinator Samuel Cristobal (Innaxis).

 

 

On the Data Science In Aviation event:

Previous editions of the Data Science in Aviation event were hosted in Madrid 2013, Paris 2014 and Brussels 2015. The popular event usually draws attendance from more than 80 individuals from top European and worldwide aviation entities (including Airbus, Eurocontrol, Boeing, EASA, Airlines, Airports, ANSPs, SESAR , Universities, etc) along with ICT and data-related entities (including CERN researchers, Fraunhofer, Infrastructure-related, and various universities). Notable presenters from the 2016 edition included EASA, Innaxis, NATS, Eurocontrol, Boeing, ENAC and Fraunhofer.

In terms of the event agenda and content, the presentations has traditionally outlined how data science is understood as a useful set of fundamental principles that support and guide the principled extraction of information and knowledge from aviation data. Furthermore, the discipline leans on well-known data-mining techniques, and goes far beyond these techniques with successful data-science paradigms which provide specific applications in various air transport areas (safety, performance, mobility etc).

 

On DATASET2050 Samuel’s presentation:

The event also highlighted a key presentation from Innaxis project coordinator, Samuel Cristobal. Samuel presented five different points on data science in aviation.

  • First, he explained how some of the data science tools, techniques and concepts have been used in the mobility context, specifically using the DATASET2050 project as a case example.
  • Second, Samuel explained the different door to door phases under analysis (door-kerb; kerb-gate; gate-gate; kerb-door), which helps to delve deeper in the different data science components within aviation phases.
  • Third, Samuel outlined the different links between project objectives and overall Flightpath2050 goals.
  • The fourth point explored mobility data in Europe, and the value of the DATASET approach in this context.
  • The presentation concluded with a fifth and final point announcing the next communication actions. The full presentation can be accessed here: https://www.dropbox.com/s/91julyl8gsij2k9/DATASET_SC_v1.pdf?dl=0

 

In sum, the fourth edition of the Data Science in Aviation event was an excellent opportunity for dissemination of DATASET2050. This was in conjunction with a fruitful exchange of ideas with other aviation data scientists, some of whom working with similar tools in other sub-areas far from mobility. We hope to continue this momentum of knowledge exchange and look forward to a potential fifth edition of the popular event.

Innaxis at ICRAT 2016

Between June 20 to 24, our PhD student Seddik Belkoura went at the very doorstep of the famous Rocky Balboa Statue, as the seventh edition of the International Conference on Air Transport (ICRAT) was held at Drexel University (Philadelphia, USA) . This successful event, co-organised by the FAA (Federal Aviation Administration-USA) and EUROCONTROL, put the emphasis the next generation of researchers, with a strong participations of students keen on interacting with more mature and expert minds.

 

In Seddik’s presentation during the conference, he wanted to highlight the dynamic nature of the delay propagation process in Air Transportation. He showed in his talk that abnormal delays at a given airport (those with an unexpected magnitude) can perturb the way the delays are propagated in “normal” conditions. The quantity of “surprise” necessary to disrupt an airport can be quantifiable, and an approximation of the additional delay necessary to disrupt the propagative dynamics of each airport have been proposed by Seddik. The audience’s interest at this point indicated that work have still have to be done to master all the complex behaviours of some processes like delay propagations.

 

The event was a success, and the areas of investigation within Air Transportation were quite wide. One special note have been noticed by Seddik: the growing number of presentation (and attention) to drones. The recentness of the concept and the velocity with which it develops and spreads is such that it deserves a special attention. Legislation are not yet fully explicit and a lot of work to design the “future” if happening right now. It is the moment to use our experience with Aviation to better fashion the drone system. Specifically, the importance of data should be pointed out, to allow a better development and a continuous improvement of this new and growing complex system.

 

Seddik’s paper and the presentation about drones will be soon available on the official website of the conference (http://www.icrat.org/)

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