Conclusion - Group 4 - 2018/2019, Semester B, Quartile 3
- Page navigation
- Notes from meeting
- Initial ideas
- Project setup
- General problem description
- State of the Art
- Specific problem description
- Present situation
- Drone analysis
- Solution analysis
- Airport analysis
- Decision Model investigation
- Decision Model implementation
- Decision Model validation
- Categorising solutions
- Web Application
In the conclusion, we want to look back at important aspects of the project and discuss our most exciting findings and results. Where we look at both the literature research we did on unwanted UAV presence at and around airports, as well as the decision model we have created. We try to give a short summary and report on all the things learned while working on this project.
Looking back at the problem where last few years multiple airports were forced to cancel hundreds or thousands of flights affecting many travellers due to sightings of UAVs at airports. Not only does this negatively affect the passengers but this also costs the airports itself enormous amounts of money. However, from our literature research and interviews with multiple (Dutch) airports, we have learned that many airports have nothing in place to quickly deal with these UAV sightings, let alone have something in place against potential attacks with (weaponised) UAVs. Since we see the increase in the number of consumer UAVs growing each year, this problem seems to become more and more critical. Furthermore, from the interviews, we know that many of these airports without any defences would like to invest in a solution against unwanted UAV presence.
There are many different potential types of solutions against UAVs at airports that can detect, identify/classify, track or neutralise unwanted UAVs. There already even exist multiple concrete systems created by many different companies using a variety of technologies that could be invested in and deployed at these airports. However, the problem is that there are multiple differences between each of the solutions, and finding the best solutions for your airport is extremely difficult. This is where our research and decision model comes into play. We have thoroughly researched many of these solutions and systems as well as many different airports and types of airports in the Netherlands. After researching the differences between all of these systems, the differences between all of the airports and the wants of the stakeholders of the airports, we have come up with a list of attributes of the solutions which are to be to create a decision model.
We have brainstormed and researched many different types of decision models, and found a voting advice application (VAA) such as the Dutch Stemwijzer, to most closely represent the model we would like to create. Where, instead of advising on political parties by using statements based on issues, we give advice on the best anti-UAV system for your airport based on propositions based on attributes of anti-UAV systems and the airport itself. For setting up these propositions, we used the attributes found in the literature research, to create an enormous table of solutions against the attributes. Then, we formed the propositions for the decision model based on the differences between the attributes of the solutions. In the decision model, we wanted to give the users of the model (airports) some freedom to indicate on attributes that they might find more interesting, or indicate attributes that the solution must necessarily have. Hence we also give the users both of these options. Furthermore, we give the users the option to decide on whether to be advice on detection only solutions, neutralisation only solutions or both. We feel like, with all of these features combined with the exhaustive research and validation of the model, the decision model is a useful anti-UAV decision tool for airports.
To make the decision model more tangible, more accessible to test, we decided to create a web-based application to implement the decision model. This decision model web-app asks the user all of the propositions, where more important attributes and must-haves can be indicated and calculates a score for each of the solutions based on the answers of the user. These scores then indicate which solution fits best with the airport and for the convenience of the user also the percentage of how well a solution matches with the airport is indicated. Lastly, the user can also find descriptions of the advanced solutions on the web-app. For the next couple of weeks, this web-app will be hosted online on the website: https://drones.jortdebokx.nl/.
The project has been wrapped in a presentation, which can be viewed here.
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