Combining Context-Awareness and Data Analytics in Support of Drone Technology

Boris Shishkov; Krassimira Ivanova; Alexander Verbraeck; Marten van Sinderen

doi:10.1007/978-3-031-23226-8_4

Combining Context-Awareness and Data Analytics in Support of Drone Technology

Boris Shishkov^*, Krassimira Ivanova, Alexander Verbraeck, Marten van Sinderen

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

3 Citations (Scopus)

206 Downloads (Pure)

Abstract

Drones performing an autonomous mission need to adapt to frequent changes in their environment. In other words, they have to be context-aware. Most current context-aware systems are designed to distinguish between situations that have been pre-defined in terms of anticipated situation types and corresponding desired behavior types. This only partially benefits drone technology because many types of drone missions can be characterized by situations that are hard to predict at design time. We suggest combining context-awareness and data analytics for a better situation coverage. This could be achieved by using performance data (generated at real-time) as training data for supervised machine learning – it would allow relating situations to appropriate behaviors that a drone could follow. The conceptual ideas are presented in this position paper while validation is left for future work.

Original language	English
Title of host publication	Telecommunications and Remote Sensing - 11th International Conference, ICTRS 2022, Proceedings
Editors	Boris Shishkov, Andon Lazarov
Publisher	Springer
Pages	51-60
Number of pages	10
ISBN (Print)	9783031232251
DOIs	https://doi.org/10.1007/978-3-031-23226-8_4
Publication status	Published - 20 Dec 2022
Event	11th International Conference on Telecommunications and Remote Sensing, ICTRS 2022 - Sofia, Bulgaria Duration: 21 Nov 2022 → 22 Nov 2022 Conference number: 11

Publication series

Name	Communications in Computer and Information Science
Volume	1730 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	11th International Conference on Telecommunications and Remote Sensing, ICTRS 2022
Abbreviated title	ICTRS 2022
Country/Territory	Bulgaria
City	Sofia
Period	21/11/22 → 22/11/22

Keywords

Context-awareness
Data analytics
Drone technology
2023 OA procedure

Access to Document

10.1007/978-3-031-23226-8_4

978-3-031-23226-8_4Final published version, 611 KBLicence: Taverne

Cite this

Shishkov, B., Ivanova, K., Verbraeck, A., & van Sinderen, M. (2022). Combining Context-Awareness and Data Analytics in Support of Drone Technology. In B. Shishkov, & A. Lazarov (Eds.), Telecommunications and Remote Sensing - 11th International Conference, ICTRS 2022, Proceedings (pp. 51-60). (Communications in Computer and Information Science; Vol. 1730 CCIS). Springer. https://doi.org/10.1007/978-3-031-23226-8_4

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title = "Combining Context-Awareness and Data Analytics in Support of Drone Technology",

abstract = "Drones performing an autonomous mission need to adapt to frequent changes in their environment. In other words, they have to be context-aware. Most current context-aware systems are designed to distinguish between situations that have been pre-defined in terms of anticipated situation types and corresponding desired behavior types. This only partially benefits drone technology because many types of drone missions can be characterized by situations that are hard to predict at design time. We suggest combining context-awareness and data analytics for a better situation coverage. This could be achieved by using performance data (generated at real-time) as training data for supervised machine learning – it would allow relating situations to appropriate behaviors that a drone could follow. The conceptual ideas are presented in this position paper while validation is left for future work.",

keywords = "Context-awareness, Data analytics, Drone technology, 2023 OA procedure",

author = "Boris Shishkov and Krassimira Ivanova and Alexander Verbraeck and {van Sinderen}, Marten",

note = "Funding Information: Acknowledgement. This work was partially supported by: (i) Contract “NGIC – National Geoin-formation Center for monitoring, assessment and prediction natural and anthropogenic risks and disasters” under the Program “National Roadmap for Scientific Infrastructure 2017–2023”, financed by Bulgarian Ministry of Education and Science; (ii) Faculty of Technology, Policy, and Management – Delft University of Technology; (iii) Faculty of Electrical Engineering, Mathematics and Computer Science – University of Twente. Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 11th International Conference on Telecommunications and Remote Sensing, ICTRS 2022, ICTRS 2022 ; Conference date: 21-11-2022 Through 22-11-2022",

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language = "English",

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Shishkov, B, Ivanova, K, Verbraeck, A & van Sinderen, M 2022, Combining Context-Awareness and Data Analytics in Support of Drone Technology. in B Shishkov & A Lazarov (eds), Telecommunications and Remote Sensing - 11th International Conference, ICTRS 2022, Proceedings. Communications in Computer and Information Science, vol. 1730 CCIS, Springer, pp. 51-60, 11th International Conference on Telecommunications and Remote Sensing, ICTRS 2022, Sofia, Bulgaria, 21/11/22. https://doi.org/10.1007/978-3-031-23226-8_4

Combining Context-Awareness and Data Analytics in Support of Drone Technology. / Shishkov, Boris; Ivanova, Krassimira; Verbraeck, Alexander et al.
Telecommunications and Remote Sensing - 11th International Conference, ICTRS 2022, Proceedings. ed. / Boris Shishkov; Andon Lazarov. Springer, 2022. p. 51-60 (Communications in Computer and Information Science; Vol. 1730 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Ivanova, Krassimira

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N2 - Drones performing an autonomous mission need to adapt to frequent changes in their environment. In other words, they have to be context-aware. Most current context-aware systems are designed to distinguish between situations that have been pre-defined in terms of anticipated situation types and corresponding desired behavior types. This only partially benefits drone technology because many types of drone missions can be characterized by situations that are hard to predict at design time. We suggest combining context-awareness and data analytics for a better situation coverage. This could be achieved by using performance data (generated at real-time) as training data for supervised machine learning – it would allow relating situations to appropriate behaviors that a drone could follow. The conceptual ideas are presented in this position paper while validation is left for future work.

AB - Drones performing an autonomous mission need to adapt to frequent changes in their environment. In other words, they have to be context-aware. Most current context-aware systems are designed to distinguish between situations that have been pre-defined in terms of anticipated situation types and corresponding desired behavior types. This only partially benefits drone technology because many types of drone missions can be characterized by situations that are hard to predict at design time. We suggest combining context-awareness and data analytics for a better situation coverage. This could be achieved by using performance data (generated at real-time) as training data for supervised machine learning – it would allow relating situations to appropriate behaviors that a drone could follow. The conceptual ideas are presented in this position paper while validation is left for future work.

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Shishkov B, Ivanova K, Verbraeck A, van Sinderen M. Combining Context-Awareness and Data Analytics in Support of Drone Technology. In Shishkov B, Lazarov A, editors, Telecommunications and Remote Sensing - 11th International Conference, ICTRS 2022, Proceedings. Springer. 2022. p. 51-60. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-23226-8_4

Combining Context-Awareness and Data Analytics in Support of Drone Technology

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