1. One to Rule them All: A Study on Requirement
Management Tools for the Development of
Modern AI-based Software
A. Ottun, M. Asadi, M. Boerger, N. Tcholtchev, J.F.F Gongalves,
D. Borovĉanin, B. Siniarski, and H. Flores
This research is part of SPATIAL project that has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No.101021808.
IEEE Big Data, Sorrento, Italy, December 15, 2023
3. Modern applications
[IEEE-PC] Z. Yin, M. Olapade, M. Liyanage, F.
Dar, A. Zuniga, N. H. Motlagh, X. Su, S. Tarkoma,
P. Hui, P. Nurmi, H. Flores: Toward City-Scale
Litter Monitoring using Autonomous Ground
Vehicles, IEEE Pervasive Computing Magazine,
[source] Ottun, Abdul-Rasheed., &.. Flores, Huber. (2023). Detection mechanisms to identify data biases and exploratory studies about
different data quality trade-offs. Deliverable 3.1, H2020 EU SPATIAL, 2023
4. System architectures
[source] Ottun, Abdul-Rasheed., &.. Flores, Huber. (2023). Detection mechanisms to identify data biases and exploratory
studies about different data quality trade-offs. Deliverable 3.1, H2020 EU SPATIAL, 2023
5. System architectures
[source] Ottun, Abdul-Rasheed., &.. Flores, Huber. (2023). Detection mechanisms to identify data biases and exploratory
studies about different data quality trade-offs. Deliverable 3.1, H2020 EU SPATIAL, 2023
6. System architectures
[source] Ottun, Abdul-Rasheed., &.. Flores, Huber. (2023). Detection mechanisms to identify data biases and exploratory
studies about different data quality trade-offs. Deliverable 3.1, H2020 EU SPATIAL, 2023
8. Modern applications
[IEEE-PC] Z. Yin, M. Olapade, M. Liyanage, F.
Dar, A. Zuniga, N. H. Motlagh, X. Su, S. Tarkoma,
P. Hui, P. Nurmi, H. Flores: Toward City-Scale
Litter Monitoring using Autonomous Ground
Vehicles, IEEE Pervasive Computing Magazine,
[source] Ottun, Abdul-Rasheed., &.. Flores, Huber. (2023). Detection mechanisms to identify data biases and exploratory studies about
different data quality trade-offs. Deliverable 3.1, H2020 EU SPATIAL, 2023
17. Local and internal regulations of companies/institutions also makes it
difficult to choose a tool
Open source tools lack detailed documentation, increasing their
learning curve
Open source tools could be adopted to comply with regulations,
however, low level instrumentation is required, increasing the cost of
adoption
AI trustworthiness is an on-going process that involves stakeholders,
users, developers and policy makers, RM tools are unable to handle the
definition of AI requirements from specific angles/terminologies
Conclusions
18. ACKNOWLEDGEMENTS
This research is part of SPATIAL project that has received
funding from the European Union’s Horizon 2020 research
and innovation programme under grant agreement
No.101021808.
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20. MOOC courses completely free! Equivalent to 2 ECTS (Content free for anyone, certificate option
also)
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Trustworthy AI Sign up!