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The need for such a mechanism for IoT has been recognized. It will be some
time before universal protocols are developed to provide a universal
semantic-based discovery mechanism.
Second, given that the number of IoT devices is estimated to exceed one
billion, how do we determine which sources are applicable to our goal with-
out having to inspect over one billion devices? What will be required is a
service similar to Google’s web crawlers that crawl IoT spaces and build a
database of semantic IoT descriptors that can be quickly searched to establish
a set of candidate devices. In fact there is a recently launched effort called
IoTCrawler that provides a Google-like search engine for the IoT
(Skarmeta et al., 2018). While it will take time for services such as IoTCraw-
ler to mature, it is a promising development towards a generalized semantic
capability for IoT devices.
ACKNOWLEDGMENTS
We thank Bill Lawless and Antonio Gilliam for their assistance.
REFERENCES
Bernon, C., Camps, V., Gleizes, M., et al. (2004). Tools for self-organizing applications engi-
neering. In G. D. M. Serugendo (Ed.), Ser. lecture notes in artificial intelligence,Vol. 2977
(pp. 283–298). Springer.
Bernon, C., Chevrier, V., Hilaire, V., et al. (2006). Applications of self-organising multi-
agent systems: an initial framework for comparison. Informatica, 30,73–82.
Blum, B. (2011). Waze steers you clear of traffic. Israel 21c. Dec. 19, 2011.
Colledanchise, M., & € Ogren, P. (2018). Behavior trees in robotics and AI: An introduction. Boca
Raton, FL: CRC Press.
Columbus, L. (2017). 2017 roundup of internet of things forecasts. https://www.forbes.com/sites/
louiscolumbus/2017/12/10/2017-roundup-of-internet-of-things-forecasts/#2fcc243f1480.
Fouad, H., Gilliam, A., Guleyupoglu, S., & Russell, S. M. (2017). Automated evaluation of
service oriented architecture systems: a case study. In Next-generation analyst V, SPIE
defense + security. Anaheim, CA, 9–13 April.
Frogger. (1981). Frogger, the adventures of a fearless frog. The Arcade Flyer Archive, 1981.
Gardelli, L., Viroli, M., Casadei, M., et al. (2006). Designing self-organising MAS environ-
ments: the collective sort case. In D. Weyns, H. V. D. Parunak, & F. Michel (Eds.), Ser.
lecture notes in artificial intelligence: Environments for multi-agent systems III, Vol. 4389
(pp. 254–271). Springer.
Georgeff, M., Pell, B., Pollack, M., Tambe, M., & Wooldridge, M. (1999). The belief-
desire-intention model of agency. In Proceedings of the 5th international workshop on intel-
ligent agents V: agent theories, architectures, and languages (ATAL-98 (pp. 1–10).
Gerber, C., Siekmann, J. H., & Vierke, G. (1999). Flexible autonomy in holonic agent systems.
AAAI Technical Report SS-99-06.
Gleizes, M., Camps, V., George, J., et al. (2007). Engineering systems which generate emer-
gent functionalities. In Proceedings of international workshop on engineering environment-
mediated multi-agent systems (EEMMAS 2007) (pp. 58–75).