26
A. Chatzimichail et al.
by transforming raw sensor data into high-level knowledge that is understandable by
humans and machines. Interoperability is one of the most important challenges in an
IoT environment, where different devices, services and entities try to connect each
other. Semantic modelling produces a definite scheme of the data meaning in a structured way by combining application knowledge and context-relevant information
with sensor data. The ontology—based development, which is a domain of semantic
modelling, of IoT frameworks can lead to universal IoT solutions multiplying the
benefits of IoT.
In this book chapter, we provided an overview of the current trends in application of semantic technologies in the IoT domain. We provided research studies on
reasoning, aggregation, fusion and interpretation solutions that aim to intelligently
process and ingest sensor information, infusing also human awareness for advanced
situational awareness. Finally, issues around Web of Things and how it augments the
IoT are discussed.
References
1. Swetina, J., Lu, G., Jacobs, P., Ennesser, F., Song, J.: Toward a standardized common M2M
service layer platform: introduction to oneM2M. IEEE Wirel. Commun. 21(3), 20–26 (2014)
2. Noura, M., Atiquzzaman, M., Gaedke, M.: Interoperability in internet of things: taxonomies
and open challenges. Mobile Netw. Appl. 24(3), 796–809 (2019)
3. Alaa, M., Zaidan, A.A., Zaidan, B.B., Talal, M., Kiah, M.L.M.: A review of smart home
applications based on Internet of Things. J. Netw. Comput. Appl. 97, 48–65 (2017)
4. Ramparany, F., Cao, Q.: A semantic approach to IoT data aggregation and interpretation
applied to home automation. In: 2016 International Conference on Internet of Things and
Applications (IOTA), pp. 23–28. IEEE (2016)
5. Huang, X., Yi, J., Zhu, X., Chen, S.: A semantic approach with decision support for safety
service in smart home management. Sensors 16(8), 1224 (2016)
6. Zolfaghari, S., Zall, R., Keyvanpour, M. R.: SOnAr: smart ontology activity recognition
framework to fulfill semantic web in smart homes. In: 2016 Second International Conference
on Web Research (ICWR), pp. 139–144. IEEE (2016)
7. Eine, B., Jurisch, M., Quint, W.: Ontology-based big data management. Systems 5(3), 45
(2017)
8. SeeClickFix | 311 Request and Work Management Software. https://en.seeclickfix.com/.
Cited 25 2019
9. FixMyStreet. https://www.fixmystreet.com/. Cited 25 2019
10. Tsampoulatidis, I., Ververidis, D., Tsarchopoulos, P., Nikolopoulos, S., Kompatsiaris, I.,
Komninos, N.: ImproveMyCity: an open source platform for direct citizen-government communication. In Proceedings of the 21st ACM International Conference on Multimedia, p.
839–842. ACM (2013)
11. Qamar, T., Bawany, N. Z., Javed, S., Amber, S.: Smart city services ontology (SCSO): semantic
modeling of smart city applications. In: 2019 Seventh International Conference on Digital
Information Processing and Communications (ICDIPC), pp. 52–56. IEEE (2019)
12. Van de Vyvere, B., Colpaert, P., Mannens, E., Verborgh, R.: Open traffic lights: a STRATEGY
for publishing and preserving traffic lights data. In: Companion Proceedings of the 2019 World
Wide Web Conference, pp. 966–971. ACM (2019)
13. Open traffic lights ontology. https://w3id.org/opentrafficlights. Cited 25 2019
14. Wachttijd tot groenlicht https://codepen.io/brechtvdv/full/BMQPNX Cited 25 2019
A. Chatzimichail et al.
by transforming raw sensor data into high-level knowledge that is understandable by
humans and machines. Interoperability is one of the most important challenges in an
IoT environment, where different devices, services and entities try to connect each
other. Semantic modelling produces a definite scheme of the data meaning in a structured way by combining application knowledge and context-relevant information
with sensor data. The ontology—based development, which is a domain of semantic
modelling, of IoT frameworks can lead to universal IoT solutions multiplying the
benefits of IoT.
In this book chapter, we provided an overview of the current trends in application of semantic technologies in the IoT domain. We provided research studies on
reasoning, aggregation, fusion and interpretation solutions that aim to intelligently
process and ingest sensor information, infusing also human awareness for advanced
situational awareness. Finally, issues around Web of Things and how it augments the
IoT are discussed.
References
1. Swetina, J., Lu, G., Jacobs, P., Ennesser, F., Song, J.: Toward a standardized common M2M
service layer platform: introduction to oneM2M. IEEE Wirel. Commun. 21(3), 20–26 (2014)
2. Noura, M., Atiquzzaman, M., Gaedke, M.: Interoperability in internet of things: taxonomies
and open challenges. Mobile Netw. Appl. 24(3), 796–809 (2019)
3. Alaa, M., Zaidan, A.A., Zaidan, B.B., Talal, M., Kiah, M.L.M.: A review of smart home
applications based on Internet of Things. J. Netw. Comput. Appl. 97, 48–65 (2017)
4. Ramparany, F., Cao, Q.: A semantic approach to IoT data aggregation and interpretation
applied to home automation. In: 2016 International Conference on Internet of Things and
Applications (IOTA), pp. 23–28. IEEE (2016)
5. Huang, X., Yi, J., Zhu, X., Chen, S.: A semantic approach with decision support for safety
service in smart home management. Sensors 16(8), 1224 (2016)
6. Zolfaghari, S., Zall, R., Keyvanpour, M. R.: SOnAr: smart ontology activity recognition
framework to fulfill semantic web in smart homes. In: 2016 Second International Conference
on Web Research (ICWR), pp. 139–144. IEEE (2016)
7. Eine, B., Jurisch, M., Quint, W.: Ontology-based big data management. Systems 5(3), 45
(2017)
8. SeeClickFix | 311 Request and Work Management Software. https://en.seeclickfix.com/.
Cited 25 2019
9. FixMyStreet. https://www.fixmystreet.com/. Cited 25 2019
10. Tsampoulatidis, I., Ververidis, D., Tsarchopoulos, P., Nikolopoulos, S., Kompatsiaris, I.,
Komninos, N.: ImproveMyCity: an open source platform for direct citizen-government communication. In Proceedings of the 21st ACM International Conference on Multimedia, p.
839–842. ACM (2013)
11. Qamar, T., Bawany, N. Z., Javed, S., Amber, S.: Smart city services ontology (SCSO): semantic
modeling of smart city applications. In: 2019 Seventh International Conference on Digital
Information Processing and Communications (ICDIPC), pp. 52–56. IEEE (2019)
12. Van de Vyvere, B., Colpaert, P., Mannens, E., Verborgh, R.: Open traffic lights: a STRATEGY
for publishing and preserving traffic lights data. In: Companion Proceedings of the 2019 World
Wide Web Conference, pp. 966–971. ACM (2019)
13. Open traffic lights ontology. https://w3id.org/opentrafficlights. Cited 25 2019
14. Wachttijd tot groenlicht https://codepen.io/brechtvdv/full/BMQPNX Cited 25 2019