TY - GEN
T1 - Overcoming the heterogeneity in the internet of things for smart cities
AU - Kazmi, Aqeel
AU - Jan, Zeeshan
AU - Zappa, Achille
AU - Serrano, Martin
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - In the past few years, the viability of the Internet of Things (IoT) technology has been demonstrated, leading to increased possibilities for novel human-centric services in the smart cities. This development has resulted in numerous approaches being proposed for harnessing IoT for smart city applications. Having received a significant attention by the research community and industry, IoT adaptation has gained momentum. IoT-enabled applications are being rapidly developed in a number of domains such as energy management, waste management, traffic control, mobility, healthcare, ambient assisted living, etc. On the other hand, this high-speed development and adaptation has resulted in the emergence of heterogeneous IoT architectures, standards, middlewares, and applications. This heterogeneity is hindrance in the realization of a much anticipated IoT global eco-system. Hence, the heterogeneity (from hardware level to application level) is a critical issue that needs high-priority and must be resolved as early as possible. In this article, we present and discuss the modelling of heterogeneous IoT data streams in order to overcome the challenge of heterogeneity. The data model is used within the VITAL project which is an open source IoT system of systems. The main objective of the VITAL platform is to enable rapid development of cross-platform and cross-context IoT based applications for smart cities.
AB - In the past few years, the viability of the Internet of Things (IoT) technology has been demonstrated, leading to increased possibilities for novel human-centric services in the smart cities. This development has resulted in numerous approaches being proposed for harnessing IoT for smart city applications. Having received a significant attention by the research community and industry, IoT adaptation has gained momentum. IoT-enabled applications are being rapidly developed in a number of domains such as energy management, waste management, traffic control, mobility, healthcare, ambient assisted living, etc. On the other hand, this high-speed development and adaptation has resulted in the emergence of heterogeneous IoT architectures, standards, middlewares, and applications. This heterogeneity is hindrance in the realization of a much anticipated IoT global eco-system. Hence, the heterogeneity (from hardware level to application level) is a critical issue that needs high-priority and must be resolved as early as possible. In this article, we present and discuss the modelling of heterogeneous IoT data streams in order to overcome the challenge of heterogeneity. The data model is used within the VITAL project which is an open source IoT system of systems. The main objective of the VITAL platform is to enable rapid development of cross-platform and cross-context IoT based applications for smart cities.
KW - Data model
KW - Internet of Things (IoT)
KW - Interoperability
KW - Linked data
KW - Smart cities
UR - http://www.scopus.com/inward/record.url?scp=85018648132&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-56877-5_2
DO - 10.1007/978-3-319-56877-5_2
M3 - Conference Publication
AN - SCOPUS:85018648132
SN - 9783319568768
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 20
EP - 35
BT - Interoperability and Open-Source Solutions for the Internet of Things - 2nd International Workshop, InterOSS-IoT 2016 held in Conjunction with IoT 2016, Invited Papers
A2 - Broering, Arne
A2 - Soursos, Sergios
A2 - Zarko, Ivana Podnar
A2 - Serrano, Martin
PB - Springer-Verlag
T2 - 2nd Workshop on Interoperability and Open-Source Solutions for the Internet of Things, InterOSS-IoT 2016 and co-located with the 6th International Conference on the Internet of Things, IoT 2016
Y2 - 7 November 2016 through 7 November 2016
ER -
