TY - GEN
T1 - Low-Code Internet of Things Application Development for Edge Analytics
AU - Chaudhary, Hafiz Ahmad Awais
AU - Guevara, Ivan
AU - John, Jobish
AU - Singh, Amandeep
AU - Margaria, Tiziana
AU - Pesch, Dirk
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022
Y1 - 2022
N2 - Internet of Things (IoT) applications combined with edge analytics are increasingly developed and deployed across a wide range of industries by engineers who are non-expert software developers. In order to enable them to build such IoT applications, we apply low-code technologies in this case study based on Model Driven Development. We use two different frameworks: DIME for the application design and implementation of IoT and edge aspects as well as analytics in R, and Pyrus for data analytics in Python, demonstrating how such engineers can build innovative IoT applications without having the full coding expertise. With this approach, we develop an application that connects a range of heterogeneous technologies: sensors through the EdgeX middleware platform with data analytics and web based configuration applications. The connection to data analytics pipelines can provide various kinds of information to the application users. Our innovative development approach has the potential to simplify the development and deployment of such applications in industry.
AB - Internet of Things (IoT) applications combined with edge analytics are increasingly developed and deployed across a wide range of industries by engineers who are non-expert software developers. In order to enable them to build such IoT applications, we apply low-code technologies in this case study based on Model Driven Development. We use two different frameworks: DIME for the application design and implementation of IoT and edge aspects as well as analytics in R, and Pyrus for data analytics in Python, demonstrating how such engineers can build innovative IoT applications without having the full coding expertise. With this approach, we develop an application that connects a range of heterogeneous technologies: sensors through the EdgeX middleware platform with data analytics and web based configuration applications. The connection to data analytics pipelines can provide various kinds of information to the application users. Our innovative development approach has the potential to simplify the development and deployment of such applications in industry.
KW - Edge analytics
KW - Low code
KW - Model driven development
UR - http://www.scopus.com/inward/record.url?scp=85142727704&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-18872-5_17
DO - 10.1007/978-3-031-18872-5_17
M3 - Conference contribution
AN - SCOPUS:85142727704
SN - 9783031188718
T3 - IFIP Advances in Information and Communication Technology
SP - 293
EP - 312
BT - Internet of Things. IoT through a Multi-disciplinary Perspective - 5th IFIP International Cross-Domain Conference, IFIPIoT 2022, Proceedings
A2 - Camarinha-Matos, Luis M.
A2 - Ribeiro, Luis
A2 - Strous, Leon
PB - Springer Science and Business Media Deutschland GmbH
T2 - 5th IFIP International Cross-Domain Conference on Internet of Things, IFIPIoT 2022
Y2 - 27 October 2022 through 28 October 2022
ER -
