TY - GEN
T1 - Enhancing Smart Agriculture Scenarios with Low-code, Pattern-oriented functionalities for Cloud/Edge collaboration
AU - Fatouros, Georgios
AU - Kousiouris, George
AU - Lohier, Theophile
AU - Makridis, Georgios
AU - Polyviou, Ariana
AU - Soldatos, John
AU - Kyriazis, Dimosthenis
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The integration of cloud computing and Internet of Things (IoT) technologies has brought significant advancements in the agriculture domain. However, the implementation of such systems often requires significant time and resources, making it challenging for smart agriculture providers to offer optimized yet affordable services for small and medium-sized farmers at scale. Low-code development platforms can be a viable solution to address these challenges, enabling non-experts to adapt or enhance existing applications with minimal coding. This paper presents a low-code approach to enhance smart agriculture scenarios with pattern-oriented functionality blocks for cloud/edge collaboration. It highlights the usage of a pattern collection for redesigning the implementation of smart agriculture applications that can enhance the data collection process as well as real-time decision-making and efficient resource management in the continuum. The effectiveness of the presented approach is demonstrated through the implementation of a case study in smart agriculture greenhouses. Evaluation results show that this approach can significantly reduce the time and effort required to deploy smart agriculture applications and provide data resilience.
AB - The integration of cloud computing and Internet of Things (IoT) technologies has brought significant advancements in the agriculture domain. However, the implementation of such systems often requires significant time and resources, making it challenging for smart agriculture providers to offer optimized yet affordable services for small and medium-sized farmers at scale. Low-code development platforms can be a viable solution to address these challenges, enabling non-experts to adapt or enhance existing applications with minimal coding. This paper presents a low-code approach to enhance smart agriculture scenarios with pattern-oriented functionality blocks for cloud/edge collaboration. It highlights the usage of a pattern collection for redesigning the implementation of smart agriculture applications that can enhance the data collection process as well as real-time decision-making and efficient resource management in the continuum. The effectiveness of the presented approach is demonstrated through the implementation of a case study in smart agriculture greenhouses. Evaluation results show that this approach can significantly reduce the time and effort required to deploy smart agriculture applications and provide data resilience.
KW - cloud patterns
KW - data resilience
KW - function as a service
KW - IoT
KW - low code
KW - smart agriculture
UR - http://www.scopus.com/inward/record.url?scp=85174411433&partnerID=8YFLogxK
U2 - 10.1109/DCOSS-IoT58021.2023.00055
DO - 10.1109/DCOSS-IoT58021.2023.00055
M3 - Conference contribution
AN - SCOPUS:85174411433
T3 - Proceedings - 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023
SP - 285
EP - 292
BT - Proceedings - 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023
Y2 - 19 June 2023 through 21 June 2023
ER -