
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
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
