Smart Farming Techniques for Climate Change Adaptation in Cyprus

Abstract

Smart farming based on Internet of Things (IoT) technologies enables crop farmers to collect real-time data related to irrigation and plant protection processes, aiming to increase production volume, improve product quality, and predict diseases, while optimizing resources and farming processes. IoT devices can collect vast amounts of environmental, soil, and crop performance data, thus building time series data that can be analyzed to forecast and compute recommendations and deliver critical information to farmers in real time. In this sense, the added-value from the farmers’ perspective is that such smart farming techniques have the potential to deliver a more sustainable agricultural production, based on a more precise and resource-efficient approach in the complex and versatile agricultural environment. The aim of this study is to investigate possible advantages of applying the Smart Farming as a Service (SFaaS) paradigm, aiming to support small-scale farmers, by taking over the technological investment burden and offering next generation farming advice through the combined utilization of heterogeneous information sources. The overall results of the pilot application demonstrate a potential reduction of up to 22% on total irrigation needs and important optimization opportunities on pesticides use efficiency. The current work offers opportunities for innovation targeting and climate change adaptation options (new agricultural technologies), and could help farmers to reduce their ecological footprint.

IRRISENS: An IoT Platform Based on Microservices Applied in Commercial-Scale Crops Working in a Multi-Cloud Environment

“…In the study here presented, we used a microservice-based approach similar to the microservice-based architectures discussed in [ 23 , 24 , 32 ], focused on message flow and the structure supporting that. A digital model was also present in the platforms introduced in [ 40 ] and in [ 22 ]. In [ 22 ], the platform was used to improve the management of crop plots and monitor crop needs for irrigation purposes and its core was the NGSI-LD broker.…”

“…In the work here presented, however, IRRISENS introduces a “digital model” and “crop parameter” microservices as the core of the microservice dataflow. In [ 40 ], the platform was used for managing irrigation and differed from that proposed here in that it was structured following a monolithic approach. Further, how the platform made use of the digital model was not described in [ 40 ].…”

“…In [ 40 ], the platform was used for managing irrigation and differed from that proposed here in that it was structured following a monolithic approach. Further, how the platform made use of the digital model was not described in [ 40 ]. The current work not only describes the platform architecture and functioning but also evaluated the platform in a truly commercial scale scenario being used by commercial farmers.…”

“…IRRISENS proposes elements to deal with all these types of heterogeneity in order to build the digital crop model. In [ 40 ], the platform makes use of several models in a monolithic platform but does not represent the entity being monitored, but rather evaluates the status of a crop, process data, and provides decision support.…”

Agriculture 4.0 and Smart Sensors. The Scientific Evolution of Digital Agriculture: Challenges and Opportunities

“…Nowadays, almost one billion people go to sleep hungry every day [13]. The human population is expected to reach 9 billion by 2050 [11] increasing food demand by up to 50% [14]. Most of these people are expected to live in the regions of South Asia and sub-Saharan Africa, where more than 20% of the current population are food insecure [15].…”