According to FAO, small-scale farming has an enormous contribution to food security and to rural economy. However, smallholders usually face a number of constraints that are impeding their productivity, profitability and contribution to economic growth. Water resource is one of the major constraints and the situation is foreseen to worsen due to water shortage in relation with current excessive use and climate change. Controlled and improved irrigation can save water while maximising plant growth and yield.
The usage of smart technologies and especially sensor systems – for instance soil water content and matric potential sensors – is not new in agriculture. So-called “Smart Farming Technologies (SFT) cover a range of different aspects of precision agriculture including data acquisition technologies, data analysis and evaluation technologies and precision application technologies”. When it comes to irrigation in particular, the underlying approach is to collect real-time soil conditions and to schedule irrigation when needed, possibly taking into account various data sources such as soil texture, soil chemical properties and weather data to name a few. However, existing high-end commercial systems are mostly based on very high cost professional sensor devices (usually coupled with costly soil mapping process) which dramatically limits the number of units that can be deployed. On the other hand, when adopting a low-cost design approach, one main issue is the reliability and accuracy of the collected data which is always low and can dramatically limit the efficiency of the deployed system.