Intel-IrriS is a PRIMA project from Section 2 Multitopic 2020 Thematic Area 1-Water management addressing low cost, lean solutions for enhancing irrigation efficiency of small-scale farms. Intel-IrriS will provide the smallholder farmers a more efficient management of its available water by deploying of an open, low-cost and autonomous irrigation control system based on IoT and smart technologies. The irrigation process to decide/suggest how much water is needed to maintain the optimal production potential without water wasting can be adapted (i) for a particular crop, (ii) at a particular moment and (iii) for a given soil type and condition because it will be seconded by algorithms predicting the behaviour of the complex soil/plant/atmosphere system.

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Period of Implementation

Jun 1, 2021 - May 31, 2024
Total Budget

EUR 1,045,120.00



The goal of Intel-IrriS is to contribute in not only saving water but also in increasing the water usage efficiency, while taking into account the specificities of socio-economic contexts of smallholder farmers as well as current irrigation practices. Existing solutions are generally very expensive and provide raw data which are not easy to be used directly by small farmers. Therefore, Intel-IrriS main objectives are (1) to reduce the cost of smart technologies for smallholders – dividing the cost by a factor between 10 and 100, (2) to increase adoption of smart technologies by smallholders by "translating" raw data into readable information used for making decision about irrigation adjustment (reducing total amount of water through improved timing and real-time adaptation to the agro-environmental conditions) and (3) to increase on a long-term the smallholders' sustained production and income, as well as the local innovation opportunities and capacities.


Objective 1: Propose low cost but highly efficient water control systems for irrigation optimization. Objective 2: Use cutting-edge technologies to propose highly innovative systems yet simple to deploy and adapted to smallholders. Objective 3: Seamless integration into existing irrigation system and/or local customs and practices. Objective 4: Improve farmer's knowledge on water-related issues, foster local adaptation of technologies, increase local innovation capacity and facilitate technology appropriation. Objective 5: Large-scale adoption of low cost smart irrigation system by smallholders, stimulating synergies between various local actors.

Problems and Needs Analysis

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.

Intervention Strategy(ies)

Intel-IrriS will propose a low-cost water control system but will improve its efficiency. It will do so (1) by enabling deployment of several complementary low-cost sensors – and not only one costly sensor for a large area – to take into account the soil spatial and water spatial & time variability at field scale, which is made possible by the much lower cost per unit, (2) by using automatic and remotely controlled procedures for advanced calibration of the different sensors to increase accuracy of collected measures so that our water-soil-plants-climate interaction models will provide increased accuracy on recommended actions and (3) by including agricultural models/knowledge with corrective & predictive analytics – from simple computer-based decision models to more advanced AI-based processing – to adapt the applied control to local conditions & practices (dry region, open field or greenhouse) and crop/plant varieties that usually have different water need profile at their various stage of development.