Development of sensor nodes and sensors for smart farming

The world population is continuously increasing. Smart farming is required to keep up with this development by producing more food in a sustainable way. In many new sensor solution developments, the results of the sensor itself is at the target, but the whole solution fails to meet the requirements of the agriculture sensing use cases: the developments suffer from singular approaches with a constricted view solely on the sensor, which might be exchangeable. In this article, we present a holistic approach that can help to overcome these challenges. This approach considers the whole use case, from sense, compute, and connect to power. The approach is discussed with the example of the PLANtAR project, where we develop a soil nitrate sensor and a new leaf wetness and microclimate sensor for application in a greenhouse. The resulting sensor is integrated into a sensor node and compared to a state-of-the-art system. The work shows what is needed to assess the best tradeoffs for agriculture use cases based on a horticulture application

Determining fresh tomato weight using depth images from an AR headset

There is a need for handsfree devices in greenhouses for training and harvesting assistance. Augmented Reality could offer this in the near future. We showed that it is possible to detect ripeness characteristics of tomatoes using the 3D scanning capabilities of the HoloLens. We verified this in an experimental setup with multiple tomato varieties. Our results show the possibilities and problems of this technique for future development

Performance evaluation of the AquaTag, a prototype near-field RF-based soil moisture sensor

Soil sensor activated irrigation scheduling is used in agriculture to optimally dose water and improve water use efficiency. Soil moisture sensors give point-related information and due to heterogeneities in soil hydraulic properties, use of a limited number of sensors may lead to errors in the average soil moisture content obtained for a field. As prices for individual IoT-based soil moisture sensors are still high, there is a need for low-cost soil moisture sensors. The AquaTag prototype is a passive, impedance-based sensor tag and a hand-held readout device for measuring soil water content. It operates contactless using a near-field, narrow-band RF-technology at 27 MHz. The tag has a lower accuracy than regular FD or TDR sensors, but it has the potential to be produced at very low-cost. Growers with small-scale, low-tech soil-grown crop production systems could use it to save water at acceptable cost. The aim of this work was to evaluate performance of prototypes, especially for the effects of production variability, reader-sensor positioning, temperature and soil type calibration. Sensor repeatability was ±0.62% and the overall accuracy tested with well-saturated glass beads was ±10.4%, taking effects of functional calibration, reader positioning and temperature into account. Production variability was improved by functional testing, selection and optimizing the reader signal analysis. Measurements for dry and wet sandy soils are possible at sensor-reader distances up to 10 cm. The reader angular position influences readings only marginally, if measurements are taken with care. Soil temperature affects sensor readings considerably, but the effect of the tag temperature is only marginally. A single calibration curve for two loamy-clay sandy soils was obtained. The AquaTag seems suitable to determine soil moisture content, but in order to reach an accuracy of below ±10%, sensors must be tuned individually, for temperature a compensation is required and in-situ calibration for well-saturated soils is advised. Sensors with a longer shaft are required to use the tag for measurements at common crop rooting depths

Beheersing emissie grondgebonden kasteelten : implementatie emissiemanagement systeem grondgebonden teelten

To make growers to be in control of the emission, a decision support system is developed for irrigation in soil grown crops. In 2013-2014 the implementation was continued and several greenhouse crops were monitored. As was found earlier, the organic greenhouse growers are able to control irrigation in a way that emission is reduced to a minimum. The results obtained at (conventional) flower growers show sometimes high emission of nitrogen. This is due at one hand to high irrigation surpluses but also to high fertilisation of nitrogen. Better tuning of the water- and nitrogen supply to the crop demand is necessary. For these stapes growers need better soil-moisture sensors

Sensor-based management of container nursery crops irrigated with fresh or saline water

The objective of this study was to design and test a prototype fertigation controller for the management of container ornamental nursery stocks irrigated with different water sources, including saline water or reclaimed municipal/industrial wastewater. The prototype could schedule irrigation in various ways, i.e. as a time clock, or by means of a soil moisture dielectric sensor, or using a crop evapotranspiration (ET) model. The prototype also monitored the salinity in the root zone using a dielectric sensor that measured both substrate moisture and electrical conductivity (EC), or a probe measuring the EC of the water draining out of the containers. Excessive substrate salinization of the containers irrigated with saline water (containing 10 mM of sodium chloride) was prevented by the automated adoption of a series of measures: irrigation with fresh water or a mixture of fresh water and saline water; progressive increase of irrigation dose for each event, and progressive reduction of fertilizer concentration in the nutrient solution delivered to the crop. The system was tested in three experiments conducted in Pistoia (Italy) between 2008 and 2010 with two ornamental species: Photinia × fraseri Dress (a salt-medium tolerant species) and Prunus laurocerasus L. (a salt-sensitive species). When irrigation with fresh water was controlled with a dielectric sensor or an ET model, total irrigation water use and the loss of both N and P were reduced by 17% to 84% compared with the time-controlled irrigation. The sensor-based control of saline water irrigation reduced the salinity effects on dry matter accumulation in both species; however, it did not prevent the occurrence of leaf damages (leaf scorch) on Prunus plants, which were unmarketable by the end of growing season. On the contrary, no leaf damages were visible on Photinia plants irrigated with saline and/or fresh water, such that all were classified in the top quality market category. The controller developed in this work could be used in commercial nurseries to improve profitability and sustainability of container hardy ornamental nursery stock production

Development of a sweet pepper harvesting robot

This paper presents the development, testing and validation of SWEEPER, a robot for harvesting sweet pepper fruit in greenhouses. The robotic system includes a six degrees of freedom industrial arm equipped with a specially designed end effector, RGB-D camera, high-end computer with graphics processing unit, programmable logic controllers, other electronic equipment, and a small container to store harvested fruit. All is mounted on a cart that autonomously drives on pipe rails and concrete floor in the end-user environment. The overall operation of the harvesting robot is described along with details of the algorithms for fruit detection and localization, grasp pose estimation, and motion control. The main contributions of this paper are the integrated system design and its validation and extensive field testing in a commercial greenhouse for different varieties and growing conditions. A total of 262 fruits were involved in a 4-week long testing period. The average cycle time to harvest a fruit was 24â\u80\u89s. Logistics took approximately 50% of this time (7.8â\u80\u89s for discharge of fruit and 4.7â\u80\u89s for platform movements). Laboratory experiments have proven that the cycle time can be reduced to 15â\u80\u89s by running the robot manipulator at a higher speed. The harvest success rates were 61% for the best fit crop conditions and 18% in current crop conditions. This reveals the importance of finding the best fit crop conditions and crop varieties for successful robotic harvesting. The SWEEPER robot is the first sweet pepper harvesting robot to demonstrate this kind of performance in a commercial greenhouse