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OUFTI-Next is the new CubeSat project of the University of Liège. This mission
was imagined after the success of OUFTI-1. The goal of this nanosatellite is to detect
hydric stress of agricultural fields around the world. It is equipped with a Mid-Wavelength
InfraRed (MWIR) detector. It will be a world premiere with such a small satellite (3U
or 30 cm × 10 cm × 10 cm). From the data, the temperature of the crop will be extracted
and the irrigation status assessed.
This satellite is a technology demonstrator for an ambitious project. The final goal
is indeed to create a smart irrigation program with a daily revisit over a location. It
will provide tools for farmers to improve the irrigation, increase the yield of their fields
and spare less drinkable water. With only one satellite, it is unfortunately impossible.
OUFTI-Next’s mission is no less important because it will demonstrate that the integration
of a MWIR detector is feasible.
This master thesis is the continuity of a feasibility study done last year (2016-2017).
From the requirements, primordial aspects of the satellite are developed. Orbits, communication,
power budget, attitude strategy, ... are typical topics introduced in this work. It
offers an overview of the satellite and a link between different subjects addressed in other
master theses (the detector’s cooling system, the optical design and the thermal aspect).
At the end, some configurations, thought as simple as possible, are introduced and
discussed. All subsystems are reviewed with the will to find an optimal configuration. Of
course, concessions are done and assumptions made. At this stage of the development, it
is natural that some information is missing.

CubeSat --- Systems Engineering --- OUFTI-Next --- Satellite --- Smart irrigation --- Ingénierie, informatique & technologie > Ingénierie aérospatiale

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Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

optical sensor --- spectral analysis --- response surface sampling --- sensor evaluation --- electromagnetic induction --- multivariate water quality parameters --- mandarin orange --- crop inspection platform --- SPA-MLR --- object tracking --- feature selection --- simultaneous measurement --- diseases --- genetic algorithms --- processing of sensed data --- electrochemical sensors --- thermal image --- ECa-directed soil sampling --- handheld --- recognition patterns --- salt concentration --- clover-grass --- bovine embedded hardware --- weed control --- soil --- field crops --- vineyard --- connected dominating set --- water depth sensors --- SS-OCT --- wheat --- striped stem-borer --- silage --- geostatistics --- detection --- NIR hyperspectral imaging --- electronic nose --- machine learning --- virtual organizations of agents --- packing density --- data validation and calibration --- dataset --- Wi-SUN --- temperature sensors --- geoinformatics --- gas sensor --- X-ray fluorescence spectroscopy --- vegetable oil --- photograph-grid method --- Vitis vinifera --- WSN distribution algorithms --- laser-induced breakdown spectroscopy --- irrigation --- quality assessment --- energy efficiency --- wireless sensor network (WSN) --- geo-information --- Fusarium --- texture features --- weeds --- discrimination --- big data --- soil moisture sensors --- meat spoilage --- land cover --- stereo imaging --- near infrared sensors --- biological sensing --- compound sensor --- pest management --- moisture --- plant localization --- heavy metal contamination --- artificial neural networks --- spectral pre-processing --- moisture content --- apparent soil electrical conductivity --- data fusion --- semi-arid regions --- smart irrigation --- back propagation model --- wireless sensor network --- energy balance --- light-beam --- fluorescent measurement --- agriculture --- precision agriculture --- deep learning --- spectroscopy --- hulled barely --- dielectric probe --- RPAS --- water supply network --- rice leaves --- mobile app --- gradient boosted machines --- hyperspectral camera --- one-class --- nitrogen --- LiDAR --- total carbon --- chemometrics analysis --- rice --- agricultural land --- on-line vis-NIR measurement --- CARS --- obstacle detection --- stratification --- neural networks --- regression estimator --- Kinect --- proximity sensing --- distributed systems --- pest --- noninvasive detection --- texture feature --- soil mapping --- classification --- soil salinity --- visible and near-infrared reflectance spectroscopy --- germination --- computer vision --- hyperspectral imaging --- diffusion --- dielectric dispersion --- UAS --- random forests --- case studies --- total nitrogen --- thermal imaging --- cameras --- dry matter composition --- near-infrared --- salt tolerance --- deep convolutional neural networks --- soil type classification --- water management --- preprocessing methods --- wireless sensor networks (WSN) --- remote sensing image classification --- precision plant protection --- radar --- spatial variability --- GF-1 satellite --- plant disease --- naked barley --- leaf area index --- CIE-Lab --- change of support --- radiative transfer model --- 3D reconstruction --- plant phenotyping --- vine --- near infrared --- vegetation indices --- remote sensing --- greenhouse --- time-series data --- scattering --- sensor --- crop area --- speckle --- spatial data --- grapevine breeding --- wide field view --- partial least squares-discriminant analysis --- spiking --- area frame sampling --- chromium content --- machine-learning --- RGB-D sensor --- pest scouting --- PLS --- Capsicum annuum --- spatial-temporal model --- drying temperature --- boron tolerance --- ambient intelligence --- laser wavelength --- fuzzy logic --- dynamic weight --- landslide --- management zones --- real-time processing --- event detection --- crop monitoring --- apple shelf-life --- rice field monitoring --- wireless sensor --- birth sensor --- proximal sensor