Data processing and analysis
Data Science services with a network of experts to process and analyze your Precision Agriculture data
Scientific and technical reviews
A state of the art and an assessment of the maturity of your technical and scientific questions in Precision Agriculture
Tailor-made training and teaching courses
Tailor-made training courses with free tools (QGIS, R, GeoFIS…) to manipulate your Precision Agriculture data
Support and follow-up of projects
A personalized support on your strategy and Precision Agriculture projects
The number of actors involved in the collection of agronomic data for monitoring agrosystems is extremely large. Farmers, cooperatives, technical and research centres, agricultural manufacturers, sensor and imaging suppliers; all generate knowledge on agricultural plots thanks to their expertise, field experiments or the use of sensor tools (static, on-board or flying platforms)
Alone, this raw data is often not that meaningful nor useful. This latter must be placed in a particular production context, exploited and processed by high-performance and tailor-made algorithms, and absolutely discussed with the actors concerned (farmers, advisors, cooperatives, etc.). The main objective is to transform this raw data into intelligible and relevant information to enable clear decision-making and concrete action on the ground. The discovery of knowledge from these data is certainly interesting, but these data will only be taken seriously by agricultural actors if it is demonstrated that they bring significant value and gain to the production system, whether at technical, logistical, economic, environmental or social levels.
Aspexit is driven by a real desire to generate concrete decisions and actions on the ground, to work with multidisciplinary approaches (agronomy, pedology, computer science, geomatics, statistics...) and to create links between public and private actors in the agricultural sector. Aspexit offers a range of services to help agricultural sector actors to exploit and enhance their Precision Agriculture data to transform the raw data collected into information and decision layers.
Birth of Aspexit
Are you interested in the research projects I have been working on ?
Ah, Precision Agriculture! We hear about it all the time right now. Agriculture 4.0 (I don’t even know what number we’re at anymore), super precise machines, connected sensors….. Digital technologies and innovations create a buzz in agriculture (Note: Sprinkle it all with a little bit of Big Data, Deep Learning or Artificial Intelligence to shine Read more about Precision Agriculture in all intimacy[…]
The complex architecture that we have detailed in detail in the previous sections is a multi-layer perceptron (MLP). This is the classic architecture of the neural network. Nevertheless, depending on the type of data used to input neural models (images, voice signal, etc.), more specific architectures have been implemented. To work with images, for example, Read more about Neural network – Let’s try to demystify all this a little bit (3) – Application to images[…]
With everything that has been presented in Part 1, I hope that you will have understood how a neural network works in general, with the two main steps of forward and back propagation. And that’s not bad enough, it’s a lot of concepts to mature! In this part, without going into too much detail either, Read more about Neural network – Let’s try to demystify all this a little bit (2) – To go a little further[…]
Unless you have emerged from a period of cryogenics or have been locked in a bunker for several years, it is unlikely that you have never heard of a neural network. Having heard about it is one thing. Understanding what can be used is another. Knowing how it works is a whole different matter. If Read more about Neural network – Let’s try to demystify all this a little bit (1) – Neural architecture[…]
The concept of fuzzy logic was proposed in the 1960s by Lotfi Zadeh, an Iranian mathematician and computer scientist, to tackle the limits of good old classical logic. Which limits are we talking about? Let’s take a first very simple example on the temperature of the water that flows when you take a shower. If Read more about Fuzzy logic or the extension of classical logic[…]
Visualizing your data is THE most important part during your project management (we often talk about “Data Visualization” or Dataviz”). Whether upstream to understand a little bit about how the data are arranged or downstream so that a decision-maker can make an informed decision, there is always a time when we will have to think Read more about Data Visualisation with R and Shiny[…]
Few will tell you that their data is all pretty and clean and can be used as is in decision models… That’s a fact. When a dataset is collected, no one is immune to the risk of biased or outliers coming up and disrupting the quality of the data. And there are plenty of sources Read more about Outliers, abnormal data, Let’s take a look at the situation[…]
Parameter setting of QGIS and R The presentation of QGIS is no longer necessary! This open-source platform is now widely used in many domains to visualize, exploit and process spatialized data. The processing functions inherent in QGIS in addition to all those of the associated geographic information systems (SAGA, GRASS…) via the geoprocessing module allow Read more about Link R and QGIS: Integrate your own R algorithms in QGIS[…]
Precision agriculture tools (pedestrian, static, tractor-mounted or airborne sensors, etc.) make it possible to acquire agronomic and environmental data sets at impressive spatial, temporal and attribute resolutions. Generally speaking, we tend to trust these captured data (sometimes too much), i.e., we often use them as they are, without really asking ourselves too many questions! However, Read more about Uncertainty and Sensitivity[…]
All the data acquisition systems positioned in and around agricultural fields generate a very large amount of information on the functioning of production systems. However, this raw data from the sensors alone is of little interest. This data must be placed in a particular production context and processed with tailor-made algorithms in order to be Read more about GeoFIS : an open source platform to process Precision Agriculture data[…]