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In the domain of efficient management of resources and ensuring nutritional consistency, accuracy in predicting crop yields becomes crucial. The advancement of artificial intelligence techniques, synchronized with satellite imagery, has emerged as a potent approach for forecasting crop yields in modern times. We used two types of data: spatial data and temporal data. Spatial data are gathered from satellite imagery and processed using ArcGIS to extract data about crops based on several indices like NDVI and NWDI. Temporal data are gathered from agricultural sensors such as temperature sensors, rainfall sensor, precipitation sensor and soil moisture sensor. In our case we used Sentinel 2 satellite to extract vegetation indices. We have used IoT systems, especially Raspberry Pi B+ to collect and process data coming from sensors. All data collected are then stored into a NoSQL server to be analysed and processed. Several machine learning and deep learning algorithms have been used for the processing of crop recommendation system, such as logistic regression, KNN, decision tree, support vector machine, LSTM, and Bi-LSTM through the collected dataset. We used GRU deep learning model for the best performance, the RMSE and R2 for this model was 0.00036 and 0.99 respectively.The main contribution of our paper is the development of a new system that can predict several crop yields, such as wheat, maize, etc., using IoT, satellite imagery for spatial data and the use of sensors for temporal data. We are the first paper that has combined spatial data and temporal data to predict crop yield based on deep learning algorithms, unlike other works that uses only remote sensing data or temporal data. We created an E-monitoring crop yield prediction system that helps farmers track all information about crops and show the result of prediction in a mobile application. This system helps farmers with more efficient decision making to enhance crop production. The main production regions of wheat in Morocco are in the rainfed areas of the plains and plateaus of Chaouia, Abda, Haouz, Tadla, Gharb and Saïs. We studied three main regions well known for wheat production which are Rabat-Salé, Fez-Meknes, Casablanca-Settat.

The static corrections are a necessary step in the sequence of the seismic processing. This paper presents a study of these corrections in the Essaouira basin. The main objective of this study is to calculate the static corrections by exploiting the seismic data acquired in the field to improve the deep structures imaging. It is to determine the roof and the basis of the superficial layers which constitute the weathered zone while calculating the delays of seismic wave’s arrivals in these layers. The purpose is to cancel the effect of the topography and the weathered zone, in order to avoid any confusion when the seismic and geological interpretation. The results obtained show the average values of the static corrections varying between - 127 and 282 ms (double time), with existence of high values by location, particularly in the Eastern and North-Eastern of the basin, which meant the presence of altered zone with irregular topography and whose thickness and speeds vary laterally. In effect the variations of velocities in the fifty meters from the surface may introduce significant anomalies in seismic refraction, with heavy consequences when the interpretation or the drilling establishment. These variations are mainly due to lateral changes in facies and variations in the formations thickness. The calculation of the static corrections, revealed high values at certain areas (East and North-East), which will enable us to better orient the future campaigns in these zones. It is therefore necessary to concentrate the seismic cores drillings and the small refraction seismic profiles by tightening the seismic lines meshes in order to have the maximum values of static corrections and thereafter a better imaging of the reflectors.

The Tleta of Beni Ider region located in the SW of Tetouan (Rif Septentrional) knows many mass instabilities. The diagnostic via the inventory, the mapping and the characterization of mass movements was made by using satellite imagery, aerial photography and field data coupled with existing documents (geological, geomorphological,…). The understanding of both their spatial distribution and the mechanism generating them, is very complex because of the existence of an important number of natural factors (geological, geomorphological, hydrological) in a relative mountainous landscape with deep valleys, steep slopes and significant elevation changes. Thus, a multidisciplinary approach was adopted to elaborate the landslide susceptibility map of the region taking into account interactions and causal relationships between the various natural parameters that tend to accentuate and aggravate the setting of landslides. The multidisciplinary database allowed us to evaluate the susceptibility thanks to a bivariate probabiliste model (Weight of Evidence). The obtained landslide susceptibility map is a major contribution to the development of urban development plans in the region.

The peninsula of Tangier (Northern Morocco) is submitted to a significant number of landslides each year due to its lithological, structural and morphological complexity; which cause a lot of damage to the road network and other related infrastructure. The main objective of this study is to create a landslide indexed susceptibility map of Tangier peninsula, by using AHP (Analytical Hierarchical Processes) model to calculate each factor’s weight. The work is made via GIS by using an ArcGIS AHP extension. In the current research, First of all, the four main types of landslides were identified and mapped from existing documents, works and new data which came from either remote sensing or fieldwork. Lithology, land use, slope, hypsometry, exposure, fault density and drainage network density were used as main parameters controlling the occurrence of the selected landslides. Then, afterward, each parameter is classified into a number of significant classes based on their relative influence on gravitational movement genesis. The validity of the susceptibility zoning map which is obtained through linear summation of indexed maps was tested and cross-checked by inventoried and studied landslides. The obtained landslide susceptibility map constitutes a powerful decision-making tool in land-use planning, i.e. New highways, secondary highways, railways, etc. within the national development program in the Northern provinces. It is a necessary step for the landslides hazard assessment in the Tangier peninsula in northern Morocco.

Despite the fact that agent technologies have widely gained popularity in distributed systems, their potential for advanced management of vehicle traffic has not been sufficiently explored. This paper presents a traffic simulation framework based on agent technology and fuzzy logic. The objective of this framework is to act on the phase layouts represented by its sequences and length to maximize throughput and fluidize traffic at an isolated intersection and for the whole multi-intersection network, through both inter- and intra-intersection collaboration and coordination. The optimizing of signal layouts is done in real time, and it is not only based on local stream factors but also on traffic stream conditions in surrounding intersections. The system profits from agent communication and collaboration as well as coordination features, along with decentralized organization, to decompose the traffic control optimization into subproblems and enable the distributed resolution. Thus, the separate parts can be resolved rapidly by parallel tasking. It also uses fuzzy technology to handle the uncertainty of traffic conditions. An instance of the proposed framework was validated and designed in the ANYLOGIC simulator. Instantiation results and analysis denote that the designed system can significantly develop the efficiency at an individual intersection as well as in the multi-intersection network. It reduces the average travel delay and the time spent in the network compared to multi-agent-based adaptative signal control systems.

In this article, the problem of the free vibration behavior of a cantilever Euler-Bernoulli beam with various non-classical boundary conditions, such as rotational, translational spring, and attached mass is investigated. For describing the differential equation of the system. An analytical procedure is proposed firstly, and a numerical method based on the differential transform method DTM is developed in order to validate the obtained results. A parametric study for various degenerate cases is presented with the aim to analyze the influence of rotational stiffness, vertical stiffness, and mass ratio on the free vibration response of the beam, particularly on its modal characteristics. The results show that the non-classical boundary conditions significantly affect the natural frequency and mode shapes of the studied beam system in comparison to the case of a classical boundary conditions such as Simply supported, clamped-clamped, etc. The comparison between the obtained results based on the proposed analytical solution and numerical scheme, and those available in the literature shows an excellent agreement.