10th International Congress on Information and Communication Technology

Authors - Hicham ESSAMRI, Abderrahim BAJIT, Khalid BOUALI, Youness ZAHID, Rachid EL BOUAYADI
Abstract - The need for sustainable agricultural techniques has become a necessary need today, as the urgent need for management of vital agricultural resources such as water, energy and fertilizers has triggered the alarm signal and immediately imposed an urgent resolution on a global scale. The new technologies proposed by precision agriculture in agricultural greenhouses IOT platforms have offered innovative environments. The growth of hardware components inside its nodes and the outcomes on an intelligent platform show how processing power and energy efficiency have evolved over time. Future developments in intelligent agriculture are made possible by these strategies. Computational intelligence allows for energy sustainability, perceptual encoding reduces communication time, while visual watermarking optimizes data integrity protection. Moreover, data analysis becomes the main challenge in precision agriculture, because on the computing machine side of the agricultural greenhouse has become the centerpiece in terms of intelligent solicitation of data instead of a classic collection from the node sensors [1]. To intelligently collect the data when needed, this aim is reached on the one hand, between a node and its relative sensors, and on the other hand between the cloud and the IoT nodes. Optimizing such behavior on the cloud side requires a good understanding, modeling and validation based on a clear analysis of the data. Thanks to computational intelligence, we can approximate the results of lost and inaccurate sensors and generate the required forecasts using data analysis tools [2], thus ensuring that farmers make informed decisions and achieve better results. Methods that support objective and subjective optimization of PAYLOAD and have a notable impact on the overall greenhouse performance, such as data optimization, energy savings, and node state management. This objective is clearly ensured by successively deploying prediction of missing or unwanted data, visually based quality coding, energy efficiency in terms of idling any sleeping node, and synchronizing their handshake with Cloud. These features, as detailed later in this article, enhance precision farming performance.