… learning, and data lake. We designed a data management reference architecture for sustainable
agriculture and … Domain scoping, domain modeling, and reference architecture design …

… concerns and addressing the ever-increasing complexity of difficulties in agricultural … in
agricultural farm monitoring and crop disease prediction using deep learning architectures. Here …

… in agriculture.AI-enabled sensors function as smart sensors and IoT has made various types
of sensor-based equipment in the field of agriculture. … using deep learning architectures. The …

… First, Section II details previous studies in the area of 1) machine learning strategies that …
SIoT architecture. Then, we describe the overall system, describing the system architecture and …

… in advance using deep learning techniques using a long short/term memory model. In [19],
models of the rainfall are obtained using deep learning architectures and time series datasets …

… sustainability. Disruptive information and communication technologies such as machine
learning… a systematic review of machine learning (ML) applications in agricultural supply chains (…

… This work also adopted the Classic Machine Learning models and deep neural network
architectures for the Multi-classification of soils for the required nutrient supply to the field and …

… beyond agriculture and is relevant to all industries aiming to enhance sustainability and …
We applied machine learning techniques and developed crop-based models for their watering …

… Sustainability of agriculture in a closed-field … agricultural and hydrological processes
and climatic conditions is essential to ensure efficient irrigation and agricultural sustainability…

… The main limits of sustainable agricultural development in sub-Saharan countries are bad
practices in agricultural practices. By making this step, it allowed creating an agricultural …