This article presents the current state-of-the-art research on applying artificial intelligence
(AI) technology in smart greenhouses to optimize crop yields, water, and fertilizer use …

With the escalating global challenges of food security and resource sustainability, innovative
solutions like deep learning and computer vision are transforming agricultural practices by …

This paper contributes to smart greenhouses and IoT (Internet of Things) research. Our
pioneering achievement centers on successfully designing, constructing, and testing a 30m2 …

More recently, smart agriculture has received widespread attention, which is a deep
combination of modern agriculture and the Internet of Things (IoT) technology. To achieve …

To improve the sustainability and resilience of modern food systems, designing improved
crop management strategies is crucial. The increasing abundance of data on agricultural …

Greenhouse farming has become increasingly popular in recent years as a way to grow
crops in a controlled environment, offering farmers the ability to extend growing seasons and …

Meta-learning for offline reinforcement learning (OMRL) is an understudied problem with
tremendous potential impact by enabling RL algorithms in many real-world applications. A …

Smart agriculture applications using IoT (Internet of Things) is getting popular in recent
years. IoT-based smart agriculture applications involve the use of various sensor devices …

This paper presents a risk mitigating, time-varying feedback control algorithm for crop
production when state dynamics are subject to uncertainty. The model based case study …

Nowadays, ongoing digital transformation across different industries entirely changes the
way of operations in light of modern technologies. In the context of Industry 4.0, one of the …