A layered IoT architecture for greenhouse monitoring and remote control

Abstract

Wireless Sensor Networks have been often used in the context of Greenhouse architectures. In this paper, an architecture is proposed for two Greenhouses based on Networked Control Systems. This architecture is IoT-based and built on top of switched Ethernet and Wi-Fi. Some sensors in the proposed architecture require a one-second real-time deadline. Riverbed simulations prove that there is zero packet loss and no over-delayed packets. An important contribution of this work is the design of a channel allocation scheme that prevents interference in this relatively large Greenhouse system. Another contribution of this work is the introduction of fault tolerance at the controller level. If one controller fails in one of the Greenhouses, the other controller automatically takes over the entire operation of the two-Greenhouse system. Riverbed simulations again show that this fault-tolerant system does not suffer any packet loss or over-delayed packets. Continuous Time Markov Chains are then developed to calculate the reliability as well as the steady state availability of the two-Greenhouse system. The Coverage parameter is taken into account. Finally, a case study is presented to quantitatively assess the advantage of fault tolerance in terms of downtime reduction; this is expected to be attractive especially in developing countries.

Artificial intelligence and machine learning in dynamic cyber risk analytics at the edge

“…The objective of this study was to build upon existing work on cyber risk standardisation [10], and AI in CPS [11], but with a greater focus on exploring the potential and practical challenges in the use of AI, in the service of improving personal and organisational resilience. The methodology applied in the study follows recommendations in existing studies on adaptive risk models [12]; feedback in IoT systems [13]; in layered IoT architecture [14]; and for optimising decision-making [15]. We identified approaches to model the risk within complex interconnected and coupled systems in cyber-physical environments.…”

Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions

“…Field monitoring applications are designed to report on different conditions such as soil fertility, temperature, humidity, gas content, air and water pressure, and the presence of disease in crops [22]. The use of IoT sensors and devices has also managed to eliminate the need for manual intervention to some extent, constituting a smart greenhouse design able to monitor and regulate various climatic parameters in accordance with the plants' needs [23].…”

Application of Digital Technologies for the Next Level of Agriculture Growth and Transformation under Changing the Indian Agriculture: A Critical Review

“…IoT base Precision farming consist of multiple monitoring and controlling applications such as climate conditions monitoring, soil patterns monitoring, pest and crop disease monitoring, irrigation, determine optimal time to plant and harvest and tracking/ tracing. Ibrahim et al [57] reported that the cultivation of greenhouse is more intense, therefore in terms of controlling and monitoring it requires high precision. To monitor environmental or weather conditions there have been several studies on the applications of WSN's in greenhouse.…”