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![Fig. 2. The architecture of the IoLT Smart Pot Gateway as shown in [28]](profile/Attila-Kertesz-2/publication/341890718/figure/fig2/AS:900121902465025@1591617193462/The-architecture-of-the-IoLT-Smart-Pot-Gateway-as-shown-in-28_Q320.jpg)
Cloud Computing and the Internet of Things (IoT) have started to revolutionize traditional systems to be smart. Smart farming is an example of this process, that aims to respond to predictions and provisions of population growth by providing smart solutions in agriculture to improve productivity and reduce waste. Plant phenotyping is an important r...
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Drought stress is one of the main threats to poplar plant growth and has a negative impact on plant yield. Currently, high-throughput plant phenotyping has been widely studied as a rapid and nondestructive tool for analyzing the growth status of plants, such as water and nutrient content. In this study, a combination of computer vision and deep lea...
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... In relation to the technological advances of Industry 4.0, cloud computing and the IoT (Internet of Things) contribute to making traditional systems smart [6][7][8]. An example of this process is smart farming (SF) that improves productivity and reduces surplus elements used in crops [9]. On the other hand, within the IoT concept, the role of wireless sensor networks (WSN) is paramount [10,11] because several IoT applications are based on wireless data transmission allowing sensor/actuator nodes to communicate with each other through a wireless network connection, even potentialized within the mMTC (massive machine-type communications) scenario of 5G [12][13][14][15]. ...
Citation: Cama-Pinto, D.; Damas, M.; Holgado-Terriza, J.A.; Arrabal-Campos, F.M.; Martínez-Lao, J.A.; Cama-Pinto, A.; Manzano-Agugliaro, F. A Deep Learning Model of Radio Wave Propagation for Precision Agriculture and Sensor System in Greenhouses. Agronomy 2023, 13, 244. https:// Abstract: The production of crops in greenhouses will ensure the demand for food for the world's population in the coming decades. Precision agriculture is an important tool for this purpose, supported among other things, by the technology of wireless sensor networks (WSN) in the monitoring of agronomic parameters. Therefore, prior planning of the deployment of WSN nodes is relevant because their coverage decreases when the radio waves are attenuated by the foliage of the plantation. In that sense, the method proposed in this study applies Deep Learning to develop an empirical model of radio wave attenuation when it crosses vegetation that includes height and distance between the transceivers of the WSN nodes. The model quality is expressed via the parameters cross-validation, R 2 of 0.966, while its generalized error is 0.920 verifying the reliability of the empirical model
... The BRC is also involved in the development of affordable phenotyping solutions, which can lower the significant price barrier, which currently stands as an obstacle to the wider application of phenotyping approaches. In collaboration with informaticians of the Szeged University they have developed a cloud-based 'smart pot' system that provides a low-cost solution for monitoring plant growth in greenhouse conditions (Pflanzner et al., 2020). In addition to plant phenotyping, they also developed phenotyping methods for microalgae by using precisely designed and operated photobioreactor systems with multiple sensors of physicochemical parameters (dissolved oxygen, pH, and optical density) and gas control, allowing real-time monitoring of the physiological changes and net photosynthesis under Ci limitation (Patil et al., 2020). ...
The Pannonian Plain, as the most productive region of the South-East Europe, has a long tradition of agronomical production as well as agronomical research and plant breeding. Many research institutions from agri-food sector of this region have a significant impact on agriculture. Their well-developed and fruitful breeding programmes resulted in productive crop varieties highly adapted to the specific regional environmental conditions. Rapid climatic changes that occurred during the last decades advanced even more investigations of complex interactions between plants and their environments and the creation of climate-smart and resilient crops. Plant phenotyping is an essential part of botanical, biological, agronomic, physiological, biochemical, genetic and different -omics approaches. Phenotyping tools and applied methods differ among these disciplines, but basically, all of them are used to evaluate and measure complex traits related to growth, yield, quality and adaptation to different environmental stresses (biotic and abiotic). During almost a century long period of plant breeding in the Pannonian region, the plant phenotyping methods have changed, from simple measures in the field to modern plant phenotyping and high throughput non-invasive and digital technologies. In this review, we will present a short historical background and the most recent developments in the field of plant phenotyping, as well as the results accomplished so far in Croatia, Hungary and Serbia. Current status and perspectives for further simultaneous regional development and modernisation of plant phenotyping are also discussed.
... Some use it to denote networks of miniaturised genomic sequencers and computational resources needed to interpret the collected genomic sequences [129]; some use it as a term for wireless sensors attached to humans, usually in healthcare context [130]; finally, some use it for sensor networks in macroscopic biological context interacting with technology, e.g. smart IoT-enabled agriculture [131]. ...
Cyborg insects are a major part of the vision of future interactions of the living world and technology, including but not limited to the Internet of Living Things (IoLT). They are crawling or flying insects with additional electronic circuitry allowing remote control of their movement and collection of sensory data. In this critical review, we survey the historical development of cyborg insects engineering, from the first backpacks on insects used for communication and sensing, to different methods of control and actuation of insects’ locomotion. We review the suggested applications of cyborg insects ranging from military use to agriculture, pointing out the problematic connotations of swarms and cyborgs in these contexts. We address the applications and the narratives around engineered insects from the perspective of philosophy, economy, law, and politics. We add perspectives on emancipatory potential of cyborg technology and where the future of it could lie.
Digital Twins can be considered as a new phase in smart and data-driven greenhouse horticulture. A Digital Twin is a digital equivalent to a real-life object of which it mirrors its behaviour and states over its lifetime in a virtual space. Research indicates that they can substantially enhance productivity and sustainability, and are able to deal with the increasing scarcity of green labour in greenhouse horticulture. This paper presents the results of a systematic literature review on Digital Twin applications in greenhouse horticulture. The review identifies 8 articles that explicitly address Digital Twins in greenhouse horticulture and 115 studies that implicitly apply the Digital Twin concept in smart IoT-based systems. Findings indicate that the concept of the Digital Twin is in a seminal phase in greenhouse horticulture, but there are existing applications that are not yet framed as Digital Twins. In the reviewed papers, there is a dominant focus on the cultivation process at the greenhouse level, among others for climate control, energy management and lighting. About 9% of the articles are virtualizing plants themselves, which indicates that the granularity level addressed is still rather limited. Only 7 % of the articles look beyond plants or single greenhouses. None of the reviewed articles consider the company level. Furthermore, most applications address monitoring and control of the state and behaviour of real-life objects. More advanced applications, including predictive and prescriptive capabilities across the complete lifecycle, are still in an early stage of development, although predictive Digital Twins are gaining prominence.
