Smart Agriculture with an Automated IoT-Based Greenhouse System for Local Communities

Li, Nianpu; Xiao, Yimeng; Shen, Lei; Xu, Zhen‐Jiang; Li, Botao; Yin, Chongxuan

doi:10.4236/ait.2019.92002

Cited by 13 publications

(7 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To start the process of building a smart hydroponic GH, it is always necessary to follow the standard recommendations in the design of the structure, especially the control and operation equipment. Beyond all the strategies, it should be used optimally at certain intervals to enrich the GH with organic materials [56].…”

Section: ) Smart Hydroponic Ghmentioning

confidence: 99%

A Systematic Review of Optimal and Practical Methods in Design, Construction, Control, Energy Management and Operation of Smart Greenhouses

Ghiasi,

Wang,

Mehrandezh

et al. 2024

IEEE Access

View full text Add to dashboard Cite

In an era characterized by severe climate change, dwindling resources, and a growing world population, the agricultural industry is facing unprecedented challenges. On the other hand, overuse of natural resources has emerged as a major concern worldwide. Greenhouses (GHs) have been developed as central environments capable of growing a diverse range of high-quality agricultural products throughout the year, regardless of external weather conditions. However, conventional GHs often impose significant costs on energy resources for their heating and cooling operations, thus presenting sustainability challenges. To address these pressing concerns, using new smart technologies as well as the integration and development of renewable energy sources, including photovoltaics (PVs), wind turbines (WT), and geothermal systems, have gained momentum. This integration not only increases the ecological footprint of GHs but also reduces their dependence on conventional energy sources. Furthermore, the adoption of smart GH technologies, characterized by advanced control and automation systems, holds significant promise in energy optimization and efficiency. Hence, this systematic review attempts to carefully examine the optimal and practical methods that include the design, fabrication, control, energy management, and operation of smart GHs. This review includes an in-depth analysis of GH structures, building materials, cooling and heating systems, new dark GH concepts, and smart lighting systems. In addition, it addresses effective strategies to curb energy consumption in smart GHs. By synthesizing and synthesizing existing research and practical experiences, this paper seeks to provide valuable insights and recommendations to facilitate the efficient and sustainable design, construction, and operation of smart GHs. Ultimately, this work aims to promote resource-efficient and environmentally conscious practices in the agricultural sector.

show abstract

Section: ) Smart Hydroponic Ghmentioning

confidence: 99%

A Systematic Review of Optimal and Practical Methods in Design, Construction, Control, Energy Management and Operation of Smart Greenhouses

Ghiasi,

Wang,

Mehrandezh

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Until recently, these domains faced many challenges, mainly due to the lack of wide-area connectivity, limited energy resources, and sometimes harsh environmental conditions that made the deployment of WSNs difficult or even impossible. Innovative and cutting-edge technological advances, however, have expanded the horizons with new low-cost enablers and energy-efficient wireless technologies [30] (like SigFox [58,59], LoRa [60][61][62], NB-IoT [61,63], GSM-IoT [64,65], and ZigBee [66][67][68]), that take us to places previously unexplored, allowing us to test, administrate and record the dynamics of such systems in secure and credible ways [69]. Some indicative works, that took place recently and have relevance to the current work, are listed below.…”

Section: Emerging Technologies For Smart Agriculturementioning

confidence: 99%

Latency-Adjustable Cloud/Fog Computing Architecture for Time-Sensitive Environmental Monitoring in Olive Groves

et al. 2020

View full text Add to dashboard Cite

The emerging and vast adoption of the Internet of Things (IoT) has sprung a plethora of research works regarding the potential benefits in smart agriculture. A popular implementation involves the deployment of Wireless Sensor Networks (WSNs), which embed low energy consumption sensory nodes to capture the critical environmental parameters prevailing on the farms. However, to manage the ever-increasing volumes of raw data successfully, new approaches must be explored. Under this scope, current work reports on the design and development of an IoT system, having in mind the case of olive groves, which are considered the dominant sector for agricultural activity in the Mediterranean Basin. The system incorporates the cloud/fog computing paradigm to equip the olive growers with a low-cost solution for accurate, reliable, and almost real-time monitoring of their crops. Its core is based on a three-layered network architecture, capable of dynamically balancing the generated load, by pushing cloud-elastic resources to the underlying fog network. As such, the premise of the approach lies in the conforming character of the system that allows for targeted alterations to its operational functionality to meet stringent latency and traffic load environmental monitoring constraints. To evaluate the performance of the proposed architecture, a demo prototype is developed and deployed in the facilities of the Ionian University. Experimental results illustrate the efficiency, flexibility, and scalability of the approach in terms of latency, achieving response time reduction across all platforms, a subject of the utmost importance when it comes to precision agriculture of the future. Moreover, it is shown that the system is capable of dynamic functionality adaptation, to meet network traffic load constraints, achieving high throughput (on average 95%) and addressing potential environmental dangers to olive oil production.

show abstract

“…Ergo, modern research turns to the previous ICT solutions and their seamless migration towards a multidisciplinary model [11] to support these sectors [28,44]. In fact, innovative enablers and wireless technologies (like SigFox [45], LoRa [46], NB-IoT [47], GSM-IoT [48], and ZigBee [49,50]) have empowered the involved stakeholders with the ability to experiment, manage, and record the dynamics of complex systems [51].…”

Section: Related Research In the Agricultural/environmental Monitorin...mentioning

confidence: 99%

An Alertness-Adjustable Cloud/Fog IoT Solution for Timely Environmental Monitoring Based on Wildfire Risk Forecasting

et al. 2020

View full text Add to dashboard Cite

Internet of Things (IoT) appliances, especially those realized through wireless sensor networks (WSNs), have been a dominant subject for heavy research in the environmental and agricultural sectors. To address the ever-increasing demands for real-time monitoring and sufficiently handle the growing volumes of raw data, the cloud/fog computing paradigm is deemed a highly promising solution. This paper presents a WSN-based IoT system that seamlessly integrates all aforementioned technologies, having at its core the cloud/fog hybrid network architecture. The system was intensively validated using a demo prototype in the Ionian University facilities, focusing on response time, an important metric of future smart applications. Further, the developed prototype is able to autonomously adjust its sensing behavior based on the criticality of the prevailing environmental conditions, regarding one of the most notable climate hazards, wildfires. Extensive experimentation verified its efficiency and reported on its alertness and highly conforming characteristics considering the use-case scenario of Corfu Island’s 2019 fire risk severity. In all presented cases, it is shown that through fog leveraging it is feasible to contrive significant delay reduction, with high precision and throughput, whilst controlling the energy consumption levels. Finally, a user-driven web interface is highlighted to accompany the system; it is capable of augmenting the data curation and visualization, and offering real-time wildfire risk forecasting based on Chandler’s burning index scoring.

show abstract

Smart Agriculture with an Automated IoT-Based Greenhouse System for Local Communities

Cited by 13 publications

References 11 publications

A Systematic Review of Optimal and Practical Methods in Design, Construction, Control, Energy Management and Operation of Smart Greenhouses

A Systematic Review of Optimal and Practical Methods in Design, Construction, Control, Energy Management and Operation of Smart Greenhouses

Latency-Adjustable Cloud/Fog Computing Architecture for Time-Sensitive Environmental Monitoring in Olive Groves

An Alertness-Adjustable Cloud/Fog IoT Solution for Timely Environmental Monitoring Based on Wildfire Risk Forecasting

Contact Info

Product

Resources

About