A New IoT-Based Platform for Greenhouse Crop Production

Muñoz, Manuel López; Guzmán, José Luis; Sánchez, Jorge Antonio; Rodríguez, Francisca Fuentes; Torres, Manuel; Berenguel, Manuel

doi:10.1109/jiot.2020.2996081

Cited by 34 publications

(12 citation statements)

References 17 publications

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“…Similarly, various studies have been conducted in agriculture IoT to digitalize the agricultural industry [61]. Thus, enabling the implementation of Precision Agriculture (PA) with increased financial returns, increased product quality and yield, and cost reduction [60], [62].…”

Section: E Environmental and Agriculture Iotmentioning

confidence: 99%

“…In contrast, the authors of [61] proposed the design of a cloud-based greenhouse crop production solution to provide various services for the environmental and economic benefits of agricultural operations, as well as to improve system performance by offering recommendations for the use of water, pesticides, fertilization, or energy.…”

Section: E Environmental and Agriculture Iotmentioning

confidence: 99%

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Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

et al. 2022

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The Internet of Things (IoT) has rapidly expanded for a wide range of applications towards a smart future world by connecting everything. As a result, new challenges emerge in meeting the requirements of IoT applications while retaining optimal performance. These challenges may include power consumption, quality of service, localization, security, and accurate modeling and characterization of wireless channel propagation. Among these challenges, the latter is critical to establishing point-to-point wireless communication between the sensors. Channel modeling also varies depending on the features of the surrounding area, which have a direct impact on the propagation of wireless signals. This presents a difficult task for network planners to efficiently design and deploy IoT applications without understanding the appropriate channel model to analyze coverage and predict optimal deployment configurations. As a result, this challenge has attracted considerable interest in academic and industrial communities in recent years. Therefore, this review presents an overview of current breakthroughs in wireless IoT technologies. The challenges in such applications are then briefly reviewed, focusing on wireless channel propagation modeling and characterization. Finally, the study gives a generalized form of commonly used channel models and a summary of recent channel modeling developments for wireless IoT technology. The outcome of this review is expected to provide a new understanding of the propagation behavior of present and future wireless IoT technologies, allowing network engineers to undertake correct planning and deployment in any environment. Additionally, the study may serve as a guideline for future channel modeling and characterization studies.

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Section: E Environmental and Agriculture Iotmentioning

confidence: 99%

Section: E Environmental and Agriculture Iotmentioning

confidence: 99%

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

et al. 2022

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“…By utilizing the application of IoT technology in agriculture, it is proven to increase productivity and production, harvest quality and resource efficiency. This research and development has been carried out using case studies and models as a service approach [18]- [21] real time and historical data and predictive models can be accessed via the web [22]. Firebase servers [23], one of the protocols used is LoRa which is considered sufficient to transmit small data from sensors to the cloud [24]- [26].…”

Section: A Search String Reviewmentioning

confidence: 99%

A Systematic Literature Review: Internet of Things on Smart Greenhouse

Setyawan¹,

Warsito²,

Marjunus³

et al. 2022

IJACSA

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Increasing food needs and climate instability require researchers to innovate agriculture using smart greenhouses that are integrated with the Internet of Things (IoT). The Systematic Literature Review (SLR) begins with determining the topic keywords followed by searching the publisher link. It obtains 301 publications to be reviewed, 58 of which address the research questions posed. This study aims to collect and analyze in depth various knowledge about the Internet of Things Smart Greenhouse regarding sensors, methods used and publishers who publish the most related topics and the possibility of a research gap. The findings are as many as 12 publications that use temperature and humidity sensors and use the research and development methods integrated with Artificial intelligence methods, of which 62.1% do not use the datasets and 37.9% use the datasets. It obtains two possibilities of a research gap, namely improvising the algorithm and the dataset used and placing full control on the microcontroller development board and making IoT a supporting tool.

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“… Schematic view of the modular network connectivity solution used for the data collection as described by References [ 13 ] and [ 16 ]. Picture is the courtesy of Adaptive AgroTech Consultancy International.…”

Section: Figurementioning

confidence: 99%

“…The amount of published literatures that have explored the use of IoT devices and wireless sensors in agriculture and greenhouse production is huge. One of the most recent examples includes the work of Munoz et al (2020) on the design of greenhouse production services with IoT-based cloud system incorporating historical data, current values, meteorological forecast, a weather model, a tomato production model and an irrigation model through a REST API (Representational State Transfer; Application Programming Interface) service [ 13 ]. Zamora introduced a smart farming IoT platform based on edge and cloud computing for soilless culture greenhouses.…”

Section: Introductionmentioning

confidence: 99%

IoT-Based Sensor Data Fusion for Determining Optimality Degrees of Microclimate Parameters in Commercial Greenhouse Production of Tomato

Rezvani

Abyaneh

Shamshiri

et al. 2020

Sensors

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Optimum microclimate parameters, including air temperature (T), relative humidity (RH) and vapor pressure deficit (VPD) that are uniformly distributed inside greenhouse crop production systems are essential to prevent yield loss and fruit quality. The objective of this research was to determine the spatial and temporal variations in the microclimate data of a commercial greenhouse with tomato plants located in the mid-west of Iran. For this purpose, wireless sensor data fusion was incorporated with a membership function model called Optimality Degree (OptDeg) for real-time monitoring and dynamic assessment of T, RH and VPD in different light conditions and growth stages of tomato. This approach allows growers to have a simultaneous projection of raw data into a normalized index between 0 and 1. Custom-built hardware and software based on the concept of the Internet-of-Things, including Low-Power Wide-Area Network (LoRaWAN) transmitter nodes, a multi-channel LoRaWAN gateway and a web-based data monitoring dashboard were used for data collection, data processing and monitoring. The experimental approach consisted of the collection of meteorological data from the external environment by means of a weather station and via a grid of 20 wireless sensor nodes distributed in two horizontal planes at two different heights inside the greenhouse. Offline data processing for sensors calibration and model validation was carried in multiple MATLAB Simulink blocks. Preliminary results revealed a significant deviation of the microclimate parameters from optimal growth conditions for tomato cultivation due to the inaccurate timer-based heating and cooling control systems used in the greenhouse. The mean OptDeg of T, RH and VPD were 0.67, 0.94, 0.94 in January, 0.45, 0.36, 0.42 in June and 0.44, 0.0, 0.12 in July, respectively. An in-depth analysis of data revealed that averaged OptDeg values, as well as their spatial variations in the horizontal profile were closer to the plants’ comfort zone in the cold season as compared with those in the warm season. This was attributed to the use of heating systems in the cold season and the lack of automated cooling devices in the warm season. This study confirmed the applicability of using IoT sensors for real-time model-based assessment of greenhouse microclimate on a commercial scale. The presented IoT sensor node and the Simulink model provide growers with a better insight into interpreting crop growth environment. The outcome of this research contributes to the improvement of closed-field cultivation of tomato by providing an integrated decision-making framework that explores microclimate variation at different growth stages in the production season.

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A New IoT-Based Platform for Greenhouse Crop Production

Cited by 34 publications

References 17 publications

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

A Systematic Literature Review: Internet of Things on Smart Greenhouse

IoT-Based Sensor Data Fusion for Determining Optimality Degrees of Microclimate Parameters in Commercial Greenhouse Production of Tomato

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