Greenhouse monitoring using WSN and SENSEnuts nodes

Lata, Suman; Sah, Ramesh Kumar; Singh, Shashank; Jaiswal, Saurabh

doi:10.1063/5.0031711

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…Srbinovska et al investigated battery lifetime by managing periodical transmitting time. They used WSN for the greenhouse [13], [14], [15]. Simultaneously, Philipose and Rajesh applied WSN to the railway system.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Energy Consumption in Sensor Node Based on Received Signal Strength Indicator (Rssi) and Sleep Awake Method

Rudati,

Feriyonika,

Sudarsa

et al. 2023

AEJ

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The transmission power management in Wireless Sensor Networks (WSN) is a critical problem. This research investigated optimizing power consumption based on transmission power (Tx Power) level according to RSSI and periodic transmission time. We investigated the RSSI value by varying Tx Power Level to get the optimum Tx Power Level. We found the optimum periodic transmission time by transmitting the data with various transmission times. By varying the Tx Power Level, we found the optimum Tx Power Level, resulting in the power consumption decreasing by about 42% and the power supply’s lifetime increasing by about 71% in the 280 m distance between the sensor node and gateway, with a 108 Wh power supply. By varying the periodic transmission time, we found that the optimum periodic transmission time is 8 seconds. Combining the optimum Tx Power Level and periodic transmission time, we found that the power supply’s lifetime is 40 times longer. This result is helpful for WSN applications in remote areas.

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Section: Introductionmentioning

confidence: 99%

Optimization of Energy Consumption in Sensor Node Based on Received Signal Strength Indicator (Rssi) and Sleep Awake Method

Rudati,

Feriyonika,

Sudarsa

et al. 2023

AEJ

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Selection of Number and Locations of Multi-Sensor Nodes Inside Greenhouse

Lata¹,

Verma²

2022

JST

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One of the possible solutions for meeting the rising food demands is to opt for wireless sensor networks (WSN) monitored intelligent greenhouses. Such greenhouses require wireless sensor nodes rather than individual sensors to monitor and control the various parameters responsible for the growth of the plants. The appropriate selection of the number of wireless sensor nodes and their placement is crucial for optimizing the cost of the wireless sensor network by minimizing the number of sensor nodes as well as the measurement error. This paper extends the two techniques, namely, equal step (ES) and equal segment area (ESA) techniques, reported earlier for the selection of the number and locations of sensors to suit multi-sensor nodes inside a greenhouse. It also compares these techniques with the equal-spacing approach. The multi-sensor nodes considered here have temperature and luminosity sensors. Initial locations of the multi-sensor nodes have been fixed on the basis of temperature profile on the premise that temperature is the most important parameter for the growth of the plants. Evaluation of these techniques has been done on the basis of the root of the sum of square errors (RSSE) of the individual parameters. The ESA technique has been found to be better than the ES technique for the assumed temperature and luminosity profiles. In the future, this work may be extended to other situations where other than temperature is the most important parameter. The other direction in which the work can be extended may be considering the 2D or even 3D distribution of sensors.

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Monitoring Experiment of Melon Greenhouse’s Environment in Tropical Climate

Wongwatcharapaiboon,

Likitswat,

Sudprasert

et al. 2024

BUILT

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Greenhouses in tropical climates are designed to control passively the environment, protecting plants from pest and extreme climate condition, which is increasingly important due to climate change. This research aims to monitor a melon greenhouse's environment in a tropical climate to understand light intensity, pollutants, and climate conditions. Indoor and outdoor conditions of melon greenhouse were real-time monitored by Vantage VUE model, DAVIS weather station, PM2.5 meter and noise meter. The findings examined that peak light intensities were recorded at 135,600 lux outdoors and 32,050 lux indoors at noon, with an average light transmittance of 38%. Additionally, PM2.5 levels remained stable around 26-30 µg/m³, and sound levels decreased from 60 dB in the morning to 45 dB. These pollution levels did not disturb farmer and indoor melon in winter season. However, other seasoning period needs to be monitored for long term adaptation of application and climate change mitigation. These research findings will support greenhouse design for human comfort and plant growth, considering and optimizing temperature and humidity conditions. IoTs mechanisms and devices were proposed high costly potential for monitoring sensor, networking process, comparative and reliable data collection for further next step of greenhouse integration. Lastly, upcycled transparent roof from LDPE were suggested to be continually used with minor development or plug-in devices for increasing light shade during the mid-daytime.

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Greenhouse monitoring using WSN and SENSEnuts nodes

Cited by 3 publications

References 6 publications

Optimization of Energy Consumption in Sensor Node Based on Received Signal Strength Indicator (Rssi) and Sleep Awake Method

Optimization of Energy Consumption in Sensor Node Based on Received Signal Strength Indicator (Rssi) and Sleep Awake Method

Selection of Number and Locations of Multi-Sensor Nodes Inside Greenhouse

Monitoring Experiment of Melon Greenhouse’s Environment in Tropical Climate

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