Smart reference evapotranspiration using Internet of Things and hybrid ensemble machine learning approach

Bashir, Rab Nawaz; Saeed, Mahlaqa; Al-Sarem, Mohammed; Marie, Rashiq; Faheem, Muhammad; Karrar, Abdelrahman Elsharif; Elhussein, Bahaeldein

doi:10.1016/j.iot.2023.100962

Cited by 8 publications

(1 citation statement)

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“…Researchers in Brazil [38] developed an IoT system to monitor reference evapotranspiration (ETo) using a weighing lysimeter. Researchers in Pakistan [39] used derived reference evapotranspiration (ETo), combining machine learning with weather data collected with an IoT system. Researchers in India [30] developed an IoT system for monitoring a micro-lysimeter for a greenhouse application.…”

Section: Introductionmentioning

confidence: 99%

An Effective and Affordable Internet of Things (IoT) Scale System to Measure Crop Water Use

Payero

2024

AgriEngineering

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Scales are widely used in many agricultural applications, ranging from weighing crops at harvest to determine crop yields to regularly weighing animals to determine growth rate. In agricultural research applications, there is a long history of measuring crop water use (evapotranspiration [ET]) using a particular type of scale called weighing lysimeters. Typically, weighing lysimeters require very accurate data logging systems that tend to be expensive. Recent developments in open-source technologies, such as micro-controllers and Internet of Things (IoT) platforms, have created opportunities for developing effective and affordable ways to monitor crop water use and transmit the data to the Internet in near real-time. Therefore, this study aimed to create an affordable Internet of Things (IoT) scale system to measure crop ET. A scale system to monitor crop ET was developed using an Arduino-compatible microcontroller with cell phone communication, electronic load cells, an Inter-Integrated Circuit (I2C) multiplexer, and analog-to-digital converters (ADCs). The system was powered by a LiPo battery, charged by a small (6 W) solar panel. The IoT scale system was programmed to collect data from the load cells at regular time intervals and send the data to the ThingSpeak IoT platform. The system performed successfully during indoor and outdoor experiments conducted in 2023 at the Clemson University Edisto Research and Education Center, Blackville, SC. Calibrations relating the measured output of the scale load cells to changes in mass resulted in excellent linear relationships during the indoor (r2 = 1.0) and outdoor experiments (r2 = 0.9994). The results of the outdoor experiments showed that the IoT scale system could accurately measure changes in lysimeter mass during several months (Feb to Jun) without failure in data collection or transmission. The changes in lysimeter mass measured during that period reflected the same trend as concurrent soil moisture data measured at a nearby weather station. The changes in lysimeter mass measured with the IoT scale system during the outdoor experiment were accurate enough to derive daily and hourly crop ET and even detect what appeared to be dew formation during the morning hours. The IoT scale system can be built using open-source, off-the-shelf electronic components which can be purchased online and easily replaced or substituted. The system can also be developed at a fraction of the cost of data logging, communication, and visualization systems typically used for lysimeter and scale applications.

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Section: Introductionmentioning

confidence: 99%