Automated cloud-edge cyber-physical IoT infrastructure for optimizing the agricultural water-energy nexus and yield
Abstract
Global agriculture faces increasing challenges associated with water scarcity and the growing demand for energy-efficient irrigation management. This study developed and evaluated an integrated three-layer cloud-edge cyber-physical Internet of Things (IoT) infrastructure based on an ESP32 microcontroller and ThingSpeak–MATLAB cloud analytics to support automated irrigation management and real-time agricultural monitoring. The system was implemented during four phenological growth stages of sweet pepper ( Capsicum annuum L. , cv. Rocky F1) using a factorial combination of four soil-moisture thresholds (60, 75, 90, and 100% of field capacity) and four biochar application rates (2.5, 5.0, 7.5, and 10.0%, w/w). The developed platform enabled continuous acquisition and cloud-based processing of environmental, irrigation, and electrical data while automatically executing the prescribed irrigation treatments. During a controlled proof-of-concept evaluation, the cloud-based alert system successfully detected all five predefined fault events, with a mean email notification latency of 3.06 s after the alert routine was initiated. Factorial analysis demonstrated significant effects of soil-moisture threshold, biochar application rate, and their interaction on crop yield, net irrigation requirement, water-use efficiency, operating current, power consumption, and cumulative electrical energy consumption. Response surface methodology (RSM) was employed to characterize the response behavior of the investigated variables, whereas the recommended operating condition (75% field capacity combined with 7.5% biochar) was established through an integrated evaluation of the experimental findings by jointly considering statistical significance together with crop yield, net irrigation requirement, water-use efficiency, and electrical energy performance. A techno-economic assessment documented the experimental-scale capital investment required to implement the developed IoT infrastructure. The developed cloud-edge cyber-physical framework provides an integrated platform for automated irrigation management, real-time monitoring, and data-driven evaluation of water, energy, and crop-production performance under the investigated experimental conditions.
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BibTeX
@article{badr2026automated,
title = {{Automated cloud-edge cyber-physical IoT infrastructure for optimizing the agricultural water-energy nexus and yield}},
author = {M. M. Badr and M. A. Noor},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-71352-1},
url = {https://www.nature.com/articles/s41598-026-71352-1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Automated cloud-edge cyber-physical IoT infrastructure for optimizing the agricultural water-energy nexus and yield
AU - M. M. Badr
AU - M. A. Noor
PY - 2026
DA - 2026/10/07
JO - Scientific Reports
DO - 10.1038/s41598-026-71352-1
UR - https://www.nature.com/articles/s41598-026-71352-1
AB - Global agriculture faces increasing challenges associated with water scarcity and the growing demand for energy-efficient irrigation management. This study developed and evaluated an integrated three-layer cloud-edge cyber-physical Internet of Things (IoT) infrastructure based on an ESP32 microcontroller and ThingSpeak–MATLAB cloud analytics to support automated irrigation management and real-time agricultural monitoring. The system was implemented during four phenological growth stages of sweet pepper ( Capsicum annuum L. , cv. Rocky F1) using a factorial combination of four soil-moisture thresholds (60, 75, 90, and 100% of field capacity) and four biochar application rates (2.5, 5.0, 7.5, and 10.0%, w/w). The developed platform enabled continuous acquisition and cloud-based processing of environmental, irrigation, and electrical data while automatically executing the prescribed irrigation treatments. During a controlled proof-of-concept evaluation, the cloud-based alert system successfully detected all five predefined fault events, with a mean email notification latency of 3.06 s after the alert routine was initiated. Factorial analysis demonstrated significant effects of soil-moisture threshold, biochar application rate, and their interaction on crop yield, net irrigation requirement, water-use efficiency, operating current, power consumption, and cumulative electrical energy consumption. Response surface methodology (RSM) was employed to characterize the response behavior of the investigated variables, whereas the recommended operating condition (75% field capacity combined with 7.5% biochar) was established through an integrated evaluation of the experimental findings by jointly considering statistical significance together with crop yield, net irrigation requirement, water-use efficiency, and electrical energy performance. A techno-economic assessment documented the experimental-scale capital investment required to implement the developed IoT infrastructure. The developed cloud-edge cyber-physical framework provides an integrated platform for automated irrigation management, real-time monitoring, and data-driven evaluation of water, energy, and crop-production performance under the investigated experimental conditions.
SN - 2045-2322
ER -