Privacy-Centric AI and IoT Solutions for Smart Rural Farm Monitoring and Control

Sensors, Год журнала: 2024, Номер 24(13), С. 4157 - 4157

Опубликована: Июнь 26, 2024

The integration of artificial intelligence (AI) and the Internet Things (IoT) in agriculture has significantly transformed rural farming. However, adoption these technologies also introduced privacy security concerns, particularly unauthorized breaches cyber-attacks on data collected from IoT devices sensitive information. present study addresses concerns by developing a comprehensive framework that provides practical, privacy-centric AI solutions for monitoring smart farms. This is performed designing includes three-phase protocol secures exchange between User, Sensor Layer, Central Server. In proposed protocol, Server responsible establishing secure communication channel verifying legitimacy User securing using rigorous cryptographic techniques. validated Automated Validation Security Protocols Applications (AVISPA) tool. formal analysis confirms robustness its suitability real-time applications IoT-enabled farms, demonstrating resistance against various attacks enhanced performance metrics, including computation time 0.04 s 11 messages detailed search where 119 nodes were visited at depth 12 plies mere 0.28 s.

Язык: Английский

---

Spatiotemporal optimization of irrigation practices for winter wheat in China: Rationale, implications, and solutions

Agricultural Water Management, Год журнала: 2025, Номер 308, С. 109297 - 109297

Опубликована: Янв. 9, 2025

Язык: Английский

---

Optimizing food crop layout considering precipitation uncertainty: Balancing regional water, carbon, and economic pressures with food security

Journal of Cleaner Production, Год журнала: 2024, Номер 467, С. 142881 - 142881

Опубликована: Июнь 17, 2024

Язык: Английский

---

Optimization of maize irrigation strategy in Xinjiang, China by AquaCrop based on a four-year study

Agricultural Water Management, Год журнала: 2024, Номер 297, С. 108816 - 108816

Опубликована: Апрель 23, 2024

Global water scarcity has become a non-negligible problem that threatens the sustainable development of agriculture. In order to alleviate contradiction between grain demand and resource constraints, it is particularly important explore appropriate irrigation strategy so as synergistically increase yield use efficiency (WUE). The AquaCrop model were locally calibrated simulate optimal amount for different hydrological years using four-year field measurements (from 2017 2020) maize with two levels (2400 m3/ha 4800 m3/ha) in Shihezi, Xinjiang, China. On this basis, regulated deficit (RDI) strategies optimized based on variation consumption soil content (SWC) during growth period. Results suggest under static (fixed proportion growing season) wet, normal, dry was 4733 m3/ha, 5381 6090 respectively. dynamic strategies, RDI4 (65% Ir (the required each interval) at R2-R5 stage) RDI5 (85% V6-V12 stage 85% can save while maintaining high yield. Under premise basically (18Mg/ha), compared year's reduce by 4.33% 2017; although slightly increased 2.77% 2018, could be 3.65%; 2019, 49.44% water, will 24.13% 2020. From study, recommended single 65% R2 R5 stages or V6 V12 (18 Mg/ha).

Язык: Английский

---

Impact of Water Management on Growth and Pigment Composition of Cauliflower and Broccoli

Plants, Год журнала: 2025, Номер 14(5), С. 725 - 725

Опубликована: Фев. 27, 2025

Global climate change minimizes fresh water resources used in agriculture worldwide. It causes drought stress, which has adverse effects on plants. To ensure food security, crops and vegetables capable of tolerating shortages over the growth period are needed. This study aimed to elucidate morphological biochemical responses three colored cauliflower (Brassica oleracea var. botrytis) cultivars (Clapton, Trevi, Di Sicilia Violetto) one broccoli cultivar italica Magic) different irrigation treatments (85–100%, 65–80%, 45–60%, 25–40% field capacity). Assessment parameters revealed no significant difference among all for root weight, leaf area, floret size. Major reduced stem weight Clapton cultivar. Additionally, under severe only Violetto had a decrease plant height, but impact number leaves was observed. The measurement pigment contents showed carotenoids cultivars; just chlorophyll decreased with moderate stress research demonstrates that likely drought-tolerant common regimes may be reviewed.

Язык: Английский

---

Preliminary Multi-Objective Optimization of Mobile Drip Irrigation System Design and Deficit Irrigation Schedule: A Full Growth Cycle Simulation for Alfalfa Using HYDRUS-2D

Water, Год журнала: 2025, Номер 17(7), С. 966 - 966

Опубликована: Март 26, 2025

Mobile drip irrigation (MDI) systems integrate the technological advantages of center-pivot (CPI) and systems, boasting a high water-saving potential. To further enhance water use efficiency in alfalfa production northern China, this preliminary study verified accuracy HYDRUS-2D soil movement numerical model through field experiments. Using model, four drip-line installation distances (60, 75, 90, 105 cm), three deficit thresholds (45–50% FC, 55–60% 65–70% FC), depths (70% W, 85% 100% 115% W) were set to simulate root uptake, surface evaporation, total amount, deep percolation during entire growth cycle alfalfa, respectively. Objective functions constructed according simulation results, NSGA-II algorithm was used for multi-objective optimization schedule. The results indicated that can accurately under MDI as RMSE values content at all measured less than 0.021 cm3/cm3, with NRMSE being below 23.3%, MAE 0.014 cm3/cm3. Increasing threshold from F1 F3 enhanced uptake by 12.24–15.34% but simultaneously increased evaporation (by up 29.58%), risk percolation; similar trends observed increasing depth. distance had no significant impact on performance. obtain Pareto-optimal solutions balance conflicting objectives. For case study, cm, 50–55% an depth 112% W recommended achieve among various This provides framework optimizing strategies. However, since deeper distribution (>80 cm) not investigated future research incorporating zones is required developing more comprehensive scheduling suitable typical cultivation scenarios.

Язык: Английский

---

Development of Mathematical and Computational Models for Predicting Agricultural Soil–Water Management Properties (ASWMPs) to Optimize Intelligent Irrigation Systems and Enhance Crop Resilience

Agronomy, Год журнала: 2025, Номер 15(4), С. 942 - 942

Опубликована: Апрель 12, 2025

Soil–water management is fundamental to plant ecophysiology, directly affecting resilience under both anthropogenic and natural stresses. Understanding Agricultural Soil–Water Management Properties (ASWMPs) therefore essential for optimizing water availability, enhancing harvest resilience, enabling informed decision-making in intelligent irrigation systems, particularly the face of climate variability soil degradation. In this regard, present research develops predictive models ASWMPs based on grain size distribution dry bulk density soils, integrating traditional mathematical approaches advanced computational techniques. By examining 900 samples from NaneSoil database, spanning diverse crop species (Avena sativa L., Daucus carota Hordeum vulgare Medicago Phaseolus vulgaris Sorghum Pers., Triticum aestivum Zea mays L.), several are proposed three key ASWMPs: soil-saturated hydraulic conductivity, field capacity, permanent wilting point. Mathematical demonstrate high accuracy (71.7–96.4%) serve as practical agronomic tools but limited capturing complex soil–plant-water interactions. Meanwhile, a Deep Neural Network (DNN)-based model significantly enhances performance (91.4–99.7% accuracy) by uncovering nonlinear relationships that govern moisture retention availability. These findings contribute precision agriculture providing robust soil–water management, ultimately supporting against environmental challenges such drought, salinization, compaction.

Язык: Английский

---

Drought stress disrupts biological nitrogen fixation and starch accumulation compromising growth and yield of cowpea plants

Plant Physiology and Biochemistry, Год журнала: 2025, Номер unknown, С. 109931 - 109931

Опубликована: Апрель 1, 2025

Язык: Английский

---

Assessing economic and hydrological effects of water-saving irrigation using a coupled SWAT–MODFLOW–AquaCrop model

Agricultural Water Management, Год журнала: 2025, Номер 314, С. 109516 - 109516

Опубликована: Май 2, 2025

Язык: Английский

---

Precision Farming for Food Security and Agricultural Land Restoration

Опубликована: Янв. 1, 2025

Язык: Английский

---