[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2154":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"view_count":32,"doi":33,"paper":34,"created_at":63},2154,"Ambient RF energy harvesting using voltage doubler rectifier for battery-free agricultural sensor networks: Design, statistical analysis, and machine learning validation","https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0350236","The growing adoption of precision agriculture requires sustainable power sources for wireless sensor networks (WSNs) deployed in remote and resource-constrained environments. Conventional battery-powered systems are constrained by limited-service life, maintenance requirements, and environmental concerns. This study presents the design, experimental validation, statistical evaluation, and machine learning (ML)-based modeling of an ambient radio-frequency (RF) energy harvesting system for agricultural monitoring applications. The proposed system harvests RF energy from AM\u002FFM broadcasting (558 kHz–108 MHz) and cellular communication bands (800–2100 MHz) using a frequency-selective broadband antenna, an integrated diplexer, switchable L-section impedance-matching networks, and a Villard voltage-doubler rectifier based on low forward-voltage OA79 germanium diodes. Experimental measurements from 30 independent repeated trials yielded a mean open-circuit output voltage of 4.07 ± 0.08 V (95% CI: 4.04–4.10 V) and a loaded output voltage of 2.11 ± 0.11 V, corresponding to a harvested power of approximately 44.5 μW across a 100 kΩ load. One-way analysis of variance (ANOVA) demonstrated significant differences among diode types (F (2,87) = 687.4, p \u003C 0.001), while Tukey’s post hoc test confirmed the superior performance of OA79 diodes compared with 1N4148 and 1N5819 alternatives. Among the evaluated ML models, Gradient Boosting regression achieved the highest predictive accuracy, with R² = 0.963 and RMSE = 0.071 V. SHapley Additive exPlanations (SHAP) analysis identified diode forward voltage and ambient RF power density as the most influential factors affecting output voltage prediction. The results indicate the potential applicability of ambient multi-band RF energy harvesting as a supplementary energy source for low-power agricultural sensing applications operating under duty-cycled conditions. By combining broadband energy harvesting, statistical validation, and predictive modeling, the proposed framework establishes a systematic methodology for evaluating self-powered agricultural IoT systems operating under variable RF environments.","精准农业的日益普及，对部署在偏远且资源受限环境中的无线传感器网络（WSN）提出了可持续供电的需求。传统电池供电系统受限于使用寿命有限、维护需求以及环境问题。本研究介绍了一种面向农业监测应用的环境射频（RF）能量收集系统的设计、实验验证、统计评估以及基于机器学习（ML）的建模。所提出的系统利用频率选择性宽带天线、集成双工器、可切换L型阻抗匹配网络以及基于低正向电压OA79锗二极管的Villard倍压整流器，从AM\u002FFM广播频段（558 kHz–108 MHz）和蜂窝通信频段（800–2100 MHz）收集射频能量。来自30次独立重复试验的实验测量结果得出，平均开路输出电压为4.07 ± 0.08 V（95% CI：4.04–4.10 V），负载输出电压为2.11 ± 0.11 V，对应在100 kΩ负载上收集的功率约为44.5 μW。单因素方差分析（ANOVA）表明，不同二极管类型之间存在显著差异（F (2,87) = 687.4，p \u003C 0.001），而Tukey事后检验证实，与1N4148和1N5819替代方案相比，OA79二极管具有更优越的性能。在评估的机器学习模型中，梯度提升回归取得了最高的预测精度，R² = 0.963，RMSE = 0.071 V。SHapley加性解释（SHAP）分析确定，二极管正向电压和环境射频功率密度是影响输出电压预测的最重要因素。结果表明，环境多频段射频能量收集作为在占空比条件下运行的低功耗农业传感应用的补充能源，具有潜在适用性。通过将宽带能量收集、统计验证和预测建模相结合，所提出的框架建立了一种系统化方法，用于评估在多变射频环境下运行的自供电农业物联网系统。",null,"PLoS ONE","2026-09-10T00:00:00Z","论文",10,false,71,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,21,17,13,8,1,"面向无电池农业传感网络的射频能量采集研究，方法完整、统计与机器学习验证扎实，但属实验室原型阶段，产业影响有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"智慧农业","农业人工智能","农业物联网","无线传感器网络","能量采集",0,"10.1371\u002Fjournal.pone.0350236",{"doi":33,"openalex_id":35,"authors":36,"venue":10,"cited_by_count":32,"oa_url":6,"card":56,"direction":60,"ingested_from":62},"W7212168596",[37,39,41,43,45,47,49,51,54],{"name":38,"orcid":9},"Md. Atik Hasan Nishat",{"name":40,"orcid":9},"Prithwiraj Biswas Pallab",{"name":42,"orcid":9},"Nowrin Jannat",{"name":44,"orcid":9},"Saleha Nasrin Mishu",{"name":46,"orcid":9},"Md Fahad Ullah Utsho",{"name":48,"orcid":9},"Md. Bipul Islam",{"name":50,"orcid":9},"Riaz Uddin Mondal",{"name":52,"orcid":53},"Md. Firoz Ahmed","https:\u002F\u002Forcid.org\u002F0000-0003-2721-0596",{"name":55,"orcid":9},"M. Hasnat Kabir",{"tldr":57,"method":58,"finding":59,"direction":60,"opportunity":61},"设计多频段环境RF能量收集系统，为无电池农业传感器网络供电并验证。","Villard倍压整流器、宽带天线、ANOVA统计与梯度提升\u002FSHAP机器学习建","OA79锗二极管性能最优，输出约44.5μW，梯度提升预测R²达0.963。","智慧农业 \u002F 农业物联网","可探索多源环境能量混合收集与自适应功率管理，提升农业物联网节点长期自持能力。","openalex","2026-09-11T23:30:16.081985Z"]