[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1255":3,"related-1255":106},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":6,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":23,"tags":27,"primary_topic":32,"secondary_topics":38,"classification":51,"search_phrases":86,"slug":89,"view_count":21,"doi":90,"paper":91,"created_at":105},1255,"Optimizing Water Management in Agriculture: The Role of IoT-Powered Smart Irrigation Systems in Addressing Global Food Security and Water Scarcity","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.21413238","Objective: This study aims to explore the impact of IoT-powered smart irrigation systems on optimizing water management in agriculture, with a specific focus on addressing global food security and mitigating water scarcity challenges. Materials and Methods: The research employs a mixed-methods approach, combining quantitative data analysis from agricultural case studies and qualitative interviews with farmers and agricultural experts. The study assesses the effectiveness of smart irrigation technologies, including soil moisture sensors, weather forecasting tools, and automated irrigation systems, in improving water use efficiency and crop yields. Results and Discussion: The findings indicate that IoT-powered smart irrigation systems significantly enhance water management practices in agriculture. These systems result in a reduction of up to 30% in water usage, while simultaneously increasing crop productivity by 15-20%. Additionally, the integration of real-time data analytics allows for more precise irrigation scheduling, which contributes to sustainable agricultural practices and improved food security. Conclusions: This research contributes to the existing literature by providing empirical evidence of the benefits of IoT technologies in agriculture. It highlights the potential of smart irrigation systems as a viable solution to the dual challenges of food security and water scarcity. The findings emphasize the need for policy interventions and investment in technology to facilitate the adoption of these systems in farming practices worldwide.",null,"Zenodo (CERN European Organization for Nuclear Research)","2026-08-30T00:00:00Z","论文",25,false,70,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,16,12,2,1,"论文实证智能灌溉节水30%增产20%，对农业水资源管理有参考价值，但时效性较低。",[24,25],{"name":9,"url":6},{"name":9,"url":26},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.21413237",[28,29,30,31],"智慧农业","粮食安全","智能灌溉","水资源管理",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[39,45],{"code":40,"slug":41,"name":42,"path":43,"parent_code":44},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",{"code":46,"slug":47,"name":48,"path":49,"parent_code":50},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",{"status":52,"locked":13,"version":53,"method":54,"evidence":55},"classified","2026-10-22.2","rules",{"candidates":56,"agricultural_evidence":59},[57,63,68,74,81],{"code":40,"score":58,"supported":59,"title":60,"abstract":61,"tags":62},13,true,[41],[41],[30,31],{"code":33,"score":19,"supported":59,"title":64,"abstract":66,"tags":67},[65],"food security",[65],[29],{"code":46,"score":69,"supported":59,"title":70,"abstract":72,"tags":73},11,[71],"IoT",[71],[],{"code":75,"score":76,"supported":59,"title":77,"abstract":78,"tags":80},"H2",3,[],[79],"soil",[],{"code":82,"score":21,"supported":13,"title":83,"abstract":84,"tags":85},"I1",[],[],[28],[87,88],"水资源管理 智慧农业 智能灌溉 粮食安全","水资源管理 智慧农业","水资源管理智慧农业智能灌溉粮食安全-1255","10.5281\u002Fzenodo.21413238",{"doi":90,"openalex_id":92,"authors":93,"venue":9,"cited_by_count":97,"oa_url":6,"card":98,"direction":102,"ingested_from":104},"W7169531097",[94],{"name":95,"orcid":96},"Mahdi Sabati Gavgani","https:\u002F\u002Forcid.org\u002F0000-0002-4585-9199",0,{"tldr":99,"method":100,"finding":101,"direction":102,"opportunity":103},"研究物联网智能灌溉系统优化农业用水，提升粮食安全与缓解水资源短缺。","混合方法：案例定量分析与农户专家定性访谈，评估传感器、天气预报和自动灌溉技术。","智能灌溉节水30%，增产15-20%，实时数据分析优化灌溉调度。","智慧农业 \u002F 农业物联网","可探索智能灌溉系统在不同作物、气候和农户采纳障碍下的适应性，以及政策激励对推广的影响。","openalex","2026-09-01T04:03:11.304099Z",{"total":107,"page":21,"page_size":107,"items":108},6,[109,183,272,339,396,455],{"id":110,"title":111,"url":112,"summary":113,"summary_zh":114,"content":8,"source_name":115,"source_url":112,"published_at":116,"category":11,"cover_url":8,"hotness":117,"is_selected":13,"score":118,"score_detail":119,"sources":124,"tags":126,"primary_topic":130,"secondary_topics":131,"classification":138,"search_phrases":164,"slug":167,"view_count":21,"doi":168,"paper":169,"created_at":182},5308,"Geopolitics and food security: A comprehensive review of emerging risks and responses","https:\u002F\u002Fdoi.org\u002F10.51200\u002Fjsffs.v2i2.7666","This review paper examines the relationship between geopolitics and food security through a Systematic Literature Review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. A total of 15 peer-reviewed journal articles published between 2015 and 2026 were reviewed to identify emerging geopolitical risks and responses affecting global food systems. The study synthesizes literature on armed conflicts, trade restrictions, climate change, supply chain disruptions, energy market instability, and technological transformation in agriculture. The findings identified four major themes. First, geopolitical conflicts and protectionist trade policies significantly disrupt global food supply chains and increase food price volatility. Second, climate-related shock such as droughts, floods, and extreme weather events intensifies food insecurity, particularly in import-dependent and developing economies. Third, weaknesses in global logistics and energy dependence expose food systems to external shocks and market instability. Fourth, technological innovations, including smart farming, precision agriculture, and digital monitoring systems, play an increasingly important role in strengthening agricultural productivity, improving resource efficiency, and enhancing resilience against geopolitical and environmental uncertainties. The policy implications of this study include strengthening regional food reserves, diversifying import sources, investing in climate-resilient agriculture, promoting the adoption of smart farming technologies, and enhancing institutional cooperation between governments and international organizations. The relevance of smart farming is increasingly evident, as precision agriculture, Internet of Things (IoT)-based monitoring systems, and data-driven farming technologies play a critical role in improving productivity, reducing resource inefficiency, and enhancing food system resilience under geopolitical stress. The study contributes to a broader understanding of how geopolitical dynamics shape food security and provides recommendations for building sustainable, resilient, and technology-driven food systems in an increasingly uncertain global environment.","本文通过遵循系统评价与荟萃分析首选报告条目（Preferred Reporting Items for Systematic Reviews and Meta-Analyses）框架的系统文献综述，考察地缘政治与粮食安全之间的关系。共 review 了2015年至2026年间发表的15篇同行评审期刊论文，以识别影响全球粮食系统的新兴地缘政治风险与应对措施。本研究综合了关于武装冲突、贸易限制、气候变化、供应链中断、能源市场不稳定以及农业技术转型的文献。研究结果识别出四大主题。第一，地缘政治冲突和保护主义贸易政策显著扰乱全球粮食供应链并加剧粮食价格波动。第二，干旱、洪水和极端天气事件等气候相关冲击加剧粮食不安全，尤其是在依赖进口的经济体和发展中经济体中。第三，全球物流的薄弱环节和能源依赖使粮食系统暴露于外部冲击和市场不稳定之中。第四，包括智慧农业、精准农业和数字监测系统在内的技术创新，在增强农业生产力、提高资源效率以及增强应对地缘政治和环境不确定性的韧性方面发挥着日益重要的作用。本研究的政策启示包括加强区域粮食储备、多元化进口来源、投资气候韧性农业、促进智慧农业技术的采用，以及加强政府与国际组织之间的制度合作。智慧农业的相关性日益明显，因为精准农业、基于物联网（IoT）的监测系统和数据驱动农业技术在提高生产力、减少资源低效以及增强地缘政治压力下粮食系统韧性方面发挥着关键作用。本研究有助于更广泛地理解地缘政治动态如何塑造粮食安全，并为在日益不确定的全球环境中构建可持续、有韧性且技术驱动的粮食系统提供建议。","Journal of Smart Farming and Food Security","2026-10-19T00:00:00Z",10,77,{"impact":16,"substance":120,"depth":121,"authority":58,"freshness":122,"relevant":21,"comment":123},20,17,9,"系统综述梳理地缘政治与粮食安全风险，并强调智慧农业的韧性价值，具政策与产业参考意义，但属综述性论文，非突破性成果。",[125],{"name":115,"url":112},[28,127,29,128,129],"农业供应链","精准农业","地缘政治",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[132,137],{"code":133,"slug":134,"name":135,"path":136,"parent_code":44},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",{"code":46,"slug":47,"name":48,"path":49,"parent_code":50},{"status":52,"locked":13,"version":53,"method":54,"evidence":139},{"candidates":140,"agricultural_evidence":59},[141,146,151,158],{"code":33,"score":142,"supported":59,"title":143,"abstract":144,"tags":145},15,[65],[29,65],[29],{"code":82,"score":69,"supported":59,"title":147,"abstract":148,"tags":150},[],[28,128,149],"precision agriculture",[28,128],{"code":133,"score":122,"supported":59,"title":152,"abstract":153,"tags":157},[],[154,155,156],"气候变化","干旱","climate change",[],{"code":46,"score":122,"supported":59,"title":159,"abstract":160,"tags":163},[],[161,162,71],"物联网","internet of things",[],[165,166],"地缘政治 粮食安全","智慧农业 粮食系统韧性","地缘政治粮食安全-5308","10.51200\u002Fjsffs.v2i2.7666",{"doi":168,"openalex_id":170,"authors":171,"venue":115,"cited_by_count":97,"oa_url":112,"card":177,"direction":102,"ingested_from":104},"W7222902031",[172,174],{"name":173,"orcid":8},"Parameswaran Mahendran",{"name":175,"orcid":176},"Wong Sing Yun","https:\u002F\u002Forcid.org\u002F0000-0001-5776-8852",{"tldr":178,"method":179,"finding":180,"direction":102,"opportunity":181},"系统综述地缘政治风险对粮食安全的影响及应对，强调智慧农业的韧性作用。","按PRISMA框架系统综述2015-2026年15篇同行评议文献。","冲突、贸易限制、气候与能源冲击威胁粮食安全，智慧农业可提升韧性与效率。","可量化研究物联网与精准农业在地缘政治冲击下对粮食系统韧性的实证贡献。","2026-10-19T23:30:07.850994Z",{"id":184,"title":185,"url":186,"summary":187,"summary_zh":188,"content":8,"source_name":189,"source_url":186,"published_at":190,"category":11,"cover_url":8,"hotness":117,"is_selected":13,"score":191,"score_detail":192,"sources":195,"tags":197,"primary_topic":201,"secondary_topics":202,"classification":204,"search_phrases":243,"slug":246,"view_count":97,"doi":247,"paper":248,"created_at":271},5077,"A Trust-Boundary Reference Architecture for Secure Cyber-Physical Agriculture: Design and Software-Based Proof-of-Concept for Smart Irrigation","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fs26206545","Smart irrigation is an operational technology (OT) problem as much as an Internet of Things (IoT) one: software decisions act directly on valves, pumps, pressure and water delivery, so a spoofed reading or a replayed command has physical consequences. This paper presents a technology-neutral reference architecture that makes those consequences controllable. It is organised into seven functional layers and three cross-cutting planes, six trust-boundary classes that fix which properties must be re-established at each crossing, and an auditable crown-asset inventory with an explicit trust-level rubric. Two governing execution principles enforce this structure: local safety authority, which keeps final actuation permission at the field gateway, remote terminal unit (RTU) or programmable logic controller (PLC), and feedback-aware execution, which treats a command as complete only when independent physical feedback confirms it. Building on process-aware and safety-supervision ideas from industrial control, the architecture makes physical confirmation a mandatory completion condition at the local enforcement point, which catches a fully authorised command that is nonetheless physically unsafe, a failure mode that authorisation checks alone cannot detect. These properties are examined through a deterministic, openly available software proof-of-concept that verifies the design against its own acceptance criteria; it is not a field validation. The software executes six attack and failure scenarios plus one nominal-operation control against an intentionally unsecured negative control and a secure controller, under identical, controlled conditions: the negative control is compromised in all 6 attack scenarios and the secure controller in 0\u002F6, with 0\u002F1 false positives on legitimate operation. Analytically, the design costs 21 bytes and 50–60% additional Long Range Wide Area Network (LoRaWAN) time-on-air per record, and 78% of single-step perturbations of the trust-scoring inputs leave asset classification unchanged: the actuator class (A2) is completely stable, and the gateway\u002FRTU\u002FPLC class (A3) is stable under 6 of 7 admissible perturbations (86%), changing only when its credential\u002Fupdate authority reaches the trust-anchor threshold. A sensor-level mapping from sampling rate, measurement drift and physical fault modes to the edge-verification controls they dictate, provisions for secure time, counter recovery and the choice between fail-closed and fail-open safe states, an illustrative hypothetical worked deployment example, and a transfer of the model to greenhouse, fertigation, livestock-watering and cold-chain settings show how the architecture could be applied in practice.","智能灌溉既是一个物联网(IoT)问题，也是一个运营技术(OT)问题：软件决策直接作用于阀门、水泵、压力和水流输送，因此被欺骗的读数或被重放的命令会产生物理后果。本文提出了一种技术中立的参考架构，使这些后果可控。该架构由七个功能层和三个横切面、六类信任边界(规定每次跨越边界时必须重新建立哪些属性)，以及一份可审计的核心资产清单(配有明确的信任等级评定标准)组成。两条主导性执行原则保障了这一结构：本地安全授权，即将最终执行许可保留在田间网关、远程终端单元(RTU)或可编程逻辑控制器(PLC)处；以及反馈感知执行，即只有当独立的物理反馈予以确认时，才将命令视为完成。该架构以工业控制中的过程感知和安全监督思想为基础，将物理确认设为本地执行点的强制性完成条件，从而能够捕获完全获得授权但在物理上仍不安全的命令——这是仅靠授权检查无法检测到的失效模式。这些特性通过一个确定性、公开可用的软件概念验证进行了检验，该验证依据其自身的验收标准对设计进行评估；这不是现场验证。该软件在相同且受控的条件下，针对一个故意不设防护的阴性对照和一个安全控制器，执行了六种攻击与故障场景以及一项标称运行对照：阴性对照在所有6种攻击场景中均被攻破，而安全控制器为0\u002F6，对合法运行的误报为0\u002F1。分析表明，该设计每条记录额外增加21字节和50–60%的LoRaWAN(LoRaWAN)空中时间，且信任评分输入的78%单步扰动不会改变资产分类：执行器类(A2)完全稳定，网关\u002FRTU\u002FPLC类(A3)在7种可允许扰动中有6种保持稳定(86%)，仅当其凭证\u002F更新权限达到信任锚阈值时才会改变。还提出了从采样率、测量漂移和物理故障模式到其所决定的边缘验证控制的传感器级映射，以及安全时间、计数器恢复和故障关闭与故障打开安全状态之间选择的保障措施。","Sensors","2026-10-15T00:00:00Z",75,{"impact":19,"substance":17,"depth":16,"authority":193,"freshness":122,"relevant":21,"comment":194},14,"面向智慧灌溉的信任边界参考架构论文，方法新颖、含软件验证与量化开销数据，但属概念验证、非田间实证，产业影响有限，可作为技术前沿精选。",[196],{"name":189,"url":186},[198,28,199,30,200],"数字乡村","农业物联网","网络安全",{"code":40,"slug":41,"name":42,"path":43,"parent_code":44},[203],{"code":46,"slug":47,"name":48,"path":49,"parent_code":50},{"status":52,"locked":13,"version":53,"method":54,"evidence":205},{"candidates":206,"agricultural_evidence":59},[207,212,216,222,228,234,239],{"code":40,"score":142,"supported":59,"title":208,"abstract":209,"tags":211},[41],[210,41],"灌溉",[30],{"code":46,"score":117,"supported":59,"title":213,"abstract":214,"tags":215},[],[161,162,71],[199],{"code":217,"score":76,"supported":59,"title":218,"abstract":219,"tags":221},"B7",[],[220],"greenhouse",[],{"code":223,"score":76,"supported":59,"title":224,"abstract":225,"tags":227},"C",[],[226],"livestock",[],{"code":229,"score":76,"supported":59,"title":230,"abstract":231,"tags":233},"F3",[],[232],"fertigation",[],{"code":235,"score":20,"supported":13,"title":236,"abstract":237,"tags":238},"I6",[],[],[198,200],{"code":82,"score":21,"supported":13,"title":240,"abstract":241,"tags":242},[],[],[28],[244,245],"智能灌溉 信任边界 参考架构","LoRaWAN 灌溉 安全","智能灌溉信任边界参考架构-5077","10.3390\u002Fs26206545",{"doi":247,"openalex_id":249,"authors":250,"venue":189,"cited_by_count":97,"oa_url":186,"card":266,"direction":102,"ingested_from":104},"W7222165876",[251,254,257,260,263],{"name":252,"orcid":253},"Alvertos Ioannis Mourikis","https:\u002F\u002Forcid.org\u002F0009-0009-2386-2803",{"name":255,"orcid":256},"Iosif Polenakis","https:\u002F\u002Forcid.org\u002F0000-0002-6427-5519",{"name":258,"orcid":259},"Christos Sarantidis","https:\u002F\u002Forcid.org\u002F0009-0003-9486-8483",{"name":261,"orcid":262},"Romanos Kalamatianos","https:\u002F\u002Forcid.org\u002F0009-0000-6939-5424",{"name":264,"orcid":265},"Ioannis Karydis","https:\u002F\u002Forcid.org\u002F0000-0002-9470-2729",{"tldr":267,"method":268,"finding":269,"direction":102,"opportunity":270},"提出面向智慧灌溉的安全参考架构，用软件验证可抵御重放与欺骗攻击。","七层三面参考架构、信任边界分类、确定性软件概念验证与LoRaWAN开销分析。","安全控制器在6种攻击场景下0次被攻破，负控制全部被攻破，且误报率为0。","可研究边缘验证控制与采样率、漂移、故障模式的映射，以及安全时间与失效安全状态选择。","2026-10-16T23:30:08.098924Z",{"id":273,"title":274,"url":275,"summary":276,"summary_zh":277,"content":8,"source_name":278,"source_url":275,"published_at":279,"category":11,"cover_url":8,"hotness":117,"is_selected":13,"score":280,"score_detail":281,"sources":284,"tags":286,"primary_topic":290,"secondary_topics":291,"classification":293,"search_phrases":315,"slug":318,"view_count":97,"doi":319,"paper":320,"created_at":338},4888,"A MATLAB-based AI-IoT simulation framework for LSTM-driven smart solar irrigation and renewable energy management","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-74935-0","Smart irrigation offers a great avenue for better water use efficiency, and farming sustainability. However, most of the studies conducted so far tend to concentrate on the monitoring systems and platforms of the Internet of Things (IoT) or on the prediction models based on Artificial Intelligence (AI) (but not on both). To address this gap, this research study proposes an Artificial Intelligence (AI)-Internet of Things (IoT) system to predict the water consumption requirements and control the energy produced by a PV system along with a battery State of Charge (SOC) management system, Maximum Power Point Tracking (MPPT) algorithm, adaptive pump-speed control, and conceptual IoT communication architecture. A dataset of real environmental data from the NASA POWER database was used to test the framework for Egypt’s New Delta region. The LSTM model was able to classify the irrigation pump operating states with an accuracy of 96.11%, a recall of 0.9820, a precision of 0.9100, and an F1-score of 0.9446. It had a better performance than the two models, Artificial Neural Network (ANN) and Support Vector Machine (SVM) when compared and robustness testing with various independent training runs showed a stable performance in predicting. An estimated annual water-saving rate of 28.57% was obtained relative to the assumed conventional fixed-schedule baseline, while motor energy use was reduced by 74.74% through adaptive pump-speed control. A sensitivity analysis was also performed, showing that the model was stable to moderate variations in environmental and operating conditions. Combined, these findings suggest that the use of AI-based modelling for renewable energy management in the context of an irrigation simulation model built in MATLAB could be a valuable asset in improving irrigation efficiency and lowering water and energy use, which is a promising start for future implementation of hardware versions of intelligent, solar-powered irrigation devices.","智能灌溉为提高用水效率和农业可持续性提供了重要途径。然而，迄今为止大多数研究倾向于集中在物联网（IoT）的监测系统和平台，或基于人工智能（AI）的预测模型（但很少两者兼顾）。为弥补这一空白，本研究提出了一种人工智能（AI）-物联网（IoT）系统，用于预测用水需求并控制光伏系统产生的能量，同时包含电池荷电状态（SOC）管理系统、最大功率点跟踪（MPPT）算法、自适应泵速控制以及概念性物联网通信架构。研究采用NASA POWER数据库中的真实环境数据集，在埃及新三角洲地区对该框架进行了测试。LSTM模型能够对灌溉泵运行状态进行分类，准确率达到96.11%，召回率为0.9820，精确率为0.9100，F1分数为0.9446。与人工神经网络（ANN）和支持向量机（SVM）两个模型相比，该模型表现更优，且通过多次独立训练运行进行的鲁棒性测试表明其在预测方面具有稳定性能。相对于假设的传统固定调度基线，估计年节水率为28.57%，而通过自适应泵速控制，电机能耗降低了74.74%。研究还进行了敏感性分析，表明该模型对环境和运行条件的中等程度变化具有稳定性。综合来看，这些发现表明，在MATLAB中构建的灌溉仿真模型背景下，将基于AI的建模用于可再生能源管理，可能是提高灌溉效率、降低水和能源消耗的有价值手段，这为未来实现智能太阳能灌溉设备的硬件版本提供了一个有前景的开端。","Scientific Reports","2026-10-12T00:00:00Z",78,{"impact":18,"substance":17,"depth":16,"authority":193,"freshness":282,"relevant":21,"comment":283},8,"该研究提出AI-IoT融合的太阳能灌溉仿真框架，LSTM预测精度达96.11%，节水28.57%、节能74.74%，方法新颖且数据可靠，对智慧农业与农业能源管理有参考价值。",[285],{"name":278,"url":275},[28,287,30,288,289],"农业人工智能","节水农业","光伏农业",{"code":46,"slug":47,"name":48,"path":49,"parent_code":50},[292],{"code":40,"slug":41,"name":42,"path":43,"parent_code":44},{"status":52,"locked":13,"version":53,"method":54,"evidence":294},{"candidates":295,"agricultural_evidence":59},[296,300,304,311],{"code":46,"score":121,"supported":59,"title":297,"abstract":298,"tags":299},[71],[161,162,71],[],{"code":40,"score":18,"supported":59,"title":301,"abstract":302,"tags":303},[41],[210,41],[30,288],{"code":305,"score":306,"supported":59,"title":307,"abstract":308,"tags":310},"I2",4,[],[309],"artificial intelligence",[287],{"code":82,"score":21,"supported":13,"title":312,"abstract":313,"tags":314},[],[],[28],[316,317],"MATLAB AI-IoT 太阳能灌溉","LSTM 智能灌溉 埃及新三角洲","MATLABAI-IoT太阳能灌溉-4888","10.1038\u002Fs41598-026-74935-0",{"doi":319,"openalex_id":321,"authors":322,"venue":278,"cited_by_count":97,"oa_url":332,"card":333,"direction":102,"ingested_from":104},"W7221571268",[323,326,329],{"name":324,"orcid":325},"Ahmed Mashaly","https:\u002F\u002Forcid.org\u002F0009-0007-7009-4531",{"name":327,"orcid":328},"Ragab Abdelaziz El-Sehiemy","https:\u002F\u002Forcid.org\u002F0000-0002-3340-4031",{"name":330,"orcid":331},"Mohamed M. Elgohary","https:\u002F\u002Forcid.org\u002F0000-0003-4441-7812","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-74935-0.pdf",{"tldr":334,"method":335,"finding":336,"direction":102,"opportunity":337},"提出MATLAB中AI-IoT仿真框架，用LSTM预测灌溉需水并管理光伏与电池。","NASA POWER环境数据，LSTM对比ANN\u002FSVM，含MPPT与自适应泵速","LSTM分类准确率96.11%，节水28.57%，电机能耗降74.74%。","可延伸至真实硬件部署与多区域验证，并融合实时气象与土壤墒情数据。","2026-10-14T23:30:13.060384Z",{"id":340,"title":341,"url":342,"summary":343,"summary_zh":344,"content":8,"source_name":345,"source_url":342,"published_at":346,"category":11,"cover_url":8,"hotness":117,"is_selected":13,"score":347,"score_detail":348,"sources":350,"tags":352,"primary_topic":354,"secondary_topics":355,"classification":357,"search_phrases":378,"slug":381,"view_count":21,"doi":382,"paper":383,"created_at":395},4296,"Smart Irrigation System for Precision Farming","https:\u002F\u002Fdoi.org\u002F10.17148\u002Fijarcce.2026.151010","Smart Irrigation System for Precision Farming is anIoT-based and sensor-driven approach designed to improve water management, crop productivity, and agricultural sustainability.Conventional irrigation practices often depend on fixed schedules or manual decisions, which can result in over-irrigation, under-irrigation, water wastage, and increased labour requirements.The proposed system integrates soil-moisture, temperature, humidity, and rainfall sensors with a microcontroller such as Arduino or ESP32 to continuously monitor field conditions in real time.Based on the collected data, the system automatically determines the irrigation requirement and controls water pumps or solenoid valves accordingly.Weather information can also be incorporated to avoid unnecessary irrigation during expected rainfall and to adapt watering according to environmental conditions.IoT connectivity enables farmers to remotely monitor soil and weather parameters through a web or mobile dashboard.The system provides a low-cost, scalable, and farmer-friendly solution that supports precision agriculture by delivering the right amount of water at the right time.Such intelligent irrigation can conserve water and energy, reduce manual effort, improve crop health, and contribute to sustainable agricultural development. IJARCCE","基于物联网和传感器的精准农业智能灌溉系统，旨在改善水资源管理、作物生产力和农业可持续性。传统灌溉方式往往依赖固定时间表或人工决策，可能导致过度灌溉、灌溉不足、水资源浪费以及劳动力需求增加。所提出的系统将土壤湿度、温度、湿度和降雨传感器与Arduino或ESP32等微控制器集成，以实时持续监测田间状况。基于采集的数据，系统自动判断灌溉需求，并相应控制水泵或电磁阀。系统还可纳入天气信息，以避免在预计降雨期间进行不必要的灌溉，并根据环境条件调整浇水。物联网连接使农民能够通过网络或移动仪表板远程监测土壤和天气参数。该系统提供了一种低成本、可扩展且对农民友好的解决方案，通过在恰当的时间提供恰当的水量来支持精准农业。这种智能灌溉能够节约水和能源、减少人工劳动、改善作物健康，并促进农业可持续发展。IJARCCE","IJARCCE","2026-10-05T00:00:00Z",49,{"impact":282,"substance":193,"depth":58,"authority":107,"freshness":282,"relevant":21,"comment":349},"面向精准农业的物联网智能灌溉系统论文，方法常规、缺乏大规模实测数据，属细分领域技术进展，公共价值有限。",[351],{"name":345,"url":342},[28,161,30,128,353],"传感器",{"code":40,"slug":41,"name":42,"path":43,"parent_code":44},[356],{"code":46,"slug":47,"name":48,"path":49,"parent_code":50},{"status":52,"locked":13,"version":53,"method":54,"evidence":358},{"candidates":359,"agricultural_evidence":59},[360,365,369,373],{"code":40,"score":16,"supported":59,"title":361,"abstract":362,"tags":364},[41],[210,363,41],"水资源",[30],{"code":82,"score":282,"supported":59,"title":366,"abstract":367,"tags":368},[],[128,149],[28,128],{"code":46,"score":282,"supported":59,"title":370,"abstract":371,"tags":372},[],[161,71],[353,161],{"code":75,"score":107,"supported":59,"title":374,"abstract":375,"tags":377},[],[376,79],"土壤",[],[379,380],"智能灌溉系统 精准农业","物联网 土壤湿度传感器 灌溉","智能灌溉系统精准农业-4296","10.17148\u002Fijarcce.2026.151010",{"doi":382,"openalex_id":384,"authors":385,"venue":345,"cited_by_count":97,"oa_url":342,"card":390,"direction":102,"ingested_from":104},"W7220437851",[386,388],{"name":387,"orcid":8},"Mr. Bhagyesh N Chaudhari",{"name":389,"orcid":8},"Dr. Dinesh D Puri",{"tldr":391,"method":392,"finding":393,"direction":102,"opportunity":394},"基于物联网与传感器构建智能灌溉系统，实时监测土壤与气象并自动控制灌溉。","用Arduino\u002FESP32连接土壤湿度、温湿度、降雨传感器及物联网仪表盘。","系统可按需精准供水，节水节能、减少人工并提升作物健康与可持续性。","可延伸至多源数据融合的灌溉决策优化、边缘智能控制及大田规模化验证。","2026-10-06T23:30:07.841226Z",{"id":397,"title":398,"url":399,"summary":400,"summary_zh":401,"content":8,"source_name":402,"source_url":399,"published_at":403,"category":11,"cover_url":8,"hotness":117,"is_selected":13,"score":404,"score_detail":405,"sources":407,"tags":409,"primary_topic":412,"secondary_topics":413,"classification":415,"search_phrases":430,"slug":433,"view_count":21,"doi":434,"paper":435,"created_at":454},3332,"Solar-powered irrigation adoption in South Asia: opportunities, challenges, and policy implications","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1892056","Solar irrigation technologies offer potential sustainable and cost-effective solutions, though their environmental sustainability depends critically on institutional and regulatory frameworks to address social and environmental challenges in regions with vast solar and agricultural potential such as south Asia. This review paper evaluates (1) technological innovations, (2) opportunities and fundamental challenges and policy frameworks, and (3) socio-economic, and environment impacts on south Asia countries including Bangladesh, India, Nepal, and Pakistan. The review results indicated that solar irrigation systems demonstrated advantage in reducing operational costs compared to diesel alternatives and contributed significantly to carbon abatement. In addition, these systems provided consistent water supply independent of erratic grid power and compatible with irrigation systems for efficiency. Surplus electricity generated by solar irrigation systems can be sold back to the grid, increasing farmer income. Reliable water access can drive a transition from subsistence farming to cash crop cultivation. However, solar irrigation system’s performance is weather-dependent and without energy storage, they cannot support nighttime irrigation. When integrated with battery storage and advanced technologies such as the Internet of Things (IoT), these systems can provide irrigation during non-sunlight hours while enabling efficient, automated water management that optimizes water use and enhances crop productivity. This review highlighted key research gaps, including the need for long-term climate-informed modeling of solar irrigation systems, empirical hydrological studies of institutional models, and deeper analysis of tenancy and gender dynamics. Addressing these gaps improves solar irrigation by enabling more accurate water-resource planning under future climate conditions, strengthening institutional and groundwater management, and ensuring more equitable access for user. In conclusion, solar irrigation in South Asia should be seen as a sustainability tool that balances technological expansion with water conservation and social equity.","太阳能灌溉技术提供了潜在的可持续且具有成本效益的解决方案，但其环境可持续性在很大程度上取决于制度和监管框架，以应对南亚等太阳能与农业潜力巨大地区所面临的社会和环境挑战。本文综述评估了（1）技术创新，（2）机遇、根本性挑战与政策框架，以及（3）对孟加拉国、印度、尼泊尔和巴基斯坦等南亚国家的社会经济和环境影响。综述结果表明，太阳能灌溉系统在降低运行成本方面相较于柴油替代方案具有优势，并对碳减排有显著贡献。此外，这些系统提供了不依赖不稳定电网电力的稳定供水，并与灌溉系统兼容以提高效率。太阳能灌溉系统产生的盈余电力可回售给电网，增加农民收入。可靠的水源获取可以推动从自给农业向经济作物种植的转变。然而，太阳能灌溉系统的性能受天气影响，且在没有储能的情况下，无法支持夜间灌溉。当与电池储能和物联网（IoT）等先进技术集成时，这些系统可以在非日照时段提供灌溉，同时实现高效、自动化的水资源管理，从而优化用水并提高作物生产力。本综述指出了关键研究空白，包括需要对太阳能灌溉系统进行长期气候信息建模、对制度模式进行实证水文研究，以及对租佃和性别动态进行更深入分析。弥补这些空白可以改进太阳能灌溉，具体途径包括：在未来气候条件下实现更准确的水资源规划，加强制度和地下水管理，并确保用户更公平地获取水资源。总之，南亚的太阳能灌溉应被视为一种可持续性工具，在技术扩展与水资源保护和社会公平之间取得平衡。","Frontiers in Sustainable Food Systems","2026-09-23T00:00:00Z",80,{"impact":16,"substance":17,"depth":16,"authority":193,"freshness":282,"relevant":21,"comment":406},"系统综述南亚四国光伏灌溉的技术、政策与社会环境效应，指出物联网与储能结合方向及研究空白，对农业信息化与智慧灌溉有参考价值。",[408],{"name":402,"url":399},[28,199,31,410,411],"光伏灌溉","南亚农业",{"code":40,"slug":41,"name":42,"path":43,"parent_code":44},[414],{"code":46,"slug":47,"name":48,"path":49,"parent_code":50},{"status":52,"locked":13,"version":53,"method":54,"evidence":416},{"candidates":417,"agricultural_evidence":59},[418,422,426],{"code":40,"score":16,"supported":59,"title":419,"abstract":420,"tags":421},[41],[210,363,41],[31],{"code":46,"score":117,"supported":59,"title":423,"abstract":424,"tags":425},[],[161,162,71],[199],{"code":82,"score":21,"supported":13,"title":427,"abstract":428,"tags":429},[],[],[28],[431,432],"南亚 光伏灌溉","农业物联网 水资源管理 光伏灌溉 南亚农业","南亚光伏灌溉-3332","10.3389\u002Ffsufs.2026.1892056",{"doi":434,"openalex_id":436,"authors":437,"venue":402,"cited_by_count":97,"oa_url":399,"card":448,"direction":452,"ingested_from":104},"W7214072186",[438,441,443,446],{"name":439,"orcid":440},"Younsuk Dong","https:\u002F\u002Forcid.org\u002F0000-0003-2400-1916",{"name":442,"orcid":8},"Heesun Jang",{"name":444,"orcid":445},"Najme Yazdanpanah","https:\u002F\u002Forcid.org\u002F0000-0003-2554-7005",{"name":447,"orcid":8},"Yadu Pokhrel",{"tldr":449,"method":450,"finding":451,"direction":452,"opportunity":453},"综述南亚太阳能灌溉的技术、政策与社会环境影响，指出其可持续性取决于制度与监管框架。","文献综述，覆盖孟加拉国、印度、尼泊尔、巴基斯坦的技术、政策与影响分析。","太阳能灌溉降低运营成本并助力碳减排，但依赖天气，需储能与物联网支持夜间灌溉。","农业绿色发展与碳","可开展气候情景下太阳能灌溉的长期水文建模，并研究租佃与性别差异对公平获取的影响。","2026-09-24T23:30:07.037091Z",{"id":456,"title":457,"url":458,"summary":459,"summary_zh":460,"content":8,"source_name":461,"source_url":458,"published_at":462,"category":11,"cover_url":8,"hotness":117,"is_selected":13,"score":463,"score_detail":464,"sources":466,"tags":468,"primary_topic":470,"secondary_topics":471,"classification":476,"search_phrases":502,"slug":505,"view_count":506,"doi":507,"paper":508,"created_at":522},3158,"Internet of things-based smart irrigation system using soil moisture and weather data","https:\u002F\u002Fdoi.org\u002F10.12928\u002Ftelkomnika.v24i5.27889","Water wastage in agriculture remains a significant challenge due to irrigation practices that often rely on fixed schedules rather than actual field conditions. This study presents an internet of things (IoT)-based smart irrigation system designed to improve water-use efficiency through real-time monitoring and automated irrigation control. The system integrates a capacitive soil moisture sensor with weather information obtained from an online application programming interface (API), while all data processing is performed locally on a Raspberry Pi edge device. A rule-based decision mechanism is used to classify soil conditions into dry, optimal, and wet categories and to determine appropriate irrigation actions based on soil moisture levels and rainfall forecasts. The system was implemented using low-cost and readily available components and tested under controlled conditions with soil moisture levels ranging from approximately 0% to above 85%. Experimental results showed consistent classification of critical dry, optimal, and critical wet conditions, enabling appropriate irrigation responses under different scenarios. In addition, email notifications were generated only during critical conditions, while no alerts were triggered under optimal moisture levels, demonstrating stable and reliable operation. The proposed system provides a practical and cost-effective solution for supporting efficient irrigation management and sustainable agricultural practices.","农业中的水资源浪费仍然是一项重大挑战，因为灌溉实践往往依赖固定时间表，而非实际田间条件。本研究提出了一种基于物联网（IoT）的智能灌溉系统，旨在通过实时监测和自动灌溉控制来提高用水效率。该系统将电容式土壤湿度传感器与从在线应用程序编程接口（API）获取的天气信息相结合，同时所有数据处理均在Raspberry Pi边缘设备上本地完成。系统采用基于规则的决策机制，将土壤状况分为干燥、适宜和湿润三类，并根据土壤湿度水平和降雨预报确定适当的灌溉措施。该系统使用低成本和易于获取的组件实现，并在受控条件下进行了测试，土壤湿度水平范围约为0%至85%以上。实验结果表明，系统能够一致地分类临界干燥、适宜和临界湿润状况，从而在不同情景下实现适当的灌溉响应。此外，电子邮件通知仅在临界状况下生成，而在适宜湿度水平下未触发任何警报，表明系统运行稳定可靠。所提出的系统为支持高效灌溉管理和可持续农业实践提供了一种实用且具有成本效益的解决方案。","TELKOMNIKA (Telecommunication Computing Electronics and Control)","2026-09-21T00:00:00Z",58,{"impact":282,"substance":18,"depth":193,"authority":19,"freshness":282,"relevant":21,"comment":465},"低成本物联网智能灌溉系统，方法清晰、结论可靠，对节水农业有实用参考价值，但属常规技术验证类论文，影响范围有限。",[467],{"name":461,"url":458},[28,161,30,469,288],"土壤墒情",{"code":40,"slug":41,"name":42,"path":43,"parent_code":44},[472,473],{"code":46,"slug":47,"name":48,"path":49,"parent_code":50},{"code":75,"slug":79,"name":474,"path":475,"parent_code":44},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"status":52,"locked":13,"version":53,"method":54,"evidence":477},{"candidates":478,"agricultural_evidence":59},[479,484,488,492,498],{"code":40,"score":480,"supported":59,"title":481,"abstract":482,"tags":483},19,[41],[210,363,41],[30,288],{"code":46,"score":16,"supported":59,"title":485,"abstract":486,"tags":487},[162],[161,162,71],[161],{"code":75,"score":142,"supported":59,"title":489,"abstract":490,"tags":491},[79],[376,79],[469],{"code":493,"score":76,"supported":59,"title":494,"abstract":495,"tags":497},"H8",[],[496],"可持续农业",[],{"code":82,"score":21,"supported":13,"title":499,"abstract":500,"tags":501},[],[],[28],[503,504],"IoT 智能灌溉 土壤湿度","Raspberry Pi 边缘计算 灌溉","IoT智能灌溉土壤湿度-3158",5,"10.12928\u002Ftelkomnika.v24i5.27889",{"doi":507,"openalex_id":509,"authors":510,"venue":461,"cited_by_count":97,"oa_url":458,"card":517,"direction":102,"ingested_from":104},"W7213907872",[511,513,515],{"name":512,"orcid":8},"Zakarie Abdi Mohamud",{"name":514,"orcid":8},"Rozeha Binti A. Rashid",{"name":516,"orcid":8},"Yazid Abubakar Sufyan",{"tldr":518,"method":519,"finding":520,"direction":102,"opportunity":521},"基于物联网与土壤湿度及天气数据，实现低成本自动灌溉决策系统。","电容式土壤湿度传感器、天气API、Raspberry Pi边缘计算与规则决策。","系统能准确分类干、适宜、湿状态，仅在临界条件触发灌溉与邮件通知。","可引入机器学习预测土壤湿度动态，优化规则阈值并扩展至多作物多区域验证。","2026-09-22T23:30:10.956765Z"]