[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2779":3,"related-2779":105},{"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,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":80,"slug":83,"view_count":22,"doi":84,"paper":85,"created_at":104},2779,"INFORMATION AND COMMUNICATION TECHNOLOGIES IN THE MANAGEMENT OF RISKS IN FAMILY AGRICULTURE: A SYSTEMATIC REVIEW OF THE LITERATURE","https:\u002F\u002Fdoi.org\u002F10.23900\u002Fartefactum.v25i9.4236","Family farming is relevant to food production, income generation and sustainable development, but it remains exposed to climatic, production, economic and operational risks. In this context, Information and Communication Technologies (ICTs) provide resources for monitoring, automation and decision support. This study analyzes the contributions of ICTs to risk management in family farming through a Systematic Literature Review conducted according to PRISMA 2020. Searches were carried out in Google Scholar, SciELO, the CAPES Periodicals Portal and the Brazilian Digital Library of Theses and Dissertations, considering publications from 2018 to 2026. After applying the inclusion and exclusion criteria, 14 studies composed the review corpus. The results indicate that the Internet of Things, sensors, automated systems and digital platforms contribute to monitoring, risk prevention, productive efficiency and sustainability. Limitations related to infrastructure, rural connectivity, implementation costs and farmer training persist. It is concluded that ICTs are strategic instruments for risk management in family farming, although integrated models combining innovation, cooperation, monitoring and decision support are still needed.","家庭农业与粮食生产、收入创造和可持续发展密切相关，但仍面临气候、生产、经济和经营风险。在此背景下，信息与通信技术（ICTs）为监测、自动化和决策支持提供了资源。本研究通过依据PRISMA 2020开展的系统性文献综述，分析ICTs对家庭农业风险管理的贡献。检索在Google Scholar、SciELO、CAPES期刊门户和巴西数字论文与学位论文图书馆中进行，考虑2018年至2026年的出版物。在应用纳入和排除标准后，14项研究构成了综述语料库。结果表明，物联网、传感器、自动化系统和数字平台有助于监测、风险预防、生产效率提升和可持续发展。与基础设施、农村连通性、实施成本和农民培训相关的局限仍然存在。结论认为，ICTs是家庭农业风险管理的战略性工具，尽管仍需要结合创新、合作、监测和决策支持的整合模式。",null,"Artefactum","2026-09-17T00:00:00Z","论文",10,false,62,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,18,15,8,9,1,"系统综述梳理物联网、传感器与数字平台在家庭农业风险管理中的作用，结论与局限清晰，但样本仅14篇且来源为行业平台，属细分领域参考性成果。",[25],{"name":10,"url":6},[27,28,29,30,31],"数字乡村","智慧农业","农业物联网","家庭农场","农业风险管理",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,53,60,65,70,75],{"code":33,"score":46,"supported":47,"title":48,"abstract":49,"tags":52},7,true,[],[50,51],"物联网","internet of things",[29],{"code":54,"score":55,"supported":47,"title":56,"abstract":57,"tags":59},"I2",3,[],[58],"decision support",[],{"code":61,"score":22,"supported":14,"title":62,"abstract":63,"tags":64},"G2",[],[],[30],{"code":66,"score":22,"supported":14,"title":67,"abstract":68,"tags":69},"G3",[],[],[31],{"code":71,"score":22,"supported":14,"title":72,"abstract":73,"tags":74},"I1",[],[],[28],{"code":76,"score":22,"supported":14,"title":77,"abstract":78,"tags":79},"I6",[],[],[27],[81,82],"农业风险管理 农业物联网 家庭农场 数字乡村","农业风险管理 农业物联网","农业风险管理农业物联网家庭农场数字乡村-2779","10.23900\u002Fartefactum.v25i9.4236",{"doi":84,"openalex_id":86,"authors":87,"venue":10,"cited_by_count":95,"oa_url":6,"card":96,"direction":102,"ingested_from":103},"W7213473081",[88,91,93],{"name":89,"orcid":90},"Vilson Gruber","https:\u002F\u002Forcid.org\u002F0000-0003-4092-8578",{"name":92,"orcid":9},"Samantha Ferreira da Silva",{"name":94,"orcid":9},"Dairce Londero",0,{"tldr":97,"method":98,"finding":99,"direction":100,"opportunity":101},"系统综述2018-2026年ICT在家庭农业风险管理中的贡献与局限。","PRISMA 2020系统文献综述，检索4个数据库，纳入14篇研究。","物联网、传感器与数字平台助力监测、风险预防与效率，但基础设施、连通性、成本与培训仍是瓶颈。","数字乡村与农业信息化","可研究面向小农户的低成本、低连通依赖的集成式风险监测与决策支持模型。","智慧农业 \u002F 农业物联网","openalex","2026-09-17T23:30:20.104369Z",{"total":106,"page":22,"page_size":106,"items":107},6,[108,203,285,356,409,479],{"id":109,"title":110,"url":111,"summary":112,"summary_zh":113,"content":9,"source_name":114,"source_url":111,"published_at":115,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":116,"score_detail":117,"sources":121,"tags":123,"primary_topic":126,"secondary_topics":132,"classification":134,"search_phrases":174,"slug":177,"view_count":95,"doi":178,"paper":179,"created_at":202},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":17,"substance":118,"depth":18,"authority":119,"freshness":21,"relevant":22,"comment":120},22,14,"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。",[122],{"name":114,"url":111},[27,28,29,124,125],"智能灌溉","网络安全",{"code":127,"slug":128,"name":129,"path":130,"parent_code":131},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[133],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":135},{"candidates":136,"agricultural_evidence":47},[137,142,147,153,159,165,170],{"code":127,"score":19,"supported":47,"title":138,"abstract":139,"tags":141},[128],[140,128],"灌溉",[124],{"code":33,"score":13,"supported":47,"title":143,"abstract":144,"tags":146},[],[50,51,145],"IoT",[29],{"code":148,"score":55,"supported":47,"title":149,"abstract":150,"tags":152},"B7",[],[151],"greenhouse",[],{"code":154,"score":55,"supported":47,"title":155,"abstract":156,"tags":158},"C",[],[157],"livestock",[],{"code":160,"score":55,"supported":47,"title":161,"abstract":162,"tags":164},"F3",[],[163],"fertigation",[],{"code":76,"score":166,"supported":14,"title":167,"abstract":168,"tags":169},2,[],[],[27,125],{"code":71,"score":22,"supported":14,"title":171,"abstract":172,"tags":173},[],[],[28],[175,176],"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":178,"openalex_id":180,"authors":181,"venue":114,"cited_by_count":95,"oa_url":111,"card":197,"direction":102,"ingested_from":103},"W7222165876",[182,185,188,191,194],{"name":183,"orcid":184},"Alvertos Ioannis Mourikis","https:\u002F\u002Forcid.org\u002F0009-0009-2386-2803",{"name":186,"orcid":187},"Iosif Polenakis","https:\u002F\u002Forcid.org\u002F0000-0002-6427-5519",{"name":189,"orcid":190},"Christos Sarantidis","https:\u002F\u002Forcid.org\u002F0009-0003-9486-8483",{"name":192,"orcid":193},"Romanos Kalamatianos","https:\u002F\u002Forcid.org\u002F0009-0000-6939-5424",{"name":195,"orcid":196},"Ioannis Karydis","https:\u002F\u002Forcid.org\u002F0000-0002-9470-2729",{"tldr":198,"method":199,"finding":200,"direction":102,"opportunity":201},"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":204,"title":205,"url":206,"summary":207,"summary_zh":208,"content":9,"source_name":209,"source_url":206,"published_at":210,"category":12,"cover_url":9,"hotness":211,"is_selected":14,"score":212,"score_detail":213,"sources":217,"tags":221,"primary_topic":225,"secondary_topics":226,"classification":227,"search_phrases":269,"slug":272,"view_count":166,"doi":273,"paper":274,"created_at":284},2312,"MridAI: Autonomous Edge-to-Conversational IoT for Democratising Precision Agriculture via Neuro-Symbolic Telemetry","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22724805","While sensor-guided precision agriculture improves water efficiency and curtails chemical run-off, adoption across smallholder farm land in the Global South remains under 1%. Commercial telemetry systems are constrained by high capital acquisition costs (>$300) and complex, dashboard-centric mobile applications that impose heavy cognitive burdens on low-literacy farmers. This paper proposes MridAI, a low-cost (\u003C$45 \u002F ₹3,420 COGS) autonomous in-ground agro-telemetry node coupled with a cloud-based neuro-symbolic artificial intelligence advisory pipeline. The physical layer integrates a multi-parameter Modbus RS485 sensor, an ESP32-C3 micro-controller, an Indian-band 4G LTE Cat-1 modem, and an energy harvesting subsystem within an IP67-rated solar stem. To eliminate measurement errors in high-clay tropical soils (Vertisols), an on-device digital signal-processing pipeline applies an adapted Topp dielectric correction alongside a one-dimensional discrete Kalman filter. To overcome rural telecommunication instability, the firmware implements an asynchronous, non-volatile store-and-forward ring buffer. At the cloud layer, an analytical solver calculates deterministic FAO-56 evapotranspiration deficits and enforces Indian Council of Agricultural Research (ICAR) chemical boundaries, strictly isolating numerical computation from an instruction-tuned Large Language Model (LLM). The generative model functions solely as a linguistic translator, delivering actionable, dialect-adapted recommendations directly via the Meta WhatsApp Cloud API without requiring third-party application downloads. Empirical power-budget modelling confirms indefinite operational autonomy (>240 days without solar irradiance), establishing a scalable paradigm for digital agriculture.","尽管传感器引导的精准农业提高了用水效率并减少了化学品径流，但在全球南方小农农田中的采用率仍不足1%。商业遥测系统受制于高昂的资本购置成本（超过300美元）以及复杂的、以仪表盘为中心的移动应用程序，后者给低识字率农民带来了沉重的认知负担。本文提出MridAI，一种低成本（物料清单成本低于45美元\u002F3，420印度卢比）的自主地下农业遥测节点，并耦合基于云的神经符号人工智能咨询流水线。物理层将多参数Modbus RS485传感器、ESP32-C3微控制器、印度频段4G LTE Cat-1调制解调器以及能量收集子系统集成于IP67防护等级的太阳能杆体内。为消除高黏土热带土壤（变性土）中的测量误差，设备端数字信号处理流水线采用适配的Topp介电校正与一维离散卡尔曼滤波器。为克服农村电信不稳定性，固件实现了异步、非易失性的存储转发环形缓冲区。在云层，分析求解器计算确定性的FAO-56蒸散亏缺，并执行印度农业研究理事会（ICAR）的化学品边界，将数值计算与指令微调的大语言模型（LLM）严格隔离。生成模型仅充当语言翻译器，通过Meta WhatsApp Cloud API直接提供可操作的、适配方言的建议，无需下载第三方应用程序。实证功率预算建模证实了无限期运行自主性（无太阳辐照下超过240天），为数字农业建立了一种可扩展的范式。","Zenodo (CERN European Organization for Nuclear Research)","2026-09-12T00:00:00Z",25,85,{"impact":118,"substance":214,"depth":18,"authority":215,"freshness":21,"relevant":22,"comment":216},23,13,"面向全球南方小农户的低成本自主土壤遥测节点与神经符号AI咨询管线，方法新颖、成本与能耗数据具体，对农业信息化与普惠数字农业有实质参考价值。",[218,219],{"name":209,"url":206},{"name":209,"url":220},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22724804",[27,28,222,29,223,224],"农业人工智能","小农户","精准灌溉",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":228},{"candidates":229,"agricultural_evidence":47},[230,238,242,248,254,259,265],{"code":71,"score":18,"supported":47,"title":231,"abstract":233,"tags":237},[232],"precision agriculture",[234,235,232,236],"精准农业","数字农业","digital agriculture",[28],{"code":33,"score":21,"supported":47,"title":239,"abstract":240,"tags":241},[145],[],[29],{"code":54,"score":46,"supported":47,"title":243,"abstract":244,"tags":247},[],[245,246],"artificial intelligence","large language model",[222],{"code":61,"score":249,"supported":47,"title":250,"abstract":251,"tags":253},4,[],[252],"smallholder",[223],{"code":127,"score":249,"supported":47,"title":255,"abstract":256,"tags":258},[],[257],"evapotranspiration",[224],{"code":260,"score":55,"supported":47,"title":261,"abstract":262,"tags":264},"H2",[],[263],"土壤",[],{"code":76,"score":22,"supported":14,"title":266,"abstract":267,"tags":268},[],[],[27],[270,271],"农业人工智能 农业物联网 数字乡村 智慧农业","农业人工智能 农业物联网","农业人工智能农业物联网数字乡村智慧农业-2312","10.5281\u002Fzenodo.22724805",{"doi":273,"openalex_id":275,"authors":276,"venue":209,"cited_by_count":95,"oa_url":206,"card":279,"direction":102,"ingested_from":103},"W7212357737",[277],{"name":278,"orcid":9},"Pranit Kamble",{"tldr":280,"method":281,"finding":282,"direction":102,"opportunity":283},"提出低成本自主地下物联网节点与神经符号AI咨询管道，让小农户用WhatsApp获取精准农业建议。","ESP32-C3与Modbus传感器、Topp校正和卡尔曼滤波、FAO-56与L","系统成本低于45美元，可独立运行超240天，无需下载应用即可通过WhatsApp获得方言化建议。","可探索低资源语言与方言适配的LLM农业咨询，以及神经符号系统在更多作物和土壤类型中的泛化验证。","2026-09-13T23:30:14.323767Z",{"id":286,"title":287,"url":288,"summary":289,"summary_zh":290,"content":9,"source_name":291,"source_url":288,"published_at":292,"category":12,"cover_url":9,"hotness":293,"is_selected":14,"score":294,"score_detail":295,"sources":299,"tags":305,"primary_topic":309,"secondary_topics":310,"classification":311,"search_phrases":340,"slug":343,"view_count":166,"doi":344,"paper":345,"created_at":355},2139,"Connecting the Canopy: C-Band and Ku-Band Satellite Technologies for Sustainable Oil Palm Plantation Management in Indonesia—A Review","https:\u002F\u002Fdoi.org\u002F10.47191\u002Fetj\u002Fv11i09.06","Indonesia's oil palm plantations are increasingly expected to combine high productivity with environmental protection, traceability, worker welfare, and smallholder inclusion. Achieving these objectives requires reliable digital connectivity across plantation landscapes that are frequently extensive, remote, and inadequately served by terrestrial telecommunications. This qualitative literature review examines the characteristics of C-band and Ku-band satellite technologies and critically explores their roles in supporting sustainable oil palm plantation management in Indonesia. Drawing on interdisciplinary literature published since 2020 covering satellite communications, Internet of Things, smart agriculture, remote sensing, oil palm agronomy, and sustainability governance, the review develops a socio-technical synthesis rather than a systematic or meta-analytic assessment. C-band generally provides stronger resilience to tropical rain attenuation and is attractive for fixed, availability-critical backbone connectivity, whereas Ku-band enables smaller terminals, greater deployment flexibility, and practical broadband access but requires more deliberate rain-fade mitigation. Neither band is intrinsically superior, and actual performance depends on link design, service architecture, traffic requirements, cost, and local conditions. The review identifies applications in environmental surveillance, precision agronomy, disease detection, harvesting, logistics, traceability, worker safety, and sustainability assurance. It proposes an Observe–Connect–Decide–Act–Verify framework and a hybrid connectivity architecture integrating field networks, satellite backhaul, terrestrial networks, edge computing, remote sensing, and analytics. Sustainable benefits ultimately depend not merely on connectivity but on inclusive governance, institutional capacity, appropriate agronomic action, and mechanisms preventing digitalization from reinforcing existing inequalities.","印度尼西亚的油棕种植园日益被期望将高生产力与环境保护、可追溯性、工人福利和小农包容性结合起来。实现这些目标需要在种植园景观中建立可靠的数字连接，而这些景观往往面积广阔、地处偏远，且地面电信服务不足。本定性文献综述考察了C波段和Ku波段卫星技术的特征，并批判性地探讨了它们在支持印度尼西亚可持续油棕种植园管理中的作用。综述借鉴了2020年以来发表的多学科文献，涵盖卫星通信、物联网、智慧农业、遥感、油棕农学和可持续性治理，构建了一种社会技术综合，而非系统性或元分析评估。C波段通常对热带降雨衰减具有更强的抵御能力，适用于固定的、可用性至关重要的骨干连接；而Ku波段则支持更小的终端、更大的部署灵活性和实用的宽带接入，但需要更有针对性的雨衰缓解措施。两者并无本质上的优劣之分，实际性能取决于链路设计、服务架构、流量需求、成本和当地条件。综述识别了其在环境监测、精准农艺、病害检测、收获、物流、可追溯性、工人安全和可持续性保障方面的应用。它提出了一个“观察—连接—决策—行动—验证”框架，以及一种混合连接架构，整合田间网络、卫星回传、地面网络、边缘计算、遥感和分析。可持续效益最终不仅取决于连接性，还取决于包容性治理、机构能力、适当的农艺行动，以及防止数字化加剧现有不平等的机制。","Engineering and Technology Journal","2026-09-10T00:00:00Z",40,76,{"impact":18,"substance":296,"depth":297,"authority":215,"freshness":20,"relevant":22,"comment":298},20,17,"综述系统梳理C波段与Ku波段卫星通信在印尼油棕可持续种植中的应用，提出“观测—连接—决策—行动—验证”框架与混合组网架构，对热带经济作物产区的农业信息化建设具有参考价值，但属文献综述、非原始数据研究，且地域局限于印尼。",[300,301,303],{"name":291,"url":288},{"name":291,"url":302},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22689903",{"name":291,"url":304},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22689902",[27,28,29,306,307,308],"遥感监测","卫星通信","油棕种植",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":312},{"candidates":313,"agricultural_evidence":47},[314,320,325,332,336],{"code":33,"score":13,"supported":47,"title":315,"abstract":316,"tags":319},[],[50,317,51,318],"边缘计算","edge computing",[29],{"code":71,"score":46,"supported":47,"title":321,"abstract":322,"tags":324},[],[28,323],"smart agriculture",[28],{"code":326,"score":46,"supported":47,"title":327,"abstract":328,"tags":331},"I3",[],[329,330],"遥感","remote sensing",[306],{"code":61,"score":55,"supported":47,"title":333,"abstract":334,"tags":335},[],[252],[],{"code":76,"score":22,"supported":14,"title":337,"abstract":338,"tags":339},[],[],[27],[341,342],"农业物联网 卫星通信 数字乡村 智慧农业","农业物联网 卫星通信","农业物联网卫星通信数字乡村智慧农业-2139","10.47191\u002Fetj\u002Fv11i09.06",{"doi":344,"openalex_id":346,"authors":347,"venue":291,"cited_by_count":95,"oa_url":288,"card":350,"direction":102,"ingested_from":103},"W7212110357",[348],{"name":349,"orcid":9},"Loso Judijanto",{"tldr":351,"method":352,"finding":353,"direction":102,"opportunity":354},"综述C波段与Ku波段卫星技术在印尼油棕可持续种植管理中的应用与选择。","2020年以来跨学科文献定性综述，提出社会技术综合框架。","两波段无绝对优劣，性能取决于链路设计、成本与本地条件，可持续性更依赖治理。","可实证比较C\u002FKu波段在热带雨林衰减下的物联网回传性能，并评估小农户数字包容机制。","2026-09-11T23:30:10.114685Z",{"id":357,"title":358,"url":359,"summary":360,"summary_zh":361,"content":9,"source_name":209,"source_url":359,"published_at":362,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":363,"score_detail":364,"sources":366,"tags":368,"primary_topic":370,"secondary_topics":371,"classification":372,"search_phrases":393,"slug":396,"view_count":95,"doi":397,"paper":398,"created_at":408},5554,"Smart Agriculture using IoT","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23531185","The Smart Agriculture Using IoT system uses different sensors installed in the agricultural field to collect data about soil and environmental conditions. The collected data is sent to a microcontroller, such as an ESP32 or Arduino with a suitable communication module. When the soil moisture level becomes lower than the required level, the system can automatically switch on the water pump. When sufficient moisture is detected, the pump switches off. Farmers can also monitor field conditions through a mobile application or web dashboard. This system reduces manual work and helps farmers use water and other resources efficiently.","基于物联网的智慧农业系统利用安装在农田中的各类传感器采集土壤与环境状况数据。采集到的数据被传送至微控制器，如ESP32或配备合适通信模块的Arduino。当土壤湿度低于所需水平时，系统可自动开启水泵；当检测到湿度充足时，水泵则关闭。农民还可通过移动应用程序或网页仪表盘监测田间状况。该系统减少了人工劳作，帮助农民高效利用水资源及其他资源。","2026-10-21T00:00:00Z",49,{"impact":20,"substance":17,"depth":13,"authority":21,"freshness":13,"relevant":22,"comment":365},"论文介绍基于ESP32\u002FArduino的土壤湿度自动灌溉与远程监测方案，属常规技术实现，方法新颖性有限，但主题贴合智慧农业且时效性强，可作为一般资讯收录。",[367],{"name":209,"url":359},[28,29,124,369],"土壤墒情",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":373},{"candidates":374,"agricultural_evidence":47},[375,379,383,388],{"code":71,"score":19,"supported":47,"title":376,"abstract":377,"tags":378},[323],[28,323],[28],{"code":33,"score":19,"supported":47,"title":380,"abstract":381,"tags":382},[145],[50,145],[29],{"code":260,"score":46,"supported":47,"title":384,"abstract":385,"tags":387},[],[263,386],"soil",[369],{"code":127,"score":249,"supported":47,"title":389,"abstract":390,"tags":392},[],[391],"水资源",[124],[394,395],"ESP32 土壤湿度 自动灌溉","农业物联网 移动端监测","ESP32土壤湿度自动灌溉-5554","10.5281\u002Fzenodo.23531185",{"doi":397,"openalex_id":399,"authors":400,"venue":209,"cited_by_count":95,"oa_url":359,"card":403,"direction":102,"ingested_from":103},"W7223137846",[401],{"name":402,"orcid":9},"Prachi Khairnar",{"tldr":404,"method":405,"finding":406,"direction":102,"opportunity":407},"基于物联网传感器实现农田土壤湿度自动监测与灌溉控制。","部署土壤与环境传感器，经ESP32\u002FArduino采集数据并联动水泵。","系统可自动启停水泵并通过手机或网页端远程监控，节水省工。","可引入多源传感融合与预测性灌溉决策，弥补仅靠阈值控制的局限。","2026-10-22T11:20:18.299106Z",{"id":410,"title":411,"url":412,"summary":413,"summary_zh":414,"content":9,"source_name":209,"source_url":412,"published_at":415,"category":12,"cover_url":9,"hotness":211,"is_selected":14,"score":416,"score_detail":417,"sources":420,"tags":424,"primary_topic":426,"secondary_topics":427,"classification":429,"search_phrases":457,"slug":460,"view_count":95,"doi":461,"paper":462,"created_at":478},5474,"Real-World Impact: Transforming Agriculture with Technology A Multi-Stakeholder Review of Smart Monitoring, Precision Irrigation, and Digital Value-Chain Integration","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23510500","There's a deliberate and significant transition from input to information. This article combines peer-reviewed evidence and public-sector data on six interrelated technology clusters that are fundamentally changing on-farm and off-farm decision making artificial intelligence (AI) based Farm Management Platforms, Internet of Things (IoT) smart irrigation, aerial and satellite crop monitoring, blockchain-enabled supply-chain digitisation, sustainability and carbon-tracking instruments, and farm data analytics dashboards. In the literature examined, precision tools have been correlated with 15% to 30% gains in crop yields, 30% to 55% of water saved during irrigation, and 10% to 20% of operational costs reduced, all with a range of variability based on the crop, the geographical region, and the size of the farm. It examines the mechanisms of these effects on the one hand and the differential rates of benefit, on the other, between large commercial farms and smallholders, and the policy and infrastructural conditions that drive actual adoption. It also highlights areas of current evidence which are lacking, such as limited long horizon field trials, poor interoperability standards, and lack of social outcome data. The article ends with a discussion on how to turn pilots into lasting, system-level change in food production, both from the government and enterprise side, as well as from the perspective of small and medium producers.","从投入要素到信息的转变是有意为之且意义重大的。本文结合经同行评审的证据与公共部门数据，聚焦六个相互关联、正在从根本上改变农场内外决策方式的技术集群：基于人工智能（AI）的农场管理平台、物联网（IoT）智能灌溉、航空与卫星作物监测、区块链赋能的供应链数字化、可持续性与碳追踪工具，以及农场数据分析仪表盘。在所考察的文献中，精准工具与作物产量提升15%至30%、灌溉用水节约30%至55%、运营成本降低10%至20%相关联，且这些效果因作物、地理区域和农场规模而存在不同程度的差异。本文一方面考察这些效应的作用机制，另一方面分析大型商业农场与小农户之间受益程度的差异，以及驱动实际采用的政策与基础设施条件。文章还指出了当前证据的薄弱之处，如缺乏长期田间试验、互操作性标准不完善以及社会成效数据缺失。文章最后讨论了如何从政府与企业两侧，以及中小生产者视角出发，将试点项目转化为粮食生产中持久、系统层面的变革。","2026-11-25T00:00:00Z",73,{"impact":118,"substance":418,"depth":297,"authority":215,"freshness":95,"relevant":22,"comment":419},21,"多利益相关方综述整合六类技术集群的量化效益与采纳差异，信息增量足、产业参考价值高，但发布于一个月后，时效性不足，暂不宜进入每日精选。",[421,422],{"name":209,"url":412},{"name":209,"url":423},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23527988",[28,222,29,425,224],"区块链溯源",{"code":127,"slug":128,"name":129,"path":130,"parent_code":131},[428],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":430},{"candidates":431,"agricultural_evidence":47},[432,436,440,444,448,453],{"code":127,"score":19,"supported":47,"title":433,"abstract":434,"tags":435},[128],[140,128],[224],{"code":33,"score":13,"supported":47,"title":437,"abstract":438,"tags":439},[],[50,51,145],[29],{"code":54,"score":249,"supported":47,"title":441,"abstract":442,"tags":443},[],[245],[222],{"code":61,"score":55,"supported":47,"title":445,"abstract":446,"tags":447},[],[223],[],{"code":449,"score":22,"supported":14,"title":450,"abstract":451,"tags":452},"E4",[],[],[425],{"code":71,"score":22,"supported":14,"title":454,"abstract":455,"tags":456},[],[],[28],[458,459],"Zenodo 智慧农业 多利益相关方综述","精准灌溉 物联网 区块链 供应链","Zenodo智慧农业多利益相关方综述-5474","10.5281\u002Fzenodo.23510500",{"doi":461,"openalex_id":463,"authors":464,"venue":209,"cited_by_count":95,"oa_url":412,"card":473,"direction":102,"ingested_from":103},"W7223034914",[465,468,470],{"name":466,"orcid":467},"A. Shaji George","https:\u002F\u002Forcid.org\u002F0000-0002-8677-3682",{"name":469,"orcid":9},"Dr.T.Baskar",{"name":471,"orcid":472},"P. Balaji Srikaanth","https:\u002F\u002Forcid.org\u002F0000-0003-4717-7367",{"tldr":474,"method":475,"finding":476,"direction":100,"opportunity":477},"综述六大农业数字技术集群对农场决策的变革及实际效益与采纳差异。","综合同行评议证据与公共部门数据，多利益相关方综述六类技术。","精准技术可增产15-30%、节水30-55%、降本10-20%，但小农获益不均。","缺乏长期田间试验、互操作标准与社会效益数据，小农采纳机制是研究空白。","2026-10-21T23:30:08.684798Z",{"id":480,"title":481,"url":482,"summary":483,"summary_zh":484,"content":9,"source_name":485,"source_url":482,"published_at":486,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":294,"score_detail":487,"sources":490,"tags":492,"primary_topic":495,"secondary_topics":496,"classification":501,"search_phrases":516,"slug":519,"view_count":95,"doi":520,"paper":521,"created_at":541},5376,"Agri-Synergy: A Hardware–Software Co-Designed Hybrid IoT System for Sensor Interface Standardization and LLM-Driven Interactive Decision Support","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fagriengineering8100446","This paper presents Agri-Synergy, a hybrid Internet of Things (IoT) system featuring a hardware–software co-design to tackle sensor data heterogeneity and the barriers to effective AI-driven decision support in smart agriculture. Unlike software-based data harmonization, we propose a universal sensor printed circuit board (PCB) with RS485\u002FModbus interface for hardware unification, complemented by on-node edge processing that ensures standardized data from source. To lower the entry barrier for farmers, the system integrates the DeepSeek large language model (LLM) API, combining static agricultural knowledge with real-time sensor data, for context-aware, natural language-based decision support, functioning without local model deployment. Field deployment showed reference-verified sensor accuracy predominantly within manufacturer specifications, stable 4G connectivity during the 4-h benchmark but intermittent dropouts during the 20-day deployment, and remote-control success rates of 96% (normal) and 80% (weak signal at 300 m). Multi-node concurrent transmission resulted in average latency of 238.0 ± 27.1 ms and packet loss below 0.5%. The system achieves a 3–5× cost reduction compared to commercial platforms. These results demonstrate that addressing data heterogeneity from source through hardware unification and software edge processing, while leveraging AI to lower the barrier to system adoption, provides a more reliable foundation for data synchronization and accessible AI-driven analytics.","本文提出Agri-Synergy，一种采用软硬件协同设计的混合物联网（IoT）系统，旨在解决智慧农业中传感器数据异构性问题以及有效AI驱动决策支持的障碍。与基于软件的数据协调方式不同，我们提出了一种带有RS485\u002FModbus接口的通用传感器印刷电路板（PCB）以实现硬件统一，并辅以节点端边缘处理，确保从源头获得标准化数据。为降低农民的使用门槛，该系统集成了DeepSeek大语言模型（LLM）API，将静态农业知识与实时传感器数据相结合，提供上下文感知的、基于自然语言的决策支持，且无需本地部署模型即可运行。现场部署表明，经参考验证的传感器精度基本处于制造商规格范围内；在4小时基准测试期间4G连接稳定，但在20天部署期间出现间歇性断连；远程控制成功率分别为96%（正常信号）和80%（300 m处弱信号）。多节点并发传输的平均延迟为238.0 ± 27.1 ms，丢包率低于0.5%。与商业平台相比，该系统实现了3–5倍的成本降低。这些结果表明，通过硬件统一和软件边缘处理从源头解决数据异构性问题，同时利用AI降低系统采用门槛，可为数据同步和可及的AI驱动分析提供更可靠的基础。","AgriEngineering","2026-10-19T00:00:00Z",{"impact":488,"substance":418,"depth":18,"authority":17,"freshness":21,"relevant":22,"comment":489},16,"硬件统一接口与边缘处理结合大模型决策支持的农业物联网系统论文，方法新颖、有实地部署数据，但属细分技术进展，公共影响有限。",[491],{"name":485,"url":482},[28,222,29,493,494],"大语言模型","传感器标准化",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[497],{"code":54,"slug":498,"name":499,"path":500,"parent_code":37},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",{"status":40,"locked":14,"version":41,"method":42,"evidence":502},{"candidates":503,"agricultural_evidence":47},[504,508,512],{"code":33,"score":18,"supported":47,"title":505,"abstract":506,"tags":507},[145],[50,51,145],[29],{"code":54,"score":488,"supported":47,"title":509,"abstract":510,"tags":511},[58],[246,58],[222,493],{"code":71,"score":46,"supported":47,"title":513,"abstract":514,"tags":515},[],[28,323],[28],[517,518],"Agri-Synergy 物联网 传感器","DeepSeek 决策支持","Agri-Synergy物联网传感器-5376","10.3390\u002Fagriengineering8100446",{"doi":520,"openalex_id":522,"authors":523,"venue":485,"cited_by_count":95,"oa_url":482,"card":536,"direction":102,"ingested_from":103},"W7222920424",[524,526,528,530,532,534],{"name":525,"orcid":9},"Leqi Lai",{"name":527,"orcid":9},"Langtao Duan",{"name":529,"orcid":9},"Yuhao Chen",{"name":531,"orcid":9},"Yuhang Zheng",{"name":533,"orcid":9},"Jinyu Yang",{"name":535,"orcid":9},"Mingyao Wen",{"tldr":537,"method":538,"finding":539,"direction":102,"opportunity":540},"提出软硬件协同的混合物联网系统，统一传感器接口并用大模型提供交互式决策支持。","通用RS485\u002FModbus传感器PCB、节点边缘处理、DeepSeek大模型A","传感器精度达标，多节点延迟238ms、丢包低于0.5%，成本降低3-5倍。","可研究弱信号下通信可靠性提升与边缘-云端LLM协同的长期田间鲁棒性。","2026-10-20T23:30:08.319698Z"]