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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 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终审：刘玉峰","中国农村经济 2026-10-21","2026-10-21T00:00:00Z",82,{"impact":18,"substance":92,"depth":18,"authority":186,"freshness":20,"relevant":21,"comment":187},15,"核心期刊论文，多案例揭示农业产业园促进小农户融入数字化供应链的协同机制与制度逻辑，理论新意足、政策参考价值高，值得进入每日精选。",[189],{"name":182,"url":179},[26,29,191,192,193],"制度逻辑","数字化供应链","农业产业园",{"code":39,"slug":195,"name":196,"path":197,"parent_code":198},"farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",[],{"status":110,"locked":13,"version":34,"method":35,"evidence":201},{"candidates":202,"agricultural_evidence":41},[203,208],{"code":39,"score":204,"supported":41,"title":205,"abstract":206,"tags":207},12,[29],[29],[29],{"code":57,"score":21,"supported":13,"title":209,"abstract":210,"tags":211},[],[],[26],[213,214],"农业产业园 小农户 数字化供应链","大荔县 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东盟果链与一证通东盟等项目亮相","https:\u002F\u002Fnynct.gxzf.gov.cn\u002Fgxfb\u002Farticle\u002Fdetails?id=6a7e6ba3-51fe-45a4-9e5b-bedfb701be73","「东盟果链」项目用人工智能和机器人实时采集果园生长与农事数据，再通过大模型语义转成多语种营销内容；「一证通东盟」以深度学习检测维持六大国际认证合规，助力脆肉罗非鱼片出口印尼、马来西亚。学生组「乡音兴桂」以一村一故事、一村一乡音打造微信小程序，把方言文化与农产品溯源结合。","广西壮族自治区农业农村厅 2026-10-19","2026-10-19T00:00:00Z","报道",65,{"impact":18,"substance":16,"depth":19,"authority":204,"freshness":79,"relevant":21,"comment":234},"省级农业农村厅发布的AI赋能品牌出海与跨境合规案例，有具体项目与出口对象，信息增量尚可，但属细分行业进展，时效略滞后。",[236],{"name":229,"url":227},[26,101,28,238,239],"农业品牌","跨境贸易",{"code":128,"slug":241,"name":242,"path":243,"parent_code":107},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",[],{"status":110,"locked":13,"version":34,"method":35,"evidence":246},{"candidates":247,"agricultural_evidence":41},[248,254,258,263],{"code":128,"score":129,"supported":41,"title":249,"abstract":250,"tags":253},[],[251,252],"大模型","深度学习",[101],{"code":52,"score":40,"supported":41,"title":255,"abstract":256,"tags":257},[],[28],[28],{"code":259,"score":21,"supported":13,"title":260,"abstract":261,"tags":262},"E5",[],[],[238],{"code":57,"score":21,"supported":13,"title":264,"abstract":265,"tags":266},[],[],[26],[268,269],"东盟果链 广西 人工智能","一证通东盟 罗非鱼","东盟果链广西人工智能-5507","2026-10-22T00:06:58.704704Z",{"id":273,"title":274,"url":275,"summary":276,"summary_zh":8,"content":8,"source_name":277,"source_url":8,"published_at":8,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":278,"score_detail":279,"sources":282,"tags":284,"primary_topic":288,"secondary_topics":292,"classification":293,"search_phrases":326,"slug":329,"view_count":21,"doi":8,"paper":330,"created_at":337},5134,"数字乡村建设的相关问题及对策建议 涉农要素供给、农业经济新业态与数字素养","http:\u002F\u002Fwww.fbxslw.com\u002Fjjlw\u002F29025.html","针对当前涉农要素供给受限的问题,文章提出:一是发挥各级政府部门在涉农要素供给中的主导作用,形成以涉农企业、数字企业为核心的产学研协同创新机制;二是积极引导农业院校、科研机构与农业企业、农户开展技术合作;三是充分发挥大数据的要素属性,完善体现当地农业农情的大数据技术平台,充分利用遥感、云计算、地理信息等新型技术;四是加大农业物联网建设力度,以农业智能设备研发及应用为基础,加强农业大数据模型与算法的结合力度。在农业经济新业态方面,文章提出继续完善农村电商、社交平台为核心的农产品数字流通渠道,推进三次产业的数字化融合力度,提升农业生产过程与生态环境保护的相容力度。最后强调提升农业生产经营主体的数字素养,通过各类数字村务、政务或教育平台向新型职业农民提供数字培训服务。","钧创学术论文网 数字乡村建设研究 2026 年 10 月",47,{"impact":16,"substance":280,"depth":204,"authority":148,"freshness":161,"relevant":21,"comment":281},14,"选题切合数字乡村与农业信息化方向，但属学术论文网转载的综述性对策文章，无新数据与独家结论，信源权威性和时效性均弱，不宜进入每日精选。",[283],{"name":277,"url":275},[285,26,286,27,287],"农村电商","数字素养","农业大数据",{"code":57,"slug":289,"name":290,"path":291,"parent_code":107},"digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village",[],{"status":110,"locked":13,"version":34,"method":35,"evidence":294},{"candidates":295,"agricultural_evidence":41},[296,300,304,308,314,320],{"code":57,"score":280,"supported":41,"title":297,"abstract":298,"tags":299},[26],[287],[287,26,286],{"code":259,"score":40,"supported":41,"title":301,"abstract":302,"tags":303},[],[285],[285],{"code":46,"score":40,"supported":41,"title":305,"abstract":306,"tags":307},[],[49],[27],{"code":309,"score":148,"supported":41,"title":310,"abstract":311,"tags":313},"G1",[],[312],"产学研",[],{"code":315,"score":148,"supported":41,"title":316,"abstract":317,"tags":319},"I3",[],[318],"遥感",[],{"code":321,"score":148,"supported":41,"title":322,"abstract":323,"tags":325},"I4",[],[324],"地理信息",[],[327,328],"数字乡村建设 涉农要素供给","农业经济新业态 数字素养","数字乡村建设涉农要素供给-5134",{"doi":8,"openalex_id":8,"authors":331,"venue":8,"cited_by_count":66,"oa_url":8,"card":332,"direction":74,"ingested_from":76},[],{"tldr":333,"method":334,"finding":335,"direction":74,"opportunity":336},"分析数字乡村建设中涉农要素供给、农业新业态与数字素养问题并提出对策。","政策分析与对策建议，涉及大数据、遥感、物联网、电商平台等。","需政府主导、产学研协同，完善大数据平台与物联网，提升农民数字素养。","可实证检验数字素养培训对农户采纳数字技术及新业态参与的影响机制。","2026-10-17T00:13:45.192454Z",{"id":339,"title":340,"url":341,"summary":342,"summary_zh":343,"content":8,"source_name":344,"source_url":341,"published_at":345,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":346,"score_detail":347,"sources":349,"tags":351,"primary_topic":354,"secondary_topics":359,"classification":361,"search_phrases":400,"slug":403,"view_count":66,"doi":404,"paper":405,"created_at":428},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":204,"substance":92,"depth":18,"authority":280,"freshness":20,"relevant":21,"comment":348},"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。",[350],{"name":344,"url":341},[26,100,27,352,353],"智能灌溉","网络安全",{"code":141,"slug":355,"name":356,"path":357,"parent_code":358},"irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[360],{"code":46,"slug":104,"name":105,"path":106,"parent_code":107},{"status":110,"locked":13,"version":34,"method":35,"evidence":362},{"candidates":363,"agricultural_evidence":41},[364,369,374,380,386,392,396],{"code":141,"score":186,"supported":41,"title":365,"abstract":366,"tags":368},[355],[367,355],"灌溉",[352],{"code":46,"score":12,"supported":41,"title":370,"abstract":371,"tags":373},[],[49,372,124],"internet of things",[27],{"code":375,"score":148,"supported":41,"title":376,"abstract":377,"tags":379},"B7",[],[378],"greenhouse",[],{"code":381,"score":148,"supported":41,"title":382,"abstract":383,"tags":385},"C",[],[384],"livestock",[],{"code":387,"score":148,"supported":41,"title":388,"abstract":389,"tags":391},"F3",[],[390],"fertigation",[],{"code":57,"score":161,"supported":13,"title":393,"abstract":394,"tags":395},[],[],[26,353],{"code":114,"score":21,"supported":13,"title":397,"abstract":398,"tags":399},[],[],[100],[401,402],"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":404,"openalex_id":406,"authors":407,"venue":344,"cited_by_count":66,"oa_url":341,"card":423,"direction":172,"ingested_from":174},"W7222165876",[408,411,414,417,420],{"name":409,"orcid":410},"Alvertos Ioannis Mourikis","https:\u002F\u002Forcid.org\u002F0009-0009-2386-2803",{"name":412,"orcid":413},"Iosif Polenakis","https:\u002F\u002Forcid.org\u002F0000-0002-6427-5519",{"name":415,"orcid":416},"Christos Sarantidis","https:\u002F\u002Forcid.org\u002F0009-0003-9486-8483",{"name":418,"orcid":419},"Romanos Kalamatianos","https:\u002F\u002Forcid.org\u002F0009-0000-6939-5424",{"name":421,"orcid":422},"Ioannis Karydis","https:\u002F\u002Forcid.org\u002F0000-0002-9470-2729",{"tldr":424,"method":425,"finding":426,"direction":172,"opportunity":427},"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":430,"title":431,"url":432,"summary":433,"summary_zh":8,"content":8,"source_name":434,"source_url":8,"published_at":8,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":435,"score_detail":436,"sources":438,"tags":440,"primary_topic":443,"secondary_topics":444,"classification":445,"search_phrases":462,"slug":465,"view_count":21,"doi":8,"paper":466,"created_at":473},4972,"数字赋能:助推小农户融入现代农业发展轨道——基于全国农户微观数据的考察","http:\u002F\u002Fwww.qikanzj.com\u002Fhek\u002Fjnxb\u002Fmulu\u002F633014.html","钟文晶、李丹、罗必良(华南农业大学经济管理学院)基于有限理性假设和信息不对称理论,探讨互联网信息技术助推小农户数字赋能的内在机理,并利用中国劳动力动态调查(CLDS)2018年的微观数据进行实证检验。结果表明,互联网使用有效促进了小农户农业生产的机械化、土地经营的规模化以及对农业的生产性投资;异质性分析表明,数字赋能在大规模农户、中老年农户、中部和东北地区的农户组中的作用尤为显著。文章强调应加快推进农村地区的数字基础设施建设,提升农户的数字素养。","《农业经济问题》",79,{"impact":92,"substance":93,"depth":18,"authority":280,"freshness":161,"relevant":21,"comment":437},"基于全国微观数据的实证研究，结论扎实且具政策参考价值，但时效性偏弱，适合主题聚合而非当日精选。",[439],{"name":434,"url":432},[26,286,29,441,442],"互联网使用","农村数字基建",{"code":39,"slug":195,"name":196,"path":197,"parent_code":198},[],{"status":110,"locked":13,"version":34,"method":35,"evidence":446},{"candidates":447,"agricultural_evidence":41},[448,452,458],{"code":39,"score":204,"supported":41,"title":449,"abstract":450,"tags":451},[29],[29],[29],{"code":453,"score":148,"supported":41,"title":454,"abstract":455,"tags":457},"F5",[],[456],"机械化",[],{"code":57,"score":161,"supported":13,"title":459,"abstract":460,"tags":461},[],[],[26,286],[463,464],"华南农业大学 小农户 数字赋能","CLDS 互联网使用 农业生产","华南农业大学小农户数字赋能-4972",{"doi":8,"openalex_id":8,"authors":467,"venue":8,"cited_by_count":66,"oa_url":8,"card":468,"direction":74,"ingested_from":76},[],{"tldr":469,"method":470,"finding":471,"direction":74,"opportunity":472},"基于CLDS数据实证检验互联网使用如何助推小农户融入现代农业发展。","有限理性与信息不对称理论，CLDS 2018农户微观数据实证。","互联网使用促进小农户机械化、规模化和生产性投资，中老年及中部东北农户效应更显著。","可探究数字素养培训与数字基础设施如何协同提升小农户数字赋能效果。","2026-10-15T00:06:09.096458Z"]