[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1415":3,"related-1415":100},{"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":23,"tags":25,"primary_topic":30,"secondary_topics":36,"classification":37,"search_phrases":66,"slug":69,"view_count":70,"doi":71,"paper":72,"created_at":99},1415,"Electroactive biodegradable microneedles for minimally invasive real-time, in-situ plant physiological monitoring and industrial NH3 sensing","https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs42825-026-00254-9","Real-time, in situ monitoring of plant physiological parameters and industrial toxic gas emissions is vital for advancing precision agriculture and ensuring environmental safety. Herein, we developed an electroactive biodegradable microneedle (PPG-MN) sensor enabling minimally invasive monitoring of interstitial glucose, ambient temperature, humidity, and environmental ammonia (NH 3 ) gas leakage. The sensor matrix was fabricated using a polyvinyl alcohol (PVA) network interpenetrated with conductive polyaniline (PANI) and doped with phytic acid (PA), while glucose oxidase (GOx) was immobilized for specificity. The resulting microneedle array exhibited sufficient mechanical strength to penetrate the plant epidermis, establishing a stable electrode–tissue interface via hydrogel swelling. The sensor demonstrated excellent environmental friendliness, featuring a pathogen inhibition rate exceeding 97% and complete soil biodegradation within 35 days. By integrating enzymatic sensing with a temperature and humidity compensation mechanism (effective across 25–50 °C and 25%–50% relative humidity (RH)), the PPG-MN achieved a rapid response time (\u003C 30 s) and a wide linear detection range (1–100 mM). Furthermore, continuous in situ monitoring of Epipremnum aureum leaves over 14 h successfully tracked dynamic glucose fluctuations driven by photosynthesis and respiration. Additionally, leveraging the reversible doping\u002Fde-doping mechanism of the PA-doped PANI network, the hydrogel base acts as a highly sensitive chemiresistive gas sensor. The PPG-MN exhibited a strong linear response (R ² = 0.986) to NH 3 across a broad concentration range of 10 to 500 ppm, effectively encompassing the typical toxic emission levels encountered during leather deliming processes. These results indicate that the PPG-MN sensor is a promising, eco-friendly tool for both agricultural Internet of Things (IoT) systems and hazardous gas pre-warning in industries like leather processing.","实时、原位监测植物生理参数和工业有毒气体排放对于推进精准农业和保障环境安全至关重要。为此，我们开发了一种电活性可生物降解微针（PPG-MN）传感器，能够实现微创监测组织间葡萄糖、环境温度、湿度以及环境氨气（NH₃）泄漏。传感器基质采用聚乙烯醇（PVA）网络与导电聚苯胺（PANI）互穿，并掺杂植酸（PA）制备而成，同时固定葡萄糖氧化酶（GOx）以确保特异性。所得微针阵列具有足够的机械强度，可穿透植物表皮，并通过水凝胶溶胀建立稳定的电极–组织界面。该传感器表现出优异的环境友好性，病原体抑制率超过97%，并在35天内完全土壤生物降解。通过将酶传感与温湿度补偿机制（在25–50 °C和25%–50%相对湿度（RH）范围内有效）相结合，PPG-MN实现了快速响应时间（\u003C30 s）和宽线性检测范围（1–100 mM）。此外，对绿萝（Epipremnum aureum）叶片进行连续14小时的原位监测，成功追踪了由光合作用和呼吸作用驱动的动态葡萄糖波动。进一步地，利用PA掺杂PANI网络的可逆掺杂\u002F去掺杂机制，水凝胶基底可作为高灵敏度化学电阻式气体传感器。PPG-MN对NH₃在10至500 ppm的宽浓度范围内表现出强线性响应（R² = 0.986），有效覆盖了皮革脱灰过程中典型的毒性排放水平。上述结果表明，PPG-MN传感器是一种兼具农业物联网（IoT）系统应用和皮革加工等行业危险气体预警功能的有前景的环保工具。",null,"Collagen and Leather","2026-09-01T00:00:00Z","论文",10,false,77,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,12,7,1,"研发可降解微针传感器，实现植物生理实时监测与工业氨气预警，兼具农业与环境应用价值。",[24],{"name":10,"url":6},[26,27,28,29],"智慧农业","农业传感器","植物监测","生物降解",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",[],{"status":38,"locked":14,"version":39,"method":40,"evidence":41},"classified","2026-10-22.2","rules",{"candidates":42,"agricultural_evidence":44},[43,51,58],{"code":31,"score":13,"supported":44,"title":45,"abstract":46,"tags":50},true,[],[47,48,49],"物联网","internet of things","IoT",[27],{"code":52,"score":20,"supported":44,"title":53,"abstract":54,"tags":57},"I1",[],[55,56],"精准农业","precision agriculture",[26],{"code":59,"score":60,"supported":44,"title":61,"abstract":62,"tags":65},"H2",6,[],[63,64],"土壤","soil",[],[67,68],"农业传感器 智慧农业 植物监测 生物降解","农业传感器 智慧农业","农业传感器智慧农业植物监测生物降解-1415",3,"10.1186\u002Fs42825-026-00254-9",{"doi":71,"openalex_id":73,"authors":74,"venue":10,"cited_by_count":91,"oa_url":6,"card":92,"direction":96,"ingested_from":98},"W7204774910",[75,78,80,82,84,86,88],{"name":76,"orcid":77},"Huie Jiang","https:\u002F\u002Forcid.org\u002F0000-0003-3699-4126",{"name":79,"orcid":9},"Tianqi Zhao",{"name":81,"orcid":9},"Lijuan Chen",{"name":83,"orcid":9},"Peng Guo",{"name":85,"orcid":9},"Lanxue Zou",{"name":87,"orcid":9},"Lin Yang",{"name":89,"orcid":90},"Xinhua Liu","https:\u002F\u002Forcid.org\u002F0000-0003-0286-2061",0,{"tldr":93,"method":94,"finding":95,"direction":96,"opportunity":97},"开发了一种可生物降解的电活性微针传感器，用于植物生理监测和工业氨气检测。","利用PVA\u002FPANI\u002FPA水凝胶和葡萄糖氧化酶构建微针阵列，实现电化学和化学电阻","传感器可实时监测植物葡萄糖、温湿度，对氨气响应快、线性好，且可生物降解。","智慧农业 \u002F 农业物联网","可探索该微针传感器在更多作物和田间环境下的长期监测，以及多参数集成和无线传输的优化。","openalex","2026-09-02T23:30:15.252008Z",{"total":60,"page":21,"page_size":60,"items":101},[102,162,232,339,387,496],{"id":103,"title":104,"url":105,"summary":106,"summary_zh":107,"content":9,"source_name":108,"source_url":105,"published_at":109,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":110,"score_detail":111,"sources":116,"tags":118,"primary_topic":121,"secondary_topics":125,"classification":127,"search_phrases":145,"slug":148,"view_count":91,"doi":149,"paper":150,"created_at":161},4295,"Smart Soil Monitoring Systems: Challenges and Strategic Solutions for Enhanced Adoption","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fwjimt.v9.no12.2025.pg245.258","Smart Soil Monitoring Systems (SSMS) represent a key innovation in precision agriculture, enabling continuous monitoring of soil parameters such as moisture, pH, nutrient content, temperature, and salinity. These systems integrate Internet of Things (IoT) technologies, wireless sensor networks, and data analytics to provide real-time insights that support data-driven decision-making, optimize resource use, and enhance crop productivity. Despite their potential, the adoption of SSMS in developing institutions, including Federal Polytechnic Bali (FPB), remains limited due to financial constraints, inadequate technical skills, low awareness, and infrastructural challenges such as unreliable internet connectivity and power supply. The high cost of devices, lack of training, and insufficient institutional policies further impede practical implementation in teaching, research, and extension activities. This study employed a descriptive survey design targeting academic and technical staff in FPB’s agricultural departments. Data collected via a structured questionnaire were analyzed using descriptive statistics, with mean scores indicating key challenges and potential strategies. Findings revealed that high device costs, poor network infrastructure, and low technical capacity were the most critical barriers. To address these, respondents emphasized capacity-building workshops, improved digital infrastructure, awareness campaigns, funding support, and policy frameworks as strategic interventions. The study concludes that enhancing SSMS adoption requires integrated solutions addressing economic, technical, and institutional barriers. Implementation of these strategies is expected to strengthen hands-on learning, improve research outputs, and promote sustainable, technology-driven agriculture at FPB. The study contributes to understanding practical adoption challenges of smart agricultural technologies in resource-constrained educational settings.","智能土壤监测系统（Smart Soil Monitoring Systems, SSMS）是精准农业的一项关键创新，能够对土壤湿度、pH值、养分含量、温度和盐度等参数进行持续监测。这些系统集成了物联网（IoT）技术、无线传感器网络和数据分析，可提供实时洞察，支持数据驱动的决策、优化资源利用并提高作物生产力。尽管潜力巨大，但包括巴厘联邦理工学院（Federal Polytechnic Bali, FPB）在内的发展中机构对SSMS的采用仍然有限，原因在于资金约束、技术技能不足、认知度低以及互联网连接和电力供应不可靠等基础设施挑战。设备成本高昂、缺乏培训以及制度政策不完善，进一步阻碍了其在教学、研究和推广活动中的实际应用。本研究采用描述性调查设计，以FPB农业部门的学术和技术人员为研究对象。通过结构化问卷收集的数据采用描述性统计进行分析，以平均分表明主要挑战和潜在策略。研究发现，设备成本高、网络基础设施差和技术能力低是最关键的障碍。为应对这些问题，受访者强调能力建设研讨会、改善数字基础设施、宣传活动、资金支持和政策框架是战略性干预措施。研究得出结论，提升SSMS的采用需要综合解决方案，以应对经济、技术和制度层面的障碍。这些策略的实施有望加强实践学习、提高研究产出，并推动FPB可持续的、技术驱动的农业发展。本研究有助于理解资源受限教育环境中智能农业技术的实际采用挑战。","WORLD JOURNAL OF INNOVATION AND MODERN TECHNOLOGY","2026-10-05T00:00:00Z",52,{"impact":112,"substance":113,"depth":114,"authority":60,"freshness":112,"relevant":21,"comment":115},8,16,14,"聚焦资源受限院校智慧土壤监测落地障碍的实证调查，结论实用但样本局限于单一院校，影响力有限。",[117],{"name":108,"url":105},[119,26,47,120,27],"数字农业","土壤监测",{"code":59,"slug":64,"name":122,"path":123,"parent_code":124},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",[126],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":38,"locked":14,"version":39,"method":40,"evidence":128},{"candidates":129,"agricultural_evidence":44},[130,134,141],{"code":59,"score":114,"supported":44,"title":131,"abstract":132,"tags":133},[64],[63,64],[],{"code":31,"score":135,"supported":44,"title":136,"abstract":137,"tags":140},11,[],[47,138,48,49,139],"无线传感","wireless sensor",[27,47],{"code":52,"score":112,"supported":44,"title":142,"abstract":143,"tags":144},[],[55,56],[119,26],[146,147],"农业传感器 土壤监测 数字农业 智慧农业","农业传感器 土壤监测","农业传感器土壤监测数字农业智慧农业-4295","10.56201\u002Fwjimt.v9.no12.2025.pg245.258",{"doi":149,"openalex_id":151,"authors":152,"venue":108,"cited_by_count":91,"oa_url":155,"card":156,"direction":96,"ingested_from":98},"W7220426775",[153],{"name":154,"orcid":9},"NUHU ABDULLAHI","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FWJIMT\u002FVOL. 9 NO. 12 2025\u002FSmart Soil Monitoring Systems 245-258.pdf",{"tldr":157,"method":158,"finding":159,"direction":96,"opportunity":160},"调查尼日利亚某院校智能土壤监测系统采纳障碍并提出策略。","描述性问卷调研农业院系教职工，用描述统计与均值分析。","设备成本高、网络差、技术能力低是主要障碍，需培训与政策支持。","可研究资源受限院校中低成本物联网土壤监测方案与采纳机制。","2026-10-06T23:30:07.776821Z",{"id":163,"title":164,"url":165,"summary":166,"summary_zh":167,"content":9,"source_name":168,"source_url":169,"published_at":170,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":171,"score_detail":172,"sources":174,"tags":176,"primary_topic":180,"secondary_topics":186,"classification":188,"search_phrases":213,"slug":216,"view_count":217,"doi":218,"paper":219,"created_at":231},4208,"High-Efficiency Solar-Piezo Hybrid Energy Harvester for Long-Term Autonomous Operation of Smart Agriculture Sensor Nodes","https:\u002F\u002Fdoi.org\u002F10.31838\u002Fece\u002F03.02.06","The paper presents the design and consideration of a highly efficient hybrid energy harvesting system, combined solar and piezo energy harvesting components to power autonomous wireless sensor nodes (WSNs) used in smart agriculture. The most important goal is to provide a maintenance free, long term operation of the sensor nodes in the envisioned variable conditions of environment. The suggested system consists of a monocrystalline solar panel and piezoelectric transducers that allow to focus both ambient light and mechanics vibrations. In-order to get maximum energy extraction, intelligent maximum power point tracking (MPPT) based power conditioning circuit is implemented, and the energy generated is stored using hybrid supercapacitor-Li-ion battery system. Up to the area of evaluation of the performance of the designed system in the real conditions, a particular WSN platform was created and deployed both in a greenhouse and an open field setting. The experimental output shows that the hybrid energy harvester records a 30-45 percent rise in energy capture than the solar-only systems. Moreover, efficiency of conversion of power is increased by about 22 % by using the MPPT implementation. The sensor nodes exhibited an outstanding reliability, surpassing 98 per cent of uptime in a 30-day non-stop deployment, and over 12 hours working autonomously without any illumination. The innovation in this study is the strength of the energy harvesting system, where supplementary sources are also utilized to increase the resilience and extend the operation weeks of smart agriculture WSNs, considering the shortcomings of using single sources in the uncontrollable outdoor situations.","本文介绍了一种高效混合能量收集系统的设计与思考，该系统结合了太阳能和压电能量收集组件，为智慧农业中使用的自主无线传感器节点（WSN）供电。最重要的目标是在预期的多变环境条件下，实现传感器节点的免维护、长期运行。所提出的系统由单晶硅太阳能板和压电换能器组成，能够同时利用环境光和机械振动。为了实现最大能量提取，采用了基于智能最大功率点跟踪（MPPT）的功率调节电路，并将产生的能量通过混合超级电容器-锂离子电池系统进行存储。为了在实际条件下评估所设计系统的性能，专门搭建了一个WSN平台，并在温室和露天田地环境中进行了部署。实验结果表明，与仅使用太阳能的系统相比，混合能量收集器的能量采集量提高了30%至45%。此外，通过采用MPPT实现，功率转换效率提高了约22%。传感器节点表现出卓越的可靠性，在30天不间断部署中正常运行时间超过98%，并在无任何光照条件下自主运行超过12小时。本研究的创新之处在于该能量收集系统的稳健性，其中还利用了辅助能源来增强智慧农业WSN的韧性并延长其运行周数，考虑到在不可控的户外环境中使用单一能源的局限性。","Progress in Electronics and Communication Engineering","https:\u002F\u002Fecejournals.in\u002Findex.php\u002FPECE\u002Farticle\u002Fview\u002F429","2026-10-22T00:00:00Z",70,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":91,"relevant":21,"comment":173},"论文提出太阳能-压电混合能量采集方案，实测能量捕获提升30-45%、节点在线率超98%，对智慧农业长期免维护传感部署有实质参考价值，但发表于半月后、时效性不足，暂不宜进入每日精选。",[175],{"name":168,"url":169},[26,177,27,178,179],"农业物联网","能量采集","无线传感器",{"code":181,"slug":182,"name":183,"path":184,"parent_code":185},"F5","machinery","农机装备与机械化","\u002Ftopic\u002Finputs-equipment\u002Fmachinery","F",[187],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":38,"locked":14,"version":39,"method":40,"evidence":189},{"candidates":190,"agricultural_evidence":44},[191,197,202,206],{"code":52,"score":192,"supported":44,"title":193,"abstract":195,"tags":196},15,[194],"smart agriculture",[26,194],[26],{"code":181,"score":135,"supported":44,"title":198,"abstract":200,"tags":201},[199],"harvester",[199],[],{"code":31,"score":112,"supported":44,"title":203,"abstract":204,"tags":205},[],[138,139],[27,177],{"code":207,"score":60,"supported":44,"title":208,"abstract":209,"tags":212},"B7",[],[210,211],"温室","greenhouse",[],[214,215],"太阳能 压电 混合能量采集","农业无线传感器 自供电","太阳能压电混合能量采集-4208",2,"10.31838\u002Fece\u002F03.02.06",{"doi":218,"openalex_id":220,"authors":221,"venue":168,"cited_by_count":91,"oa_url":169,"card":226,"direction":96,"ingested_from":98},"W7219845622",[222,224],{"name":223,"orcid":9},"N. K. Havalam",{"name":225,"orcid":9},"Ragaba Mean Bosco",{"tldr":227,"method":228,"finding":229,"direction":96,"opportunity":230},"设计太阳能-压电混合能量收集系统，为智慧农业无线传感器节点提供长期免维护供电。","单晶硅太阳能板与压电换能器混合，MPPT电路及超级电容-锂离子电池储能，温室和露","混合系统能量捕获比纯太阳能高30-45%，MPPT提升转换效率约22%，30天运行时间超98%，无光","可探索混合能量收集与低功耗传感器调度协同优化，以及基于环境预测的动态能量管理策略。","2026-10-05T23:30:08.764944Z",{"id":233,"title":234,"url":235,"summary":236,"summary_zh":237,"content":9,"source_name":238,"source_url":235,"published_at":239,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":240,"score_detail":241,"sources":246,"tags":248,"primary_topic":251,"secondary_topics":252,"classification":258,"search_phrases":320,"slug":323,"view_count":112,"doi":324,"paper":325,"created_at":338},3536,"Functional photonic and optoelectronic materials and devices for climate-resilient smart agriculture: a review","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffmats.2026.1943334","The variation in the temperature, precipitation, and extreme events has rendered climate change very threatening to crop production and the overall world food security. The prospects of sustainable and climate resilient agricultural production is brought up with the use of photonics and optoelectronics coupled with smart farming technology. The paper offers an overall foundation of smart agricultural systems that are assisted by photonics and optoelectronics that combine the state-of-the-art optical sensors, Internet of Things (IoT) communications, and machine learning algorithms in the crop and soil monitoring. Due to optical sensing technologies including fiber optic sensors, LiDAR, fluorescence spectroscopy, and hyperspectral imaging, optical sensors can also be used in high resolution and non-destructive measurement of physiological properties of plants, nutrient status, water stress and disease incidence. With the help of optoelectronic devices, it is possible to carry out the accurate signal processing, data collection, automated control of irrigation, fertigation and microclimate regulating systems. When sensor-based information is incorporated with any decision support systems the quality of early stress detection is improved, wastage of resources is minimized and the effect on the environment is minimized. Multispectral and temporal data based on machine learning models enhance forecasting of climate risk, diseases, and pest outbreaks forecasting, and crop yield forecasting. The system will aid in making the contemporary crop production systems more sustainable and resilient in the long-term due to the fact that it will provide scalable and flexible solutions across the agroecological regions.","温度、降水及极端事件的变化使气候变化对作物生产和全球粮食安全构成严重威胁。光子学与光电子学结合智慧农业技术，为实现可持续且气候韧性的农业生产带来了前景。本文提供了由光子学和光电子学辅助的智慧农业系统的总体基础，该系统将先进的光学传感器、物联网（IoT）通信和机器学习算法结合应用于作物与土壤监测。借助光纤传感器、激光雷达（LiDAR）、荧光光谱和高光谱成像等光学传感技术，光学传感器还可用于高分辨率、非破坏性地测量植物生理特性、养分状况、水分胁迫和病害发生情况。借助光电子器件，可以实现精确的信号处理、数据采集以及灌溉、施肥和微气候调节系统的自动控制。当基于传感器的信息与决策支持系统相结合时，早期胁迫检测的质量得以提高，资源浪费降至最低，对环境的影响也降至最小。基于机器学习模型的多光谱和时间序列数据增强了气候风险、病虫害暴发预测以及作物产量预测的能力。该系统将有助于使当代作物生产系统在长期内更具可持续性和韧性，因为它将为各农业生态区域提供可扩展且灵活的解决方案。","Frontiers in Materials","2026-09-25T00:00:00Z",76,{"impact":17,"substance":242,"depth":243,"authority":244,"freshness":112,"relevant":21,"comment":245},20,17,13,"系统综述光子与光电子技术在气候韧性智慧农业中的应用，方法覆盖全面、结论可靠，对农业信息化领域有较高参考价值。",[247],{"name":238,"url":235},[26,177,249,27,250],"机器学习","光谱遥感",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[253],{"code":254,"slug":255,"name":256,"path":257,"parent_code":35},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",{"status":38,"locked":14,"version":39,"method":40,"evidence":259},{"candidates":260,"agricultural_evidence":44},[261,265,269,275,282,289,293,300,307,314],{"code":52,"score":19,"supported":44,"title":262,"abstract":263,"tags":264},[194],[26],[26],{"code":31,"score":135,"supported":44,"title":266,"abstract":267,"tags":268},[],[47,48,49],[27,177],{"code":254,"score":13,"supported":44,"title":270,"abstract":271,"tags":274},[],[249,272,273],"machine learning","decision support",[249],{"code":276,"score":60,"supported":44,"title":277,"abstract":278,"tags":281},"A8",[],[279,280],"粮食安全","food security",[],{"code":283,"score":60,"supported":44,"title":284,"abstract":285,"tags":288},"F3",[],[286,287],"施肥","fertigation",[],{"code":59,"score":60,"supported":44,"title":290,"abstract":291,"tags":292},[],[63,64],[],{"code":294,"score":60,"supported":44,"title":295,"abstract":296,"tags":299},"H3",[],[297,298],"灌溉","irrigation",[],{"code":301,"score":60,"supported":44,"title":302,"abstract":303,"tags":306},"H7",[],[304,305],"气候变化","climate change",[],{"code":308,"score":60,"supported":44,"title":309,"abstract":310,"tags":313},"I3",[],[311,312],"multispectral","hyperspectral",[],{"code":315,"score":70,"supported":44,"title":316,"abstract":317,"tags":319},"H6",[],[318],"农业生态",[],[321,322],"光子学 光电材料 智慧农业","光纤传感 高光谱成像 作物监测","光子学光电材料智慧农业-3536","10.3389\u002Ffmats.2026.1943334",{"doi":324,"openalex_id":326,"authors":327,"venue":238,"cited_by_count":91,"oa_url":235,"card":333,"direction":96,"ingested_from":98},"W7214293156",[328,330],{"name":329,"orcid":9},"Karthika Vishnu Priya Kathula",{"name":331,"orcid":332},"Murugesan Mohana Keerthi","https:\u002F\u002Forcid.org\u002F0000-0002-2018-0200",{"tldr":334,"method":335,"finding":336,"direction":96,"opportunity":337},"综述光子与光电子材料器件结合物联网和机器学习，支撑气候韧性智慧农业的作物与土壤监测。","综述光纤传感、LiDAR、荧光光谱、高光谱成像与IoT、机器学习融合方案。","光学传感与光电器件可实现无损高分辨监测，提升早期胁迫检测并减少资源浪费。","可探索低成本光子传感器与轻量ML模型在田间边缘端的集成及跨生态区泛化验证。","2026-09-26T23:30:09.644423Z",{"id":340,"title":341,"url":342,"summary":343,"summary_zh":344,"content":9,"source_name":345,"source_url":342,"published_at":346,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":171,"score_detail":347,"sources":349,"tags":351,"primary_topic":354,"secondary_topics":355,"classification":356,"search_phrases":369,"slug":372,"view_count":217,"doi":373,"paper":374,"created_at":386},2298,"A systematic review of data handling and management techniques in edge computing for IoT","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs42452-026-09533-w","The proliferation of Internet of Things (IoT) devices and latency-sensitive applications has increased the need for edge computing, which complements existing cloud systems by enabling data processing closer to the source. By processing data closer to the source, edge computing reduces latency, bandwidth consumption, and response time. Organisations face major challenges in data management because edge environments use decentralised systems and limited resources, which require them to manage multiple data management tasks, including storage resources, data caching, data aggregation and data integrity verification. The resolution of these problems is necessary to create Edge-IoT systems that can operate at a large scale while maintaining trustworthy and secure operations. This paper presents a comprehensive and systematic review of recent advancements that occurred between 2022 and 2025 in data handling optimisation techniques for edge computing in IoT applications. The study employs a structured review methodology that meets Scopus and Web of Science standards to evaluate research studies that are divided into four main categories, which include data storage optimisation, data caching strategies, data aggregation mechanisms and data integrity assurance techniques. A total of 52 primary technical studies were selected for detailed comparative analysis, while additional secondary literature sources were used for theoretical background and contextual discussion. The study conducts a comprehensive comparative analysis, which assesses performance through latency and energy consumption, system scalability, security overhead and system performance under varying workloads. The review evaluates application-specific use cases, which include smart cities, healthcare, industrial IoT, autonomous vehicles and smart agriculture, to demonstrate the real-world significance of present solutions. The review identifies gaps in adaptive optimisation, heterogeneous device support, privacy preservation, and cross-layer coordination as critical research problems. The document describes existing challenges and future research paths that will help create advanced data processing systems for edge-enabled Internet of Things networks.","物联网（IoT）设备的激增以及对延迟敏感的应用需求推动了边缘计算的发展，边缘计算通过在更接近数据源的位置进行数据处理，对现有云系统形成补充。通过在更接近数据源的位置处理数据，边缘计算降低了延迟、带宽消耗和响应时间。由于边缘环境采用去中心化系统且资源有限，组织在数据管理方面面临重大挑战，需要管理多项数据管理任务，包括存储资源、数据缓存、数据聚合和数据完整性验证。解决这些问题对于构建能够大规模运行且保持可信和安全操作的边缘物联网系统至关重要。本文对2022年至2025年间物联网应用中边缘计算数据处理优化技术的最新进展进行了全面系统的综述。本研究采用符合Scopus和Web of Science标准的结构化综述方法，将研究文献分为四大类进行评估，包括数据存储优化、数据缓存策略、数据聚合机制和数据完整性保障技术。共选取52篇主要技术研究进行详细比较分析，同时使用其他二手文献来源提供理论背景和情境讨论。本研究进行了全面的比较分析，从延迟和能耗、系统可扩展性、安全开销以及不同工作负载下的系统性能等方面评估性能。综述评估了特定应用场景，包括智慧城市、医疗健康、工业物联网、自动驾驶汽车和智慧农业，以展示当前解决方案的实际意义。综述指出了自适应优化、异构设备支持、隐私保护和跨层协调方面的不足，将其列为关键研究问题。本文描述了现有挑战和未来研究方向，有助于为边缘赋能的物联网网络构建先进的数据处理系统。","Discover Applied Sciences","2026-09-11T00:00:00Z",{"impact":19,"substance":242,"depth":243,"authority":244,"freshness":112,"relevant":21,"comment":348},"系统综述边缘计算数据管理技术，含智慧农业等应用场景，对农业物联网部署有参考价值，但非农业专属研究，影响范围有限。",[350],{"name":345,"url":342},[26,352,47,27,353],"边缘计算","数据管理",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":357},{"candidates":358,"agricultural_evidence":44},[359,365],{"code":31,"score":360,"supported":44,"title":361,"abstract":363,"tags":364},28,[49,362],"edge computing",[47,352,48,49,362],[27,47,352],{"code":52,"score":20,"supported":44,"title":366,"abstract":367,"tags":368},[],[26,194],[26],[370,371],"农业传感器 数据管理 智慧农业 边缘计算","农业传感器 数据管理","农业传感器数据管理智慧农业边缘计算-2298","10.1007\u002Fs42452-026-09533-w",{"doi":373,"openalex_id":375,"authors":376,"venue":345,"cited_by_count":91,"oa_url":342,"card":381,"direction":96,"ingested_from":98},"W7212114265",[377,379],{"name":378,"orcid":9},"Sourabh Natu",{"name":380,"orcid":9},"Ankur Goyal",{"tldr":382,"method":383,"finding":384,"direction":96,"opportunity":385},"系统综述2022-2025年IoT边缘计算数据处理与管理优化技术，涵盖存储、缓存、聚合与完整性四类。","遵循Scopus\u002FWoS标准的结构化综述，比较分析52篇主要技术研究。","识别出自适应优化、异构设备支持、隐私保护与跨层协调四大关键研究空白。","可将边缘数据管理优化方法迁移至农业IoT场景，填补农业边缘计算中自适应与跨层协调的研究空白。","2026-09-13T23:30:09.503310Z",{"id":388,"title":389,"url":390,"summary":391,"summary_zh":392,"content":9,"source_name":393,"source_url":390,"published_at":394,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":395,"score_detail":396,"sources":399,"tags":401,"primary_topic":406,"secondary_topics":409,"classification":412,"search_phrases":466,"slug":469,"view_count":91,"doi":470,"paper":471,"created_at":495},5564,"Dynamic thermal imaging for crop water stress detection across phenological stages: Enhancing irrigation scheduling precision","https:\u002F\u002Fdoi.org\u002F10.14719\u002Fpst.17728","Thermal remote sensing and derived indices such as the crop water stress index (CWSI) can assess crop water status and support precision irrigation. However, most operational and artificial intelligence (AI)-based approaches rely on fixed, season-long thresholds to interpret canopy–air temperature differences and often overlook the influence of crop phenology. This review synthesises evidence from grapevine, wheat, maize, potato and several other crops on how developmental stage affects the non-water-stressed baseline (NWSB), CWSI thresholds and irrigation-scheduling algorithms. It covers CWSI theory and estimation practices; crop-specific, phenology-dependent behaviour of baselines and thresholds; a comparison of threshold-based, machine learning, Internet of Things (IoT), digital twin and Food and Agriculture Organization (FAO)-56 approaches with respect to crop phenology; and a conceptual framework for phenology-aware scheduling. Across the reviewed crops, baseline behaviour generally varied systematically across the growing season, the relationship between CWSI and crop water status generally strengthened after canopy closure and CWSI measured during reproductive stages was generally most closely related to yield. A quantitative audit of 56 AI-, thermal-imaging-, or CWSI-based studies found that 78.6 % either did not explicitly incorporate crop phenology or relied on day of year as a temporal proxy, whereas only 5.4 % explicitly encoded phenological stage. The proposed framework considers phenology explicitly in baseline estimation, threshold setting and data fusion or machine learning for irrigation scheduling; the framework will require multi-year, multi-site field validation before operational use. Future research should prioritise standardised phenology definitions and long-term, multi-location studies to establish and validate stage-specific parameters.","热红外遥感及其衍生的作物水分胁迫指数（crop water stress index, CWSI）等指标可评估作物水分状况并支持精准灌溉。然而，大多数业务化方法和基于人工智能（artificial intelligence, AI）的方法依赖固定的全生育期阈值来解释冠层—空气温差，且往往忽视作物物候的影响。本文综述了葡萄、小麦、玉米、马铃薯及其他若干作物在发育阶段如何影响非水分胁迫基线（non-water-stressed baseline, NWSB）、CWSI阈值和灌溉调度算法的相关证据。综述内容涵盖CWSI理论与估算实践；基线和阈值的作物特异性、物候依赖性行为；基于阈值、机器学习、物联网（Internet of Things, IoT）、数字孪生及联合国粮农组织（Food and Agriculture Organization, FAO）-56等方法在作物物候方面的比较；以及物候感知调度的概念框架。在所综述的作物中，基线行为在整个生长季通常呈系统性变化，CWSI与作物水分状况之间的关系在冠层封垄后总体增强，且在生殖阶段测得的CWSI与产量的关系总体最为密切。对56项基于AI、热成像或CWSI的研究进行的定量审查发现，78.6%的研究要么未明确纳入作物物候，要么依赖年积日作为时间代理变量，而仅5.4%的研究明确编码了物候阶段。所提出的框架在基线估算、阈值设定以及用于灌溉调度的数据融合或机器学习中明确考虑物候；该框架在投入业务应用前尚需多年、多站点的田间验证。未来研究应优先建立标准化的物候定义，并开展长期、多地点研究以建立和验证阶段特异性参数。","Plant Science Today","2026-10-21T00:00:00Z",79,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":397,"relevant":21,"comment":398},9,"系统综述热成像与CWSI在物候期感知灌溉中的应用，含56项研究量化审计，方法学价值突出，但属综述类论文，影响偏学术层面。",[400],{"name":393,"url":390},[26,402,403,404,405],"农业人工智能","遥感","作物水分胁迫","精准灌溉",{"code":294,"slug":298,"name":407,"path":408,"parent_code":124},"水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",[410,411],{"code":254,"slug":255,"name":256,"path":257,"parent_code":35},{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":38,"locked":14,"version":39,"method":40,"evidence":413},{"candidates":414,"agricultural_evidence":44},[415,419,424,428,434,439,446,453,460],{"code":294,"score":192,"supported":44,"title":416,"abstract":417,"tags":418},[298],[297,298],[405],{"code":254,"score":13,"supported":44,"title":420,"abstract":421,"tags":423},[],[249,272,422],"artificial intelligence",[402],{"code":31,"score":397,"supported":44,"title":425,"abstract":426,"tags":427},[],[47,48,49],[],{"code":52,"score":20,"supported":44,"title":429,"abstract":430,"tags":433},[],[431,432],"数字孪生","digital twin",[26],{"code":308,"score":20,"supported":44,"title":435,"abstract":436,"tags":438},[],[403,437],"remote sensing",[403],{"code":440,"score":60,"supported":44,"title":441,"abstract":442,"tags":445},"A2",[],[443,444],"小麦","wheat",[],{"code":447,"score":60,"supported":44,"title":448,"abstract":449,"tags":452},"A3",[],[450,451],"玉米","maize",[],{"code":454,"score":60,"supported":44,"title":455,"abstract":456,"tags":459},"A5",[],[457,458],"马铃薯","potato",[],{"code":461,"score":70,"supported":44,"title":462,"abstract":463,"tags":465},"B2",[],[464],"葡萄",[],[467,468],"热成像 作物水分胁迫","CWSI 灌溉调度","热成像作物水分胁迫-5564","10.14719\u002Fpst.17728",{"doi":470,"openalex_id":472,"authors":473,"venue":393,"cited_by_count":91,"oa_url":390,"card":489,"direction":96,"ingested_from":98},"W7223088921",[474,477,480,483,486],{"name":475,"orcid":476},"R M Jeya","https:\u002F\u002Forcid.org\u002F0009-0001-3621-8533",{"name":478,"orcid":479},"P. C. Prabu","https:\u002F\u002Forcid.org\u002F0000-0002-7237-9481",{"name":481,"orcid":482},"K P Ragunath","https:\u002F\u002Forcid.org\u002F0000-0002-7851-4437",{"name":484,"orcid":485},"P. Kannan","https:\u002F\u002Forcid.org\u002F0000-0001-7003-3535",{"name":487,"orcid":488},"P. M. Shanmugam","https:\u002F\u002Forcid.org\u002F0000-0002-6706-8419",{"tldr":490,"method":491,"finding":492,"direction":493,"opportunity":494},"综述物候期对热成像CWSI阈值的影响，提出物候感知灌溉调度框架。","综述葡萄、小麦、玉米等作物的热遥感CWSI研究，并审计56项AI\u002F热成像研究。","78.6%研究未显式纳入物候，仅5.4%编码物候期；CWSI与产量在生殖期关联最强。","农业遥感与作物表型","可开展多站点多年物候期特异性CWSI阈值标定与标准化物候定义研究。","2026-10-22T11:20:24.526683Z",{"id":497,"title":498,"url":499,"summary":500,"summary_zh":501,"content":9,"source_name":502,"source_url":499,"published_at":394,"category":12,"cover_url":9,"hotness":503,"is_selected":14,"score":91,"score_detail":504,"sources":506,"tags":510,"primary_topic":514,"secondary_topics":515,"classification":516,"search_phrases":532,"slug":535,"view_count":91,"doi":536,"paper":537,"created_at":547},5555,"IoT Security Challenges and Solutions: Threats, Standards and Layered Protection","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23542095","The Internet of Things (IoT) has become an important part of modern life. Smart homes, wearable devices, healthcare systems, industrial machines, and smart agriculture use connected devices to collect and exchange information. Although IoT makes many activities easier, it also introduces security and privacy risks. Weak passwords, insecure communication, outdated firmware, unauthorized access, and data leakage can expose devices and users to cyberattacks. This paper examines major security challenges faced by IoT systems and discusses practical solutions based on established cybersecurity guidance. It synthesizes three complementary perspectives: academic survey research on IoT security, the National Institute of Standards and Technology (NIST) IoT security baseline, and the OWASP Internet of Things security guidance. The study explains common threats, reviews relevant standards, and proposes a layered protection model covering devices, networks, applications, data, and system management. It concludes that IoT security should be considered throughout the device lifecycle rather than added only after a problem occurs","物联网（IoT）已成为现代生活的重要组成部分。智能家居、可穿戴设备、医疗保健系统、工业机械和智慧农业均利用互联设备采集和交换信息。尽管物联网使许多活动更加便捷，但也带来了安全与隐私风险。弱密码、不安全的通信、过时的固件、未经授权的访问以及数据泄露，都可能使设备和用户暴露于网络攻击之中。本文考察了物联网系统面临的主要安全挑战，并基于既有的网络安全指南讨论了切实可行的解决方案。研究综合了三个互补视角：关于物联网安全的学术调查研究、美国国家标准与技术研究院（NIST）物联网安全基线，以及OWASP物联网安全指南。本研究阐释了常见威胁，梳理了相关标准，并提出了一种涵盖设备、网络、应用、数据和系统管理的分层防护模型。研究结论认为，物联网安全应在设备全生命周期中加以考虑，而非仅在问题出现后才予以补加。","Zenodo (CERN European Organization for Nuclear Research)",25,{"impact":91,"substance":91,"depth":91,"authority":91,"freshness":91,"relevant":91,"comment":505},"通用物联网安全综述，仅泛泛提及智慧农业，与三农及农业信息化主题关联薄弱，不建议入选。",[507,508],{"name":502,"url":499},{"name":502,"url":509},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23541648",[26,511,512,513],"网络安全","物联网安全","NIST标准",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":517},{"candidates":518,"agricultural_evidence":44},[519,523,527],{"code":31,"score":243,"supported":44,"title":520,"abstract":521,"tags":522},[49],[47,48,49],[],{"code":52,"score":20,"supported":44,"title":524,"abstract":525,"tags":526},[],[26,194],[26],{"code":528,"score":21,"supported":14,"title":529,"abstract":530,"tags":531},"I6",[],[],[511],[533,534],"物联网安全 智慧农业 网络安全 NIST标准","物联网安全 智慧农业","物联网安全智慧农业网络安全NIST标准-5555","10.5281\u002Fzenodo.23542095",{"doi":536,"openalex_id":538,"authors":539,"venue":502,"cited_by_count":91,"oa_url":499,"card":542,"direction":96,"ingested_from":98},"W7223144955",[540],{"name":541,"orcid":9},"himesh suryawanshi",{"tldr":543,"method":544,"finding":545,"direction":96,"opportunity":546},"综述物联网安全挑战，结合学术与NIST、OWASP标准提出分层防护模型。","综合学术综述、NIST物联网安全基线与OWASP指南，构建分层防护模型。","物联网安全需覆盖设备全生命周期，而非事后补救。","可将通用分层防护模型落地到农业物联网场景，研究低成本设备与田间网络的轻量安全方案。","2026-10-22T11:20:18.423667Z"]