Determination of Water Stress in Okra Plants Using Canopy Temperature Measurement by Infrared Thermometer
用红外测温仪测秋葵冠层温度并结合随机森林，实现水分胁迫的早期无损分类。
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Spatial variability of soil fertility indicators using GIS for sustainable land management in Banaskantha district western India
用GIS与多元统计评估印度半干旱区Banaskantha土壤肥力指标的空间变异。
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AgriMAC: An Attention Based Multimodal Deep Clustering Framework for Rice Health Assessment
提出无监督多模态聚类框架AgriMAC，融合无人机NDVI、IoT土壤与气象数据评估水稻健康。
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AshGdNutDefAM: Machine-learning-based multi-feature framework for nutrient deficiency detection and classification in Ash gourd Plant
提出AshGdNutDefAM多特征机器学习框架，自动检测和分类冬瓜缺镁缺铁症状。
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Tradeoff between economic and environmental assessment of paddy-wheat and maize-wheat cropping system in Indian Punjab: a pathway to sustainable agriculture
比较印度旁遮普省稻麦与玉米麦轮作的经济环境权衡，评估玉米麦作为替代的可持续性。
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Deep learning-based classification of wet direct seeded rice, broadcasted direct seeded rice and transplanted rice using drone imagery for precision agriculture
用无人机可见光影像和深度学习模型区分直播稻、湿直播稻与移栽稻三种水稻种植方式。
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Machine Learning-Based Prediction of Soil Moisture in Sikkim's High-Rainfall Zones Using Multimodal Remote Sensing Data
用多模态遥感与机器学习预测印度锡金高降雨区表层土壤水分。
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Empowering India's Digital Future through Artificial Intelligence in Geography
本文探讨地理空间人工智能（GeoAI）如何推动印度数字治理与可持续发展。
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MridAI: Autonomous Edge-to-Conversational IoT for Democratising Precision Agriculture via Neuro-Symbolic Telemetry
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。
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Coffee phytobiome dynamics: integrating multitrophic interactions and plant physiology for climate-resilient production
综述咖啡植物微生物组与多营养级互作，提出整合植物生理与微生物组提升气候韧性生产。
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Future-proofing the plantation sector for wellbeing and welfare: Insights from PLACROSYM XXVI
综述PLACROSYM XXVI研讨会成果，提出印度种植园部门面向2047的科技驱动与碳智能转型路线
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Integrating Artificial Intelligence and IoT for Precision Farming: A Review of Agriculture 4.0 Technologies, Applications, and Challenges
综述AI与IoT在精准农业中的集成技术、应用与挑战，提出未来研究方向。
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AI-Driven Smart Agriculture And Food Security In Developing Countries: A Comparative Perspective
比较六国AI驱动智慧农业对粮食安全的影响，发现数字基础设施和AI准备度是关键。
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Smart Crop Recommendation System
提出智能作物推荐系统，结合AI与实时天气，推荐作物并检测病害。
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IoT-Based Soil Condition Monitoring System for Supporting Precision and Sustainable Agriculture in West Java
开发基于IoT的土壤监测系统，支持西爪哇精准可持续农业，提高灌溉效率并增产。
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Application of Precision Agriculture and IoT-Based Smart Irrigation in Greenhouse Vegetable Production
原文标题:Application of Precision Agriculture and IoT-Based Smart Irrigation in Greenhouse Vegetable Production。作者:Zeeshan Ahmed、Muhammad Taimur Maqbool Muhammad、Abbas Khan Muhammad、Zain Ul Abideen、Abdul Haq。DOI: 10.63163/jpehss.v4i1.1226。该综述综合分析了精准农业(PA)和基于物联网(IoT)的智能灌溉在温室蔬菜生产中的集成,涉及土壤湿度、EC、pH、微气候监测器等物联网传感器与数据分析(AI/ML模型)及自动执行器在番茄、黄瓜、辣椒等作物实时资源管理中的整合。关键组件包括使用ZigBee/LoRa协议的无线传感器网络、低延迟边缘/雾计算和预测算法(如LSTM、SVM),可减少20-50%用水量,同时提高10-30%产量和养分效率。来自中国、欧洲和印度的案例展示了变量灌溉(VRI)和施肥系统的实际应用,实现高达40%的能源节约和最小化淋失。
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