面向联网精准农业农场的AI云边架构设计与评估
Design and Evaluation of an AI-Enabled Cloud-Edge Architecture for Connected Precision Agriculture Farms
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中文总结 AI 辅助
针对番茄病害人工监测难以适配大规模农场的问题，本文提出集成IoT、UAV等的AI云边架构，部署TensorFlow模型实现番茄病害92%-95%的实时检测，助力精准农业。
中文摘要 AI 辅助
植物病害在全球范围内造成显著产量损失，其中番茄作物尤其易受早疫病、晚疫病和叶霉病侵害。人工监测仅适用于小型农场，规模扩大后便难以实施。为解决此局限，本文提出一种人工智能（AI）支持的云边架构用于自主作物监测，该架构集成物联网（IoT）传感器、无人机（UAV）、深度学习、基于Azure IoT Hub的云分析，以及多平台（移动应用、网页应用、嵌入式边缘设备平台）接口，实现番茄病害的实时检测。训练与验证阶段使用PlantVillage、Kaggle等公开数据集，在自建数据集上训练的TensorFlow模型被部署至移动、网页及边缘设备平台。实验结果显示，检测准确率约为92%-95%，在不同环境和设备平台上性能稳定。该系统提升了病害检测准确率，降低了对人工检查的依赖，支持及时干预，从而助力可持续、联网的精准农业农场。
英文摘要
Plant diseases cause significant yield losses worldwide, with tomato crops particularly susceptible to early blight, late blight, and leaf mold. Manual monitoring is practical only for small-scale farms and becomes unmanageable at larger scales. To tackle this limitation, an artificial intelligence (AI) enabled cloud-edge architecture is proposed for autonomous crop monitoring. This proposed architecture integrates Internet of Things (IoT) sensors, unmanned aerial vehicles (UAVs), deep learning, Azure IoT Hub-based cloud analytics, and multi-platform (mobile app, web app, and embedded edge device platform) interfaces to enable real-time detection of tomato diseases. For training and validation, we used publicly available datasets, such as PlantVillage and Kaggle. A TensorFlow model trained on a collected dataset is deployed across mobile, web, and edge-device platforms. Experimental results show detection effectiveness around 92-95%, with consistent performance over diverse environments and device platforms. The proposed system improves disease detection effectiveness, lowers dependence on manual inspection, and enables prompt interventions, thereby supporting sustainable, connected precision agriculture farms.
发表机构
- Autonomous Robotics Systems Limited（自主机器人系统有限公司）
- University of Hyderabad（海得拉巴大学）
- ThoughtGreen Technologies Private Limited（ThoughtGreen科技私人有限公司）
- Ideabytes Software India Private Limited（Ideabytes软件印度私人有限公司）
- Georgia Institute of Technology（佐治亚理工学院）
- Tata Consultancy Services（塔塔咨询服务公司）
- EPAM India（埃培智印度分公司）
- Kaveri University（卡弗里大学）
- University of Malaya（马来亚大学）
机构由 AI 辅助整理，请以论文原文为准。
