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通过物联网和人工智能驱动技术赋予垂直农业权力:全面审查

Ajit Singh Rathor¹, Sushabhan Choudhury¹, Abhinav Sharma¹

¹Department of Electrical & Electronics Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand, India.

|August 19, 2024

概括

垂直农业 (VF) 为应对粮食供应挑战提供了一个可持续的解决方案. 整合人工智能 (AI) 和物联网 (IoT) 增强了VF系统中的作物产量预测,疾病检测和资源管理.

科学领域:

农业技术农业技术
人工智能在农业中的应用
可持续的粮食生产可持续的粮食生产

背景情况:

全球人口不断增长使传统的粮食供应受到压力.
垂直农业 (VF) 为传统农业提供了一种水和土地效率高的替代方案.
城市地区面临着土地稀缺和农业高成本的挑战.

研究的目的:

分析机器学习 (ML) 和物联网 (IoT) 在垂直农业 (VF) 的应用.
探索基于人工智能的技术如何应对虚拟机的挑战,例如监控和诊断.
评估ML和物联网在VF系统中提高作物质量和生产的潜力.

主要方法:

研究用于作物图像分类的计算机视觉技术,以预测产量和疾病.
分析ML算法 (包括深度学习) 和物联网设备在VR中的集成.
审查基于人工智能的控制技术,用于同时监测多个指标.

主要成果:

机器学习和物联网应用在疾病检测和使用图像处理预测作物产量方面表现有前途.
人工智能驱动的系统可以优化VF中的营养和灌控制管理.
实施的ML和物联网系统有可能提高产品质量和长期生产.

结论:

人工智能,机器学习和物联网对于克服垂直农业目前的局限性至关重要.
这些技术可以显著提高城市农业的效率,生产力和可持续性.
进一步评估基于知识的VF系统中的ML和IoT是有必要的,以了解结果和局限性.

关键词:

人工智能的人工智能是人工智能.深度学习是一种深度学习.疾病检测检测疾病检测培技术是一种水培技术.这就是为什么物联网物联网物联网.机器学习是机器学习.垂直农业是一种垂直农业.预测收益率的预测

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