Optimized RTPS platform for IIoT based smart farming systems

Basem Almadani, Saud Mohammad Mostafa
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引用次数: 2

Abstract

With the ever-growing population, food and water demands have risen exponentially. Almost 80-85% of food is produced by agriculture but the rise in demand needs to be met by an increase in food production. The agriculture sector tends to tackle this issue by incorporating the Industrial Internet of Things (IIoT) and cloud technologies to improve productivity and reduce wastage of resources needed for it. The prime target of incorporation of these technologies would be to facilitate farmers to grow crops and raise livestock with ease and lower cost with increasing profits. Smart farming systems can comprise of one or more sub-systems that are automated using IIoT technology and processing is done either in local server or cloud. Most researchers work on individual sub-system and improve the performance providing local optimization. These sub-systems can have different vendors and integration is quite difficult at times. Therefore, we propose to use Data Distribution Service (DDS) middleware to integrate these heterogeneous sub-systems and provide high performance with low latency system. In this paper, we introduce a novel approach to tackle the issue of heterogeneity and provide global optimization. A suitable mathematical model for our proposed system is given and experiments are conducted to show the efficiency of the system in terms of throughput and delay.
优化基于工业物联网的智能农业系统的RTPS平台
随着人口的不断增长,对食物和水的需求呈指数级增长。近80-85%的粮食是由农业生产的,但需求的增加需要通过粮食产量的增加来满足。农业部门倾向于通过结合工业物联网(IIoT)和云技术来解决这个问题,以提高生产力并减少所需资源的浪费。结合这些技术的主要目标将是帮助农民轻松种植作物和饲养牲畜,降低成本并增加利润。智能农业系统可以由一个或多个子系统组成,这些子系统使用工业物联网技术实现自动化,处理工作在本地服务器或云中完成。大多数研究人员都是在单个子系统上进行工作,并通过局部优化来提高性能。这些子系统可以有不同的供应商,有时集成相当困难。因此,我们建议使用数据分布服务(DDS)中间件来集成这些异构子系统,以提供高性能和低延迟的系统。在本文中,我们引入了一种新的方法来解决异质性问题并提供全局优化。给出了一个合适的数学模型,并进行了实验,以证明系统在吞吐量和延迟方面的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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