基于物联网的植物营养缺乏症监测服务系统性能评价

IF 7.7 Q1 AGRICULTURE, MULTIDISCIPLINARY Information Processing in Agriculture Pub Date : 2023-03-01 DOI:10.1016/j.inpa.2021.10.001
Heri Andrianto , Suhardi , Ahmad Faizal , Novianto Budi Kurniawan , Dimas Praja Purwa Aji
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引用次数: 7

摘要

本研究旨在开发并评估基于物联网(IoT)的植物营养缺乏症监测和肥料建议服务系统平台的性能。这项工作与以前的工作有两个明显的不同;即,该服务系统平台基于物联网,采用系统工程方法开发,并使用可靠性对其性能进行了评估。我们成功开发并集成了基于物联网的服务系统平台和叶绿素计。我们还使用JMeter软件对业务系统平台的性能进行了测试。从五个测试变量(可靠性、可用性、完整性、可维护性和安全性)测量的可靠性值显示为0.97,这表示系统在正常操作条件下不会向用户提供服务的信心水平非常高。从未来的角度来看,该平台可以作为一种替代服务,用于监测植物的营养缺乏,并提供施肥建议,以提高产量,降低肥料成本,防止使用过量的肥料,造成环境污染。
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Performance evaluation of IoT-based service system for monitoring nutritional deficiencies in plants

This study aimed to develop and evaluate the performance of a service system platform based on the Internet of Things (IoT) for monitoring nutritional deficiencies in plants and providing fertilizer recommendations. There are two distinct differences between this work and previous ones; namely, this service system platform has been developed based on IoT using a system engineering approach and its performance has been evaluated using dependability. We have successfully developed and integrated a service system platform and chlorophyll meter that is based on IoT. We have also successfully tested the performance of the service system platform using the JMeter software. The dependability value measured from the five tested variables (reliability, availability, integrity, maintainability, and safety) showed a value of 0.97 which represents a very good level of system confidence in not failing to deliver services to users under normal operational conditions. From a future perspective, this platform can be used as an alternative service to monitor nutrient deficiencies in plants and provide fertilization recommendations to increase yields, reduce fertilizer costs, and prevent the use of excessive fertilizers, which can cause environmental pollution.

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来源期刊
Information Processing in Agriculture
Information Processing in Agriculture Agricultural and Biological Sciences-Animal Science and Zoology
CiteScore
21.10
自引率
0.00%
发文量
80
期刊介绍: Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining
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