Performance evaluation of IoT-based service system for monitoring nutritional deficiencies in plants

被引:11
作者
Andrianto, Heri [1 ]
Suhardi, Ahmad [1 ]
Faizal, Ahmad [2 ]
Kurniawan, Novianto Budi [3 ]
Aji, Dimas Praja Purwa [1 ]
机构
[1] Inst Teknol Bandung, Sch Elect Engn & Informat, Bandung 40132, Indonesia
[2] Inst Teknol Bandung, Sch Life Sci & Technol, Bandung 40132, Indonesia
[3] Stat Indonesia, Directorate Stat Informat Syst, Jakarta 10710, Indonesia
关键词
Dependability; Fertilization recommendation; Internet of Things; Nutritional deficiencies; Service system platform; System engineering; LEAF CHLOROPHYLL CONCENTRATION; METER; MANAGEMENT; VALUES; COLOR;
D O I
10.1016/j.inpa.2021.10.001
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
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.(c) 2021 China Agricultural University. Production and hosting by Elsevier B.V. on behalf of KeAi. This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:52 / 70
页数:19
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