Evaluating Smart Greenhouse Viability Through Engineering Design and Software Cost Modelling

Author:

Nugroho A P,Nasrul R M,Sutiarso L,Falah M A F,Dzaky M A F

Abstract

Abstract Introducing smart greenhouse technology in tropical agricultural in Indonesia has the potential to bring about substantial advantages, such as higher crop yields, decreased water consumption, and enhanced food security. Nevertheless, the feasibility of this technology must be evaluated before it can be widely adopted. The objectives of this study were to evaluate the viability of smart greenhouse technology in using the engineering economics and software cost estimation model (SCEM), consider the fixed and variable cost for operational, and effort for developing the supporting modules. The findings of this study suggest that the investment in Smart Greenhouse technology is economically viable and financially justified. The Internal Rate of Return (IRR) of 11% exceeds the 10% discount rate, Benefit Cost Ratio (BCR) of 1.16 signifies that the discounted value of benefits surpasses costs over the project lifetime, with the economics return 16% higher than the break-even level. The Smart Greenhouse investment will become profitable after five years, with positive returns above the minimum threshold. The SCEM analysis shows that the software development workload is significant for some modules, such as Smart Agri Engrow and Smart Agri Nutrigrow. These software cost estimates can now be used for budgeting, planning, and assessing the feasibility of the Smart Greenhouse technology implementation.

Publisher

IOP Publishing

Reference12 articles.

1. The state and food security discourses of Indonesia: feeding the bangsa;Neilson;Geographical Research,2017

2. Farmers’ knowledge and practice regarding good agricultural practices (GAP) on safe pesticide usage in Indonesia;Istriningsih;Heliyon,2022

3. Appropriate adaptation of precision agriculture technology in open field cultivation in tropics;Nugroho;IOP Conference Series: Earth and Environmental Science,2019

4. IoT-based Smart Greenhouse with Disease Prediction using Deep Learning;Fatima;International Journal of Advanced Computer Science and Applications,2021

5. A methodology for model-based greenhouse design: Part 4, economic evaluation of different greenhouse designs: A Spanish case;Vanthoor;Biosyst Eng,2012

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3