Development of a mobile computing framework to aid decision-making on organic fertilizer management using a crop growth model

Hyun, Sung Pil; Yang, Soo Jung; Kim, Junhwan; Kim, Kwang S.; Shin, Jae Hoon; Lee, Sang Min; Lee, Byun-Woo; Beresford, R.; Fleisher, David H.

doi:10.1016/j.compag.2020.105936

Cited by 9 publications

(1 citation statement)

References 25 publications

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“…Vitale (2014) reports a mobile application based DSS for local public transport service. Hyun et al (2021) report a software development framework to facilitate the development of a decision support system based on a mobile computing platform. The proposed is framework is used for organic fertilizer management in organic farming.…”

Section: Literature Reviewmentioning

confidence: 99%

A mobile application-based decision support system for routing and decision making problems

Bolat,

Bedel,

Çetinkurt

et al. 2023

Journal of Advanced Research in Natural and Applied Sciences

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Industry 4.0 applications and related topics open up new opportunities in problem solving for states, companies, production systems and individuals. These developments make data gathering and processing easier. Moreover, mobile devices offer more sophisticated approaches since they can gather data and process the collected data by various algorithms, which are embedded to devices via applications. Appro-priate problem related algorithms can be coded and they can be deployed to mobile devices to increase mobility and ease of use for end users. In the present paper, a prototype of mobile application-based decision support system is developed for industrial systems including routing and multi-criteria decision making problems. The developed application is comprised of several modules including registry and signup modules as well as problem solving modules. Problem solving modules can gather data from both user and outer sources such as GPS in order to solve both routing problems and multi-criteria decision-making problems. The mentioned application adopts a Simulated Annealing Algorithm to find promising routes for the users, while multi-criteria decision-making module uses both Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on the choice of the users. The proposed application is coded on Java and Python due to their strong integration capabilities with Android. According the results of the developed prototype, the proposed application offer promising results and ease of use.

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Section: Literature Reviewmentioning

confidence: 99%