USING A USER-CENTERED FRAMEWORK, WE CAN ASSESS THE USABILITY OF E-AGRICULTURE APPLICATIONS

Authors

  • Mahanz Sadie Department of Computer Engineering, Ramhormoz Branch, Islamic Azad University, Ram-hormoz, Iran Author
  • Hanane Aznaoui LAMAI Laboratory, Faculty of Sciences and Techniques, Cady Ayyad University, Marra-kech, Morocco Author

DOI:

https://doi.org/10.36755/jac.v1i1.48

Keywords:

Usability, Crops production, framework , Usability Mobile, E-agriculture

Abstract

E-agriculture is a growing and well-known field with a focus on the development of rural regions and farming through value-added information and improved communication systems. With the widespread usage of mobile devices today and its applicability in every aspect of life, including agriculture. In Pakistan, there are several different agriculture-related apps in use. Usability emerges as a key determinant of whether users are generally utilising the new technology to create the most effective e-agriculture application software. Since individuals are not properly aware of the digital data options, usability in agriculture continues to be a challenging issue. The present deficiencies in agriculture mobile apps, such as memo-rability, learnability, operability fault handling, and flexi-bility, are not covered by the previous usability paradigm. The goal of this study is to evaluate the usability of e-agricultural mobile applications from the user's point of view and to provide a usability framework that identifies the most significant gaps currently present in agriculture apps. The suggested framework can be used to create a cutting-edge mobile app with features for agriculture. For this reason, two of the most popular agriculture apps, Bakhabar Kissan and agriculture Extension, are chosen to be measured and evaluated for their usability on our suggested framework from the user's perspective in order to fully utilise the apps and subsequently increase crop production to meet the needs of the nation.

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References

[1] Ullah, A., Salam, A., El Raoui, H., Sebai, D., & Rafie, M. (2022). Towards more accurate iris recognition system by using hybrid approach for feature extraction along with classifier. Int J Reconfigurable & Embedded Syst, 11(1), 59-70. DOI: https://doi.org/10.11591/ijres.v11.i1.pp59-70

[2] Sebai, D., & Shah, A. U. (2022). Semantic-oriented learning-based image compression by Only-Train-Once quantized autoencoders. Signal, Image and Video Processing, 1-9 DOI: https://doi.org/10.1007/s11760-022-02231-1

[3] Ouhame, S., Hadi, Y., & Ullah, A. (2021). An efficient forecasting approach for resource utilization in cloud data center using CNN-LSTM model. Neural Computing and Applications, 33(16), 10043-10055. DOI: https://doi.org/10.1007/s00521-021-05770-9

[4] Khansa, L., Ma, X., Liginlal, D., & Kim, S. S. (2015). Understanding members’ active participation in online question-and-answer communities: A theory and empirical analysis. Journal of Management Information Systems, 32(2), 162-203. DOI: https://doi.org/10.1080/07421222.2015.1063293

[5] Katusiime, J., & Pinkwart, N. (2019). A review of privacy and usability issues in mobile health systems: Role of external factors. Health informatics journal, 25(3), 935-950. DOI: https://doi.org/10.1177/1460458217733121

[6] Karetsos, S., Costopoulou, C., & Sideridis, A. (2014). Developing a smartphone app for m-government in agriculture. Agrárinformatika/Journal of Agricultural Informatics, 5(1), 1-8. DOI: https://doi.org/10.17700/jai.2014.5.1.129

[7] Johnson, N., Kumar, M. S., & Dhannia, T. (2020). A study on the significance of smart IoT sensors and Data science in Digital agriculture. Paper presented at the 2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA), 80-88. DOI: https://doi.org/10.1109/ACCTHPA49271.2020.9213207

[8] Jake-Schoffman, D. E., Silfee, V. J., Waring, M. E., Boudreaux, E. D., Sadasivam, R. S., Mullen, S. P., . . . Bennett, G. G. (2017). Methods for evaluating the content, usability, and efficacy of commercial mobile health apps. JMIR mHealth and uHealth, 5(12), e8758. DOI: https://doi.org/10.2196/mhealth.8758

[9] Ismail, N., Ahmad, F., Kamaruddin, N., & Ibrahim, R. (2016). A review on usability issues in mobile applications. IOSR Journal Of Mobile Computing and Application, 3(3), 47-52. DOI: https://doi.org/10.9790/0050-03045261

[10] Iribarren, S. J., Schnall, R., Stone, P. W., & Carballo-Diéguez, A. (2016). Smartphone applications to support tuberculosis prevention and treatment: review and evaluation. JMIR mHealth and uHealth, 4(2), e5022. DOI: https://doi.org/10.2196/mhealth.5022

[11] Hanane, A., Ullah, A., & Raghay, S. (2021). Enhanced GAF protocol based on graph theory to optimize energy efficiency and lifetime in WSN technology. International Journal of Intelligent Unmanned Systems. DOI: https://doi.org/10.1108/IJIUS-08-2021-0096

[12] Haapala, H., Nurkka, P., Kaustell, K., Mattila, T., & Suutarinen, J. (2006). Usability as a challenge in agricultural engineering. Suomen Maataloustieteellisen Seuran Tiedote 21, 1–7. DOI: https://doi.org/10.33354/smst.76058

[13] Goyal, S., Morita, P., Lewis, G. F., Yu, C., Seto, E., & Cafazzo, J. A. (2016). The systematic design of a behavioural mobile health application for the self-management of type 2 diabetes. Canadian journal of diabetes, 40(1), 95-104. DOI: https://doi.org/10.1016/j.jcjd.2015.06.007

[14] Gawade, S., Raikar, K., & Chopade, S. (2017). Usability evaluation of agricultural websites. Paper presented at the 4th International Conference on “Computing for Sustainable Global Development”(INDIACom-2017), Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi, 136-141.

[15] Garcia, E., Martin, C., Garcia, A., Harrison, R., & Flood, D. (2011). Systematic analysis of mobile diabetes management applications on different platforms. Paper presented at the Symposium of the Austrian HCI and Usability Engineering Group, 7058, 379-396. DOI: https://doi.org/10.1007/978-3-642-25364-5_27

[16] Gao, C., Zhou, L., Liu, Z., Wang, H., & Bowers, B. (2017). Mobile application for diabetes self-management in China: Do they fit for older adults? International journal of medical informatics, 101, 68-74. DOI: https://doi.org/10.1016/j.ijmedinf.2017.02.005

[17] Costopoulou, C., Ntaliani, M., & Karetsos, S. (2016). Studying mobile apps for agriculture. Journal of Mobile Computing & Application 3(6), 44-49.

[18] Alam, T., Ullah, A., & Benaida, M. (2022). Deep reinforcement learning approach for computation offloading in blockchain-enabled communications systems. Journal of Ambient Intelligence and Humanized Computing, 1-14. DOI: https://doi.org/10.1007/s12652-021-03663-2

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Published

23-12-2023

How to Cite

USING A USER-CENTERED FRAMEWORK, WE CAN ASSESS THE USABILITY OF E-AGRICULTURE APPLICATIONS. (2023). Journal of Advancement in Computing, 1(1), 14-20. https://doi.org/10.36755/jac.v1i1.48