Development of an Android Mobile App for Real Time Maize Stem Borers Monitoring in Precision Farming
DOI:
https://doi.org/10.24203/ijcit.v10i6.181Keywords:
Android Studio, Kotlin, Maize Stemborers, Spodoptera SpeciesAbstract
Development of an Android mobile app for real time maize stem borers’ monitoring in precision agriculture is presented. In farmland, cultivated maize requires farmers’ constant care and monitoring during the developing stage to avoid sudden attack of insect pests such as stem borers in the field. The maize monitoring process taken by farmers to ensure attack free and healthy growth is very strenuous and time consuming. The sudden invasion of the Spodoptera species (stem borers) to maize farm early 2016 caused huge loss to farmers and imposed food scarcity in the land. These species are hardly distinguished from one another by farmers in the farm because they look alike in appearance. Rural farmers do not know the right insecticides to apply for the effective control of these species. These issues kept on lingering and now have become serious concern to farmers. Hence, this work is to bridge the gap by providing android mobile app that would enable farmers to effectively monitor these species remotely. The mobile app architecture consists of various sections such as captured insects, categories of spodoptera species, insect pest population plots, determination of economic injury level (EIL) and economic threshold (ET), and control measure was successfully designed. The mobile app structure and behavior were also designed using Unified Modeling Language (UML). The maize Stem borers App was developed in android studio using Kotlin programming language. The App is linked to the cloud server where all the captured and recognized species are stored for downloading and farmers’ visualization. The Internet of Things (IoT) hardware was setup in the maize farm which captured these targeted insect pests, processed via Nividia Jetson Nano and sent to the cloud server. The mobile App synchronized successfully with the cloud server and could download stored maize insect pests in the farmer’s Android phone.
References
P. Richard, “Armyworm: The hungry caterpillar threatening a global food crisis”, 2017, Available online at: www.theguardian.com/global-development-professionals network/2017/may/16/armyworms-the-hungry-caterpillar-threatening-a-global-food-crisis, accessed 12 November 2019.
B. Anna‐Maria, J. K. Karl, M. Joyce, and H. F. Christine,
“Defining biotechnological solutions for insect control in sub-saharan African”, Food and Energy Security (WILEY), pp. 1-21, 2019. Available at:www.onlinelibrary.wiley.com/doi/epdf/10.1002/fes3.191>, accessed 13 December 2019.
H. C. Simon, N. Mayumbo, P. Jackson , and S. Philemon , “An Application of Machine Learning Algorithms in Automated Identification and Capturing of Fall Armyworm (FAW) Moths in the Field”, Proceedings of the Information and Communication Technology Society of Zambia (ICTSZ) International Conference in ICTS (Icict2018) - Lusaka, Zambia, 2018.
Z.C.Qiang, S. C. Kuek, A. Dymond, and S. Esselaar, “Mobile Applications for Agriculture and Rural Development”, ICT Sector Unit World Bank, 2020.
Biswajit S., A. Kowsar, B. Premankur, and C. Amit, “Development of m-Sahayak- the Innovative Android based Application for Real-time Assistance in Indian Agriculture and Health Sectors”, The Sixth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, UBICOMM., pp.133-137, 2012.
R.L. Meena1, B. Jirli, M. Kanwat and N.K. Meena, “Mobile Applications for Agriculture and Allied Sector”,International Journal of Current Microbiology and Applied Sciences (IJCMAS), vol.7, no.2, pp. 2317-2326, 2018.
K.Sotiris, C. Constantina, and S. Alexander, “Developing a smartphone app for m-government in agriculture”, Journal of Agricultural Informatic, vol.5, no. 1, pp. 1-8, July 2014.
T. Ankur, K. P. Ravi , L. C. De Rampal, K.S.Rakesh,and D.R. Singh
“Mobile App - Android application on ‘Orchid Farming” based on North Eastern States of India”, Short communication, Indian J. Hort., vol.76, no.4, pp.752-756, December 2019.
M. Priti, S. Mukul, M. Timothy, and K. Rakesh, “Mobile detection of crop diseases for agricultural yield management”, Real-Time Image Processing and Deep Learning, SPIE Defense + Commercial Sensing, Baltimore, Maryland, United States, vol. 10996, pp.2-14, May 2019.
P. Pawan, ‘Insights to Agile Methodologies for Software Development’, 2019, , accessed 10 January 2020.
Queppelin, “Agile Methodologies for Mobile Application Development”, 2016, , accessed 10 January 2020.
B. Subham, K. Aditi, M. Madhuleena, and B. Madhurima,“A Comparative Study: Java Vs Kotlin Programming in Android Application Development”, International Journal of Advanced Research in Computer Science, vol.9, no.3, pp.41-45, 2018.
O. Janis and D.Uldis, “Unified Modeling Language”, 2017, <https://www.sciencedirect.com/topics/computer-science/unified-modeling-language>, accessed 5 December 2019.
B.M. Prasanna, J.E. Huesing, R. Eddy, and V.M. Peschkem, “Fall Armyworm in Africa: A guide for Integrated Pest management”, 1st edn, feed the future: the U.S. Government’s Global Hunger & Food Security Initiative, 2018.
S. Tadele and G. Emana, “Determination of the economic threshold level of tomato leaf miner, Tuta absoluta Meyrick (Lepidoptera: Gelechiidae) on tomato plant under glasshouse conditions”, Journal of Horticulture and Forestry, vol.10, no.2, pp. 9-16, 2018.
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Ezeofor Chukwunazo Joseph
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The articles published in International Journal of Computer and Information Technology (IJCIT) is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.