Integration of Mechatronic and Automation Technology in Sustainable Farming for Achieving Food Security in Kenya
##plugins.themes.bootstrap3.article.main##
Advanced farming that involves modern technology, especially in large scale, can aid in attaining food security for any given country. In this study, the prospects of automation, mechatronics and the developments for modern farming are explored for sustainable agriculture in Kenya. For the purpose of technological diversification, the use of mechatronics and automation in various smart farming technological systems is presented. It is possible to step up development in realizing food security in Kenya with the use of these modern farming techniques among other similar technologies. The use Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IOT), Global System for Mobile (GSM) Communications, photovoltaic thermal solar systems, cloud data storage and radio frequency identification (RFID) technologies that are utilized in autonomous tractors, drone farming, livestock monitoring, smart poultry, dairy, irrigation, greenhouse, and farm warehouse systems are discussed. These advances can result in significant increase in production, efficiency, profits, as well as better monitoring, surveillance and tracking in the farm. Finally, the impact of these technologies on agriculture in relation to sustainable food security is explored, where it is demonstrated that mechatronic farm automation integrated with the mobile applications can offer better farm monitoring, increase yields as well as contribute towards better land utilization.
Downloads
References
-
Ericksen PJ, Ingram JSI, Liverman DM. Food security and global environmental change: emerging challenges. Environmental Science & Policy, 2009 Jun;12(4):373?377.
Google Scholar
1
-
The future of food and agriculture. Alternative pathways to 2050 |Policy Support and Governance| Food and Agriculture Organization of the United Nations. [Accessed 2021 May 14].
Google Scholar
2
-
ACTED. 2020 Global Hunger Index: A year of crisis slows progress towards hunger eradication. 2020 [Accessed 2021 May 24].
Google Scholar
3
-
GFSI. Global Food Security. [Accessed 2021 May 24].
Google Scholar
4
-
Shamshiri R, Kalantari F, Ting K, Thorp K, Hameed I, Weltzien C, et al. Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture. International Journal of Agricultural and Biological Engineering, 2018 Jan 31;11.
Google Scholar
5
-
Big4. The Big 4 - Empowering the Nation [Internet]. Available from: https://big4.delivery.go.ke/ [Accessed 2021 May 24].
Google Scholar
6
-
Government of Kenya. Monitoring. And planning in Kenya. https://monitoring.planning.go.ke/wp-content/uploads/2020/10/Big-Four-Agenda-Report-2018_19.pdf [Accessed 2021 May 24].
Google Scholar
7
-
Xie L, Luo B, Zhong W. How Are Smallholder Farmers Involved in Digital Agriculture in Developing Countries: A Case Study from China. Land. 2021 Mar;10(3):245. [Accessed 13th May 2021].
Google Scholar
8
-
Pesce M, Kirova M, Soma K, Bogaardt MJ, Poppe K, Thurston C, et al. Research for AGRI Committee?Impacts of the digital economy on the food-chain and the CAP. European Parliament, Policy Department for Structural and Cohesion Policies: Brussels, Belgium. 2019. https://www.europarl.europa.eu/thinktank/en/document/IPOL_STU(2019) 629192 [Accessed 28th May 2021].
Google Scholar
9
-
Oliverwyman. Agriculture 4.0 ? The Future Of Farming Technology https://www.oliverwyman.com/our-expertise/insights/2018/feb/agriculture-4-0--the-future-of-farming-technology.html [Accessed 2021 May 27].
Google Scholar
10
-
Jha K, Doshi A, Patel P, Shah M. A comprehensive review on automation in agriculture using artificial intelligence. Artificial Intelligence in Agriculture, 2019 Jun.
Google Scholar
11
-
Shockley J, Dillon C, Shearer S. An economic feasibility assessment of autonomous field machinery in grain crop production. Precision Agriculture, 2019.
Google Scholar
12
-
Islam MM, Sourov Tonmoy S, Quayum S, Sarker AR, Umme Hani S, Mannan MA. Smart Poultry Farm Incorporating GSM and IoT. In: 2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST). 2019. p. 277?80.
Google Scholar
13
-
EOS. Precision Agriculture: How To Improve Farming With Satellite Data 2019. https://eos.com/blog/precision-agriculture-from-concept-to-practice/ [Accessed 2021 May 27].
Google Scholar
14
-
Lunner-Kolstrup C, H?rndahl T, Karttunen JP. Farm operators? experiences of advanced technology and automation in Swedish agriculture: a pilot study. Journal of Agromedicine, 2018 Jul 3;23(3):215?26.
Google Scholar
15
-
?nal ?, Topakci M. Design of a Remote-Controlled and GPS-Guided Autonomous Robot for Precision Farming. International Journal of Advanced Robotic Systems, 2015 December.
Google Scholar
16
-
Pedersen SM, Fountas S, Have H, Blackmore BS. Agricultural robots?system analysis and economic feasibility. Precision Agric, 2006 Sep 1; 7(4):295?308.
Google Scholar
17
-
Moorehead S, Wellington C, Gilmore B, Vallespi C. Automating Orchards: A System of Autonomous Tractors for Orchard Maintenance. 2012.
Google Scholar
18
-
Zhang Z, Noguchi N, Ishii K, Yang L, Zhang C. Development of a Robot Combine Harvester for Wheat and Paddy Harvesting. IFAC Proceedings Volumes, 2013 Jan 1;46(4):45?48.
Google Scholar
19
-
Yamaha. Precision Agriculture - RMAX [Internet]. Available from: https://www.yamahamotorsports.com/motorsports/pages/precision-agriculture-rmax. [Accessed 2021 May 26].
Google Scholar
20
-
SMARTBOW. Herd Monitoring Software | SMARTBOW. https://www.smartbow.com/en/home.aspx [Accessed 2021 May 26].
Google Scholar
21
-
Schweinzer V, Gusterer E, Kanz P, Krieger S, Suess D, Lidauer L, et al. Evaluation of an ear-attached accelerometer for detecting estrus events in indoor housed dairy cows. Theriogenology, 2019 Mar 1;130.
Google Scholar
22
-
Choukidar GA, Dawande NA. Smart Poultry Farm Automation and Monitoring System. In: 2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA), 2017. p. 1?5.
Google Scholar
23
-
Jilani MT. Comparative Analysis of Wireless Technologies for Internet-Of-Things Based Smart Farm. Science International. 2017 Jan 1;29:373?8.
Google Scholar
24
-
Hamdi S, Ahmed A, Bilal G. Smart Greenhouse Powered by Solar Energy: A Review. Solid State Technology, 2021 May 10;64:4280?93.
Google Scholar
25
-
Wangmo P, Jadoun VK, Agarwal A. A Review on Solar Energy-Based Smart Greenhouse. In: Recent Advances in Mechanical Engineering - Select Proceedings of NCAME, 2019:629-634. Springer Gabler.
Google Scholar
26
-
Kumar H, Jain PK, editors. Recent Advances in Mechanical Engineering. Singapore: Springer; 2020. p. 629?634. (Lecture Notes in Mechanical Engineering).
Google Scholar
27
-
Vij A, Vijendra S, Jain A, Bajaj S, Bassi A, Sharma A. IoT and Machine Learning Approaches for Automation of Farm Irrigation System. Procedia Computer Science, 2020 Jan 1 ;167:1250?1257.
Google Scholar
28
-
Azeta J, Bolu CA, Alele F, Daranijo EO, Onyeubani P, Abioye AA. Application of Mechatronics in Agriculture: A review. J Phys: Conf Ser. 2019 December.
Google Scholar
29
-
Groener B, Knopp N, Korgan K, Perry R, Romero J, Smith K, et al. Preliminary Design of a Low-cost Greenhouse with Open Source Control Systems. Procedia Engineering, 2015 Dec;107:470?479.
Google Scholar
30
-
Roopaei M, Rad P, Choo K-KR. Cloud of Things in Smart Agriculture: Intelligent Irrigation Monitoring by Thermal Imaging. IEEE Cloud Computing, 2017 Jan 1;4:10?15.
Google Scholar
31
-
ISSAfrica.org. Food security under threat in Kenya [Internet]. ISS Africa. 2018. Available from: https://issafrica.org/iss-today/food-security-under-threat-in-kenya [accessed 2021 May 27].
Google Scholar
32