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Title: | Smart Irrigation Scheduling Algorithms and Deployment Scenarios: Challenges and Recommendations for Farming in the Sub-Saharan Africa |
Authors: | Supreme Ayewoh Okoh, Bala Alhaji Salihu S. Zubair, Elizabeth N. Onwuka |
Keywords: | Smart irrigation system scheduling algorithm internet of things, Sub-Sahara Africa |
Issue Date: | 5-Nov-2021 |
Publisher: | Proceedings of the International Conference on Industrial Engineering and Operations Management Monterrey, Mexico, November 3-5, 2021 |
Citation: | Okoh, S. A., Salihu, B. A., Zubairu, S., & Onwuka, E. N. Smart Irrigation Scheduling Algorithms and Deployment Scenarios: Challenges and Recommendations for Farming in the Sub-Saharan Africa. |
Abstract: | This paper buttresses the need for IoT-enabled agriculture, in order to tackle food insecurity globally, especially in the Sub-Saharan African (SSA) region where the global population rise is predicted to concentrate. It details the nitty gritty involved in setting up a smart irrigation system and presents a systematic review of seven (7) scheduling algorithms used to drive smart irrigation systems. Analysis of the algorithms shows that they differ in terms of sensor inputs and level of precision. Recommendations were made in choosing a suitable algorithm and how the chosen algorithm can be deployed to withstand network connectivity problems. This paper also proposes a community Internet of Things (IoT) network to deploy smart irrigation systems and other applications of IoT-enabled agriculture, in rural areas among smallholder farmers. This is to mitigate the challenges that are likely to discourage farmers especially those in the SSA from embracing the technology. |
URI: | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/18276 |
Appears in Collections: | Telecommunication Engineering |
Files in This Item:
File | Description | Size | Format | |
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70(1).pdf | Smart Irrigation Scheduling Algorithms and Deployment Scenarios: Challenges and Recommendations for Farming in the Sub-Saharan Africa | 1.87 MB | Adobe PDF | View/Open |
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