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Project properties |
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| Title | Smart and data-driven drip irrigation system: a cost-effective solution to increase crop productivity in developing countries |
| Group | Water Resources Management group |
| Project type | thesis |
| Credits | 36 |
| Supervisor(s) | Harm Boesveld, Raphael Kiran |
| Examiner(s) | |
| Contact info | harm.boesveld@wur.nl |
| Begin date | 2021/03/01 |
| End date | 2022/01/01 |
| Description | Country: Netherlands
Host institute: MegaGroup Trade Holding B.V. Period: tbd Project type: thesis or internship Problem context A major share of developing countries’ GDP is dependent on agriculture. Water is a critical input for agricultural production. The consequence of global warming and increasing drought are creating a negative impact on the availability of water resources. Also changing dynamics, non-linearity of soil moisture content, as well as other weather/plant variables requires a real-time monitoring with accurate predictive model for effective irrigation and crop management. Due to lack of cost-effective smart irrigation systems, developing countries consume more water in contrast to the developed countries for achieving the same yield. Research Objective/Question The objective of the research is to co-develop and to analyze the ease of implementation of a cost-effective smart irrigation system for developing countries. The system will rely on the sensors data, weather forecast information and intelligent processing in order to achieve an optimum water-resource utilization. A dynamic prediction model or an algorithm must be developed to predict the irrigation time/pattern based on air temperature, relative humidity, soil temperature, soil moisture as well as the precipitation information of upcoming days. The smartness and accuracy of the proposed algorithm will be evaluated and compared with real data. What is expected from the student (type of research) The student is expected to investigate the financial, cultural and technological challenges in introducing low-cost smart irrigation system in developing countries. Student is encouraged to work alongside engineers, developers and designers in co-developing a smart irrigation system implementing predictive algorithms that can be used to automate the irrigation process. Evaluation of the predictive algorithm is done through a pilot testing. |
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