Design and Development of IoT Smart Drip Irrigation and Fertigation Prototype for Small and Medium Scale Farmers. Acase Study of Tomato Farmers in Tanzania

Abstract In Tanzania, almost 30% of the farm land are practicing traditional irrigation farming while around 60% rely on the seasonal rains which are only once every year. This resulted to inefficiency agriculture practices due to the absence of real-time weather data that in cooperates plants characteristics on seasonal growth for better yield. Studies have shown that, only about 10% of the crop caltivated land in Tanzania are farming using modern irrigation practices which include drip and smart irrigation systems. To address these challenges for the purpose of improving crop yield, there is a need to research, design and develop an integrated farming system that will monitor crop environmental conditions and nutritional requirements for the purpose of improving harvest and reduce food shortages. Based on this gap, the current research is aiming to design and develop a smart drip irrigation and fertigation system, using Internet of Things (IoT) technology. Due to the availability of many crops in Tanzania, this study will specifically focusing on tomato farming because they are commonly used as food crop as well cash crops in many parts of Tanzania. This innovative idea integrates sensors and real-time data analysis capabilities to enhance precision in water conservation and nutrient management. Studies have shown that tomato crops thrive best in the temperature range between 20 and 30 ℃ with humidity content above 60% and soil pH value between 6.2 and 6.8. This suitable weather condition for tomato growth is available in many parts of the Tropical countries like Tanzania. The implementation of this research project is based on design and develop a prototype for smart drip irrigation and fertigation system to be used for small and medium farmers in Tanzania. The culmination of these efforts aims to modernize Tanzanian agriculture by improving the efficiency and sustainability of farming practices. The project underscores the significance of precision agriculture techniques in optimizing crop yield and resource utilization. It emphasizes the potential of IoT—driven solutions in addressing longstanding agricultural challenges. The developed of a smart irrigation and fertigation system not only offers a promising avenue for enhancing agricultural productivity but also contributes to environmental conservation efforts through more efficient resource management.

Authors

Institutions

Publication Details

Journal
Journal of The Institution of Engineers (India) Series A
Published
2025-01-09
DOI
https://doi.org/10.1007/s40030-024-00857-7
Citations
5
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
8.75

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design and Development of IoT Smart Drip Irrigation and Fertigation Prototype for Small and Medium Scale Farmers. Acase Study of Tomato Farmers in Tanzania

Herb S. Rhee, Aneth P. Buberwa, Daniel H. Ngoma, Dickson J. Nkongo et al.
5 citations
Journal of The Institution of Engineers (India) Series A
Smart Agriculture and AI
8.75
article

Design and Development of IoT Smart Drip Irrigation and Fertigation Prototype for Small and Medium Scale Farmers. Acase Study of Tomato Farmers in Tanzania

Herb S. Rhee, Aneth P. Buberwa, Daniel H. Ngoma, Dickson J. Nkongo, Humoud M. Abdul-Rahman, Baraka H. Muna, Edison Ngaiza
article en
5 citations

Abstract

Abstract In Tanzania, almost 30% of the farm land are practicing traditional irrigation farming while around 60% rely on the seasonal rains which are only once every year. This resulted to inefficiency agriculture practices due to the absence of real-time weather data that in cooperates plants characteristics on seasonal growth for better yield. Studies have shown that, only about 10% of the crop caltivated land in Tanzania are farming using modern irrigation practices which include drip and smart irrigation systems. To address these challenges for the purpose of improving crop yield, there is a need to research, design and develop an integrated farming system that will monitor crop environmental conditions and nutritional requirements for the purpose of improving harvest and reduce food shortages. Based on this gap, the current research is aiming to design and develop a smart drip irrigation and fertigation system, using Internet of Things (IoT) technology. Due to the availability of many crops in Tanzania, this study will specifically focusing on tomato farming because they are commonly used as food crop as well cash crops in many parts of Tanzania. This innovative idea integrates sensors and real-time data analysis capabilities to enhance precision in water conservation and nutrient management. Studies have shown that tomato crops thrive best in the temperature range between 20 and 30 ℃ with humidity content above 60% and soil pH value between 6.2 and 6.8. This suitable weather condition for tomato growth is available in many parts of the Tropical countries like Tanzania. The implementation of this research project is based on design and develop a prototype for smart drip irrigation and fertigation system to be used for small and medium farmers in Tanzania. The culmination of these efforts aims to modernize Tanzanian agriculture by improving the efficiency and sustainability of farming practices. The project underscores the significance of precision agriculture techniques in optimizing crop yield and resource utilization. It emphasizes the potential of IoT—driven solutions in addressing longstanding agricultural challenges. The developed of a smart irrigation and fertigation system not only offers a promising avenue for enhancing agricultural productivity but also contributes to environmental conservation efforts through more efficient resource management.

Journal of The Institution of Engineers (India) Series AVol. 106(2)
Seoul National University (KR), University of Arusha (TZ)
Seoul National University
Zero hunger
Openalex Percentile: Top 3%
Smart Agriculture and AI
8.75
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.