Smart Crops Irrigation System with Low Energy Consumption

Pierre, Nyakuri Jean; Sefu, Bikorimana; Venuste, Sefu; D’Amour, Mirembe Jean; Daniel, Kanyarwanda; Pierre, Nzemerimana Jean; Bosco, Kalisa Jean; Felix, Harerimana

doi:10.37675/jat.2022.00192

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…IoT technology has been increasingly employed in irrigation and fertigation practices to enhance resource management, optimize crop growth, and improve overall agricultural productivity. Soil moisture sensors and actuators have been used in [19], [20][21] for automatic irrigation but they are based only on threshold values of the moisture in the field. A system consisting of soil moisture sensors, soil temperature sensors, a Raspberry Pi as the MCU, and a water pump is proposed for automatic irrigation monitoring [22].…”

Section: Related Workmentioning

confidence: 99%

AI Based Real-Time Weather Condition Prediction with Optimized Agricultural Resources

Pierre,

Ishimwe Viviane,

Lambert

et al. 2023

EJT

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Purpose: Unpredictable and rapid change in weather patterns has great impact on agricultural activities, especially for precision agriculture that results in worsened water resources availability, decreased soil fertility, use of pesticide as well as decreased yield productivity. In attempt to alleviate these challenges, this study aims at developing a real-time weather and farm field data driven Artificial Intelligence (AI) and Internet of Things (IoT) system that analyze, manage and schedule irrigation and fertigation as well as enabling farmers to interact with their farms via Smart phone or PCs to optimize energy and water resources. Methodology: The system employs weather condition monitoring sensors such as atmospheric pressure, air temperature, air humidity and wind speed for collecting real-time farm field data and uses Fuzzy Inference System (FIS) to predict rainfall rate at farm area for 24 hours period. The system also gathers field data such as soil moisture content and soil nutrient content and uses the Machine Learning (ML) algorithms to predict the time for irrigation and fertigation. By combining weather and farm field data, the system schedules the irrigation and fertigation activity. In addition, the mobile application is developed for the farmers to interact, control and monitor the farming activities and the data is presented to the farmers in both graphical and numerical formats. Findings: The system prototype deployed and tested in the two hectors Maize farm proved that 55% of water, 51% of energy and 20% of fertilizer were saved as well as increases in 20% of Maize yield production compared to previous season. Recommendations: Since the current irrigation and fertigation practices are based on predetermined time of the day and threshold values for automatic irrigation, this solution introduced the new concept of real-time and short-term weather forecasting that enables farmers to balance the irrigation period and weather pattern for water and fertilizer resources optimization.

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Section: Related Workmentioning

confidence: 99%

AI Based Real-Time Weather Condition Prediction with Optimized Agricultural Resources

Pierre,

Ishimwe Viviane,

Lambert

et al. 2023

EJT

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Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey

Mowla,

Shah

et al. 2023

IEEE Access

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The increasing food scarcity necessitates sustainable agriculture achieved through automation to meet the growing demand. Integrating the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) is crucial in enhancing food production across various agricultural domains, encompassing irrigation, soil moisture monitoring, fertilizer optimization and control, early-stage pest and crop disease management, and energy conservation. Wireless application protocols such as ZigBee, WiFi, SigFox, and LoRaWAN are commonly employed to collect real-time data for monitoring purposes. Embracing advanced technology is imperative to ensure efficient annual production. Therefore, this study emphasizes a comprehensive, futureoriented approach, delving into IoT-WSNs, wireless network protocols, and their applications in agriculture since 2019. It thoroughly discusses the overview of IoT and WSNs, encompassing their architectures and summarization of network protocols. Furthermore, the study addresses recent issues and challenges related to IoT-WSNs and proposes mitigation strategies. It provides clear recommendations for the future, emphasizing the integration of advanced technology aiming to contribute to the future development of smart agriculture systems. INDEX TERMSInternet of things, wireless sensor networks, wireless network protocols, smart agriculture applications.

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Smart Crops Irrigation System with Low Energy Consumption

Cited by 2 publications

References 14 publications

AI Based Real-Time Weather Condition Prediction with Optimized Agricultural Resources

AI Based Real-Time Weather Condition Prediction with Optimized Agricultural Resources

Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey

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