Smart Agriculture Monitoring and Irrigation System Using IoT

Pratihar, Raktim; Bhowmick, Roberto; Ray, Bikram; Sadhukhan, Debmalya; Mullik, Anuron; Majumder, Bansari Deb

doi:10.2139/ssrn.3526009

Cited by 4 publications

(1 citation statement)

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“…The authors [24] presented a new scenario of decreasing water tables and drying up rivers was studied, so the environment needs an urgent utilization of water. To cope with the situation, temperature and moisture sensors have been implemented in a suitable location for measuring irrigation.…”

Section: Figure 2: Smart Farm Irrigation Embedded Devicementioning

confidence: 99%

Contextual use of a Smart Farm Irrigation System using Internet of Things (IoT)

Abioye(Ogunbiyi,

Adegoke,

Abogunrin

et al. 2023

Preprint

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A crucial component of agricultural output is water, and its production can be reduced by shortage, which negatively affects food security. In an effort to address this developing issue, irrigation was employed as form of water management. Various irrigation methods were employed but there were various limitation to those methods such as soil and water erosion due to inability of soil moisture determination. This work focusses on the creation of an irrigation system based on the Internet of Things. The implementation was done using Arduino microcontroller programmed in C programming Language. The application’s data on soil moisture level, valve condition, and remote management of the smart irrigation system were all displayed using an Arduino microcontroller. In Nigeria, the smart irrigation system was tested on three different soil types: clay, loam, and sandy. Data including the moisture reading and irrigation time were acquired after inserting the moisture sensor probe into the soil sample. The average time taken to irrigate clay, loamy and sandy soil at 2kg, 5kg, 8kg and 10kg were 10.93s, 15s, 19.75s, 23.25s; 9.5s, 12.4s, 17s, 21.5s; 8.25s, 11.3s, 14.7s and 20.2s, respectively. This system helps in reducing soil erosion, as it monitors and reads soils moisture in real-time.

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Section: Figure 2: Smart Farm Irrigation Embedded Devicementioning

confidence: 99%

Contextual use of a Smart Farm Irrigation System using Internet of Things (IoT)

Abioye(Ogunbiyi,

Adegoke,

Abogunrin

et al. 2023

Preprint

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Future Hydrological Drought Analysis Considering Agricultural Water Withdrawal Under SSP Scenarios

Kim

Sung

Shahid

et al. 2022

Water Resour Manage

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Hydrological drought is assessed through river ow, which depends on river runoff and water withdrawal. This study proposed a framework to project future hydrological droughts considering agricultural water withdrawal (AWW) for shared socioeconomic pathway (SSP) scenarios. The relationship between AWW and potential evapotranspiration (PET) was determined using a deep belief network (DBN) model and then applied to estimate future AWW using projections of the twelve global climate models (GCMs). 12 GCMs were bias-corrected using the quantile mapping method, climate variables were generated, and river ow was estimated using the soil and water assessment tool (SWAT) model. The standardized runoff index (SRI) was used to project the changes in hydrological drought characteristics. The results revealed a higher occurrence of severe droughts in the future. Droughts would be more frequent in the near future than in the far future (2061-2100) and more severe when AWW is considered. Droughts would also be more severe for SSP5-8.5 than for SSP2-4.5. The study revealed that the increased PET due to rising temperatures is the primary cause of the increased drought frequency and severity. The AWW will accelerate the drought severities in the future in the Yeongsan River basin. ProcedureThis study consists of a total of six steps. The rst step was to perform bias correction of the simulations of the twelve GCMs using the quantile mapping method. The performance of bias correction was evaluated using several statistical performance indices. The second step was to formulate the SWAT model for the Yeongsan River basin using historical meteorological observation data, AWW, and discharges from the wastewater treatment facility. The SWAT parameters were calibrated using SWAT-CUP (Calibration and Uncertainty Procedure; Abbaspour et al., 2007) based on observed runoff levels at Geukrakgyo (bridge), as shown in Figure 1. The third step was to estimate the future AWW outcomes using GCMs based on the derived relationship between PET and AWW for the observation period. The PET was calculated using Thornthwaite's (1948) method, and the relationship was quanti ed using the DBN. The fourth step estimated the river ow for the twelve GCMs and two SSP scenarios. The fth step calculated the SRI and analyzed the future drought characteristics. The analysis of the future period was divided into the near future (NF) (2021-2060) and the far future (FF) (2061-2100). In the last, uncertainty analysis was performed using REA (Reliability ensemble average) for the runoff and drought index considering with or without AWW. Study area and datasetsThe basin area of the Yeongsan River is 3,371.4 km², and the average annual temperature and rainfall amount are 14.0°C and 1,293 mm, respectively. Land use includes forest (45.4%), agriculture (35.5%), urban areas (7.3%), grasslands (5.2%), water bodies (3.4%), bare lands (1.8%), and wetlands (1.4%). The Yeongsan River basin, located in the southwestern region of Korea, is known as a large-scale agricultural area, ...

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IOT based Innovative Irrigation using Adaptive Cuckoo Search Algorithm comparison with the State of Art Drip Irrigation to attain Efficient Irrigation

Jahnavi

Kalyanasundaram

2022

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)

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Smart Agriculture Monitoring and Irrigation System Using IoT

Cited by 4 publications

References 0 publications

Contextual use of a Smart Farm Irrigation System using Internet of Things (IoT)

Contextual use of a Smart Farm Irrigation System using Internet of Things (IoT)

Future Hydrological Drought Analysis Considering Agricultural Water Withdrawal Under SSP Scenarios

IOT based Innovative Irrigation using Adaptive Cuckoo Search Algorithm comparison with the State of Art Drip Irrigation to attain Efficient Irrigation

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