Smart Irrigation System Using IoT

Kumar, Amit; Ranjan, Praful; Saini, Vaibhav

doi:10.1108/s1877-636120220000027009

Cited by 6 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Smart irrigation systems include different technologies, such as sensors, computer or mobile phone applications, and automatic control devices integrated within different irrigation technologies and/or methods. Thus, weather, soil moisture, and evapotranspiration are monitored to optimize water use efficiency [11].…”

Section: Introductionmentioning

confidence: 99%

Environmental and Economic Assessment of Membrane Capacitive Deionization (MCDI) and Low-Pressure Reverse Osmosis (LPRO) for Sustainable Irrigation in the Mediterranean Region

Ben Saad,

Cañas Kurz,

Hong

et al. 2024

Sustainability

View full text Add to dashboard Cite

Ensuring the sustainability of a product or a system requires a thorough evaluation of its environmental and socioeconomic impacts. In this context, one of the objectives of the EU-PRIMA SmaCuMed project is to evaluate the socioeconomic and environmental impacts of the Smart Cube system. The Smart Cube was developed for the PV-powered desalination of brackish groundwater with membrane capacitive deionization (MCDI) and low-pressure reverse osmosis (LPRO); it additionally uses smart sensors for controlled irrigation in remote agricultural areas in Morocco, as an example for the North African region. Based on the Life Cycle Sustainability Assessment approach, this paper aims to assess the environmental and economic impacts of the Smart Cube, using Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) analyses for environmental evaluation. Various scenarios have been defined for both environmental and economic assessments. Based on 1 m3 of produced desalinated water, the LCC results showed that, when using the desalination technologies directly connected to the grid, the prices are lower than those obtained when it was supplied by the PV system. This is only due to the very low energy prices from the Moroccan grid (EUR 0.10/kWh). The LCC results showed that LPRO is a more cost-effective option for producing desalinated water, with a lower total cost compared to MCDI. However, LCA results indicated that LPRO has a higher environmental impact compared to MCDI. If higher water production capacity is a priority, MCDI connected to PV is the best choice, with lower carbon emission but higher overall water costs.

show abstract

Section: Introductionmentioning

confidence: 99%

Environmental and Economic Assessment of Membrane Capacitive Deionization (MCDI) and Low-Pressure Reverse Osmosis (LPRO) for Sustainable Irrigation in the Mediterranean Region

Ben Saad,

Cañas Kurz,

Hong

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…In order to increase crop productivity and avoid the misuse of water resource smart irrigation system is needed. [1] Presents a system using different sensors like (1) Soil Moisture sensor, which measures the moisture present in the soil, (2) Humidity and Temperature Sensor (DHT11), which traces the temperature change. All these sensors are connected to the Node MCU ESP8266 microcontroller, which is also a Wi-Fi module.…”

Section: Introductionmentioning

confidence: 99%

Automatic Irrigation System with Remote Monitoring Facility

2024

IRJMETS

View full text Add to dashboard Cite

India is one of the biggest producers of agricultural goods. But India has very low productivity ratio with respect to its farm land area. In order to increase productivity of farm lands precise use of water resource, fertilizers and compost etc. is need of the hour. This paper proposes an automated irrigation system model which aims at efficient use of water resource in irrigation. This smart irrigation system acquires knowledge about soil moisture and temperature of surrounding using soil moisture and temperature sensors installed in the field. This automatic irrigation system makes use of Arduino Uno as controller module. Soil moisture sensors and temperature sensors data is input to the controller. Controller unit runs water motor based upon this data. After precise irrigation of the crop water motor is switched off by the controller unit based on the soil moisture and environment temperature data being fed back to the controller by the sensors. Farmer can observe sensor measurement data and action taken by microcontroller on mobile through Wi-Fi module installed on the controller unit.

show abstract