Evaluation of IoT based smart drip irrigation and ETc based system for sweet corn

S, Vinod Kumar; Singh, Chetan; Rao, K. V.; Kumar, Matthew; Rajwade, Yogesh Anand; Babu, B. T. R.; Singh, Karan P.

doi:10.1016/j.atech.2023.100248

Cited by 13 publications

(3 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The field data collection system contains three sensors: a capacitive soil moisture sensor (v2.0), a soil temperature sensor (DS18B20), and a temperature and humidity sensor (DHT11). The output of this sensor is read by an ESP32-WROOM-32 microcontroller, which wirelessly transmits the recorded data to an IoT platform (ThingSpeak) using an ESP8266 Wi-Fi module (Kumar et al 2020;Kumar et al 2022;Kumar et al 2023). Details of the development of IoT-based smart drip irrigation systems are described in (Kumar et al 2022;Kumar et al 2023), and a flowchart of the process is shown in (Fig.…”

Section: Iot-based Data Acquisition Systemmentioning

confidence: 99%

“…Due to the wiring connection range, such systems have a limited deployment size for monitoring points; they require extensive cabling, which leads to high installation, maintenance, and relocation costs; and the cables are easily damaged if placed outdoors in adverse conditions (Kumar et al 2020;Kumar et al 2022;Kumar et al 2023). In the present research work, we have developed an IoT system that uses wireless sensor networks (WSNs) technology to overcome previous wired sensor system issues.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

IoT-based Smart Drip Irrigation Scheduling and Wireless Monitoring of Microclimate in Sweet Corn Crop under Plastic Mulching

Singh,

Rao

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

Precision irrigation with IoT-based decision-making technologies has proven effective in optimizing agricultural production irrigation. The Internet of Things (IoT) is crucial for monitoring the real-time data from sensors and automatically activating irrigation systems. This study evaluated the effectiveness of a drip irrigation system based on IoT and soil moisture sensors in a field experiment with sweet corn between 2020 and 2022. There were nine treatments with three replications: ETc-based drip irrigation (ETc 100%) and IoT-based drip irrigation scheduling with two soil moisture levels under three mulches: black plastic mulch, silver plastic mulch, and control (bare soil). IoT-based drip irrigation scheduling (100% FC) applied irrigation when soil moisture reached a lower threshold (≤ 33.1%) and ended when the field capacity was reached (≥ 43.5). With IoT-based drip irrigation scheduling (80% FC), irrigation was applied when the soil moisture content reached the threshold (≤ 33.1%) and ended when the field capacity reached 80% (≥ 34.8). Growth variables (root biomass, yield, corn length, cob weight, and water productivity) were compared for each irrigation method. Results showed that the ET-based irrigation method was easier to implement with less infrastructure and could result in lower yields than the IoT-based drip irrigation method with 100% FC. Grain and stalk yields increased by more than 12.05% and 14.97% for the IoT irrigation with 100% FC. It was found that IoT-based drip irrigation with 100% FC and 80% FC used 12.7% and 24.5% less irrigation water, respectively, and provided IoT-based drip irrigation with 100% FC, there was a 12.8% increase in marketable yield than ETc and IoT-based drip irrigation with 80% FC. The results show that the developed IoT system can potentially monitor the microclimate of plants in real time under different conditions of using plastic mulch. The IoT system is rugged and water-resistant, making it suitable for outdoor agriculture. Solar panels power the system, so there is no need for cabling and sensor nodes can be efficiently monitored. Research conducted on the IoT system shows that it can record and display environmental parameters to users via the cloud (ThingSpeak).

show abstract

Section: Iot-based Data Acquisition Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

IoT-based Smart Drip Irrigation Scheduling and Wireless Monitoring of Microclimate in Sweet Corn Crop under Plastic Mulching

Singh,

Rao

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Increasing water use efficiency in irrigated agriculture with smart technologies like sensors and the Internet of Things (IoT) is a growing trend in agriculture [1]. Smart irrigation necessitates real-time data collection by integrating sensors and wireless sensor communication on the weather, soil, and plant parameters to augment plant growth and productivity, reducing environmental impacts and conserving resources [2]. Implementing soil moisture monitoring for irrigation scheduling allows for data-driven decision-making regarding irrigation water volume, leading to enhanced water use efficiency, improved soil moisture management, and potentially boosted plant productivity through optimized water supply to the root zone [3].…”

Section: Introductionmentioning

confidence: 99%

Mangosteen Yield and Fruit Quality under Regulated Irrigation with Sensors and IoT

Jaroensutasinee,

Boonsanong

et al. 2024

J. Hum. Earth Future

View full text Add to dashboard Cite

Mangosteen (Garcinia mangostana L.) generates over 88 billion USD in export revenue to Thailand annually but is restrained due to fruit defects. This study aimed to determine whether smart irrigation with sensors, IoT, and real-time data collection for regulating stable soil water content affects mangosteen fruit quantity and quality. Climate, soil, and mangosteen parameters were compared between irrigated and non-irrigated productions. Flowering and fruit yield data were collected from twenty randomly selected mangosteen trees per irrigation treatment. The results showed that air and soil temperatures were lower, but relative humidity and soil moisture on mangosteen production were greater in irrigated trees than in non-irrigated trees. Irrigated and non-irrigated mangosteen trees showed no significant difference in trunk diameter or crown size. Irrigation boosted mangosteen yields with increased flowers, fruits, and weight but thinner peels, fewer pulp segments, and a higher vulnerability to fruit imperfections. The mean fruit circumference did not differ significantly between non-irrigated and irrigated mangosteen production systems. Mangosteen fruits in irrigated production had fewer fruit defects than those in non-irrigated production. Regulated irrigated mangosteen production with stable soil moisture using soil moisture sensors and IoT produced high-quantity and quality mangosteens with fewer fruit defects. Doi: 10.28991/HEF-2024-05-02-05 Full Text: PDF

show abstract

IoT-based smart drip irrigation scheduling and wireless monitoring of microclimate in sweet corn crop under plastic mulching

Vinod Kumar,

Singh,

Rao

et al. 2024

Irrig Sci

View full text Add to dashboard Cite

Evaluation of IoT based smart drip irrigation and ETc based system for sweet corn

Cited by 13 publications

References 41 publications

IoT-based Smart Drip Irrigation Scheduling and Wireless Monitoring of Microclimate in Sweet Corn Crop under Plastic Mulching

IoT-based Smart Drip Irrigation Scheduling and Wireless Monitoring of Microclimate in Sweet Corn Crop under Plastic Mulching

Mangosteen Yield and Fruit Quality under Regulated Irrigation with Sensors and IoT

IoT-based smart drip irrigation scheduling and wireless monitoring of microclimate in sweet corn crop under plastic mulching

Contact Info

Product

Resources

About