Low-cost IoT framework for irrigation monitoring and control

Abstract

PurposeThe purpose of this work is to make an IoT-based low-cost and power-efficient portable system to control irrigation using a threshold value algorithm and to measure soil-irrigation-related parameters such as soil moisture, soil temperature, humidity and air temperature.Design/methodology/approachThis paper presents a threshold value algorithm to optimize power consumption and to control irrigation process.FindingsThe system uses ESP-12F 8266 as the main microcontroller unit to monitor and control irrigation system. The system also consists of an actuator system that triggers automatically based on a threshold value algorithm. An open-source cloud platform is used to monitor and store all the data for future perspective. To make the system run for a long time without any human intervention, a solar panel is used as an alternate source of energy for charging the 12V lithium-ion battery. The battery takes 2.64 h for full charging considering peak intensity of sunlight. A capacitive moisture sensor is included using less expensive 555 timer and calibrated to measure water content in the soil. The 555 timer is used in astable mode of configuration to generate a signal of 572 KHz. The calibrated sensor data when compared with a standard SEN0193 moisture sensor shows an error of 3.4%. The prototype model is made to optimize the power consumption. This can be achieved by utilizing sleep mode of ESP-12F 8266. The total cost involved to make the system is 3900.55 Indian rupees and around US$54.90.Practical implicationsThe device is tested in a flower garden during winter season of Nagaland, India, for 75 days to collect all the data and to automate the irrigation process.Originality/valueThe proposed threshold value algorithm optimizes the power consumption of the device, and wastage of water is reduced up to 60% as compared to the traditional method of irrigation.

Automated Low-Cost Soil Moisture Sensors: Trade-Off between Cost and Accuracy

“…[42] for example, tested the SKU sensor under three soil textures and found distinct calibration curves. The individual calibration curves (Figure 7) showed satisfactory consistency between SWC and sensor output with R 2 greater than 0.94, similar to the correlation found in other studies [2,23,24,[42][43][44][45][46] On the other hand, the use of universal and single-point calibration curves presented a high correlation between sensor output and SWC, being viable options for quick interpretation of collected data, since individual calibration is a time-consuming task and demands qualified labor [24]. For example, the individual calibration of a sensor takes approximately 3 h while the single-point calibration only takes approximately 15 min.…”

Creating a Sensor Tier for the EMULSION IoT Platform with Low-Cost Electronic Modules

“…In [10], a lowcost Wi-Fi based IoT prototype was proposed, costing around US $60 for a single unit. In [11], a lowcost IoT system for irrigation monitoring and control, utilizing ESP-12F 8266 as MCU, was proposed, with a cost of US $54.90. In [12], low-cost agriculture devices were built with Raspberry Pi 3.…”

Wireless Sensor Network-Based Artificial Intelligent Irrigation System: Challenges and Limitations

“…When activated for the first time, the system checks the weather. The rain causes the machine to sleep for about half an hour; otherwise, it will connect to the nearest open WiFi network [38]. The general flowchart of the threshold value algorithm is shown in Fig.…”

“…Applying other algorithms, including threshold-based methods, Kalman filtering, PSO, and more, in irrigation systems provides diverse approaches for efficient water management, crop yield optimization, and sustainable agricultural practices, as evidenced by numerous recent studies and advancements in this field. Borah et al [38] Created a lightweight, low-cost, and energy-efficient IoT-based irrigation control system using the threshold value algorithm. Measuring soil irrigation variables using a moisture sensor, a soil temperature sensor, and a moisture and air temperature sensor.…”