IoT-Based Capacitive soil moisture sensor for Smart Irrigation scheduling in White Cucumber (Cucumis sativus, L.) cultivation using drip irrigation
| dc.contributor.author | Jerrand Nolan D. Acosta and Chrostopher Alebert L. Jacobo | |
| dc.date.accessioned | 2026-02-20T06:23:23Z | |
| dc.date.available | 2026-02-20T06:23:23Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Traditionally, irrigation scheduling relied on manual observations and estimations, resulting in inefficient water usage as well as potential yield losses. The integration of Internet of Things (IoT) technology and capacitive soil moisture sensors has emerged as a promising solution for precise and automated irrigation management in agriculture in response to these challenges. This study was conducted to evaluate the IoT-based capacitive moisture sensor for automatically scheduling drip irrigation for White Cucumber (Cucumis sativus L.). Specifically, the study aims to calibrate and interpret the capacitive soil moisture sensor for automatic irrigation scheduling , create a system that automatically irrigates the field based on the set treatments, asses the growth and yield of white cucumber, and conduct a sample cost analysis for the installation of the capacitive soil moisture sensor. Treatment 1 = 40% of AW, Treatment 2=45% of AW, Treatment 3= 50% of AW, and Treatment 4= Farmer’s Practice (Control) for the percentage of MAD. Calibration involves fine-tuning the sensor readings to match the actual soil conditions, enhancing the precision of subsequent measurements. During the program development in the Arduino IDE, the lowest and highest values were determined and established as the wet and dry soil references for the system, respectively. Notably, the highest value was assigned to the wet soil condition because the presence of electrolytes in the soil tended to be higher when the soil was dry and lower when it was wet. capabilities for optimizing water management, as treatments exhibited significantly of weight (13.7 kg) and pieces (62.3 pcs) of White Cucumber produce. In contrast, all treatments have comparable development parameters throughout the study. A simple cost analysis was done, which yielded a 16.51% return on investment when smart automatic drip irrigation was implemented. For the study alone, a total of Php9,766.78 was used for the whole production and cultivation. | |
| dc.identifier.uri | http://granarium.clsu.edu.ph/handle/123456789/978 | |
| dc.language.iso | en_US | |
| dc.relation.supervisor | WENDY С. МАТЕО, Ph.D. | |
| dc.title | IoT-Based Capacitive soil moisture sensor for Smart Irrigation scheduling in White Cucumber (Cucumis sativus, L.) cultivation using drip irrigation | |
| dc.type | Thesis |