DESIGN OF A PROTOTYPE FOR SOIL MOISTURE MONITORING AND WATERING CONTROL OF CHILI PLANTS BASED ON IOT (INTERNET OF THINGS) USING BLYNK

This study aims to develop an IoT-based prototype system for monitoring soil moisture and controlling irrigation in chili plants using the Blynk platform. The research employs a Research and Development (R&D) approach with a prototypedevelopment model. The system integrates a capacitive soil moisture sensor (Soil Moisture Sensor Capacitive V1.2) to measure soil moisture levels and automate irrigation decisions. The system's effectiveness was evaluated through 56 trials, achieving a 98.15% success rate, indicating high reliability in providing real-time soil moisture data. The usability assessment showed that all respondents rated the system positively, with functionality reaching 100% feasibility and usability rated at 86.3%, categorized as very good. However, further analysis is needed to validate the questionnaire used in usability testing and assess whether training is required for farmers to operate the system efficiently. In terms of reliability, the system recorded a 5% sensor accuracy deviation, highlighting the need for additional calibration and comparative testing with alternative sensors. Overall, this system has the potential to enhance agricultural productivity and optimize water usage, reducing dependence on manual irrigation. Future research should focus on improving system connectivity, refining sensor accuracy, and expanding the system's application to various crops and environmental conditions to promote sustainable and technology-driven farming practices.

Authors

Institutions

Publication Details

Journal
Journal of Electrical Engineering and Informatics
Published
2025-03-21
DOI
https://doi.org/10.59562/jeeni.v2i2.6800
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DESIGN OF A PROTOTYPE FOR SOIL MOISTURE MONITORING AND WATERING CONTROL OF CHILI PLANTS BASED ON IOT (INTERNET OF THINGS) USING BLYNK

Muhammad Burhan, Al Imran, Iwan Suhardi, Dessy Ana Laila Sari et al.
Journal of Electrical Engineering and Informatics
Smart Agriculture and AI
article

DESIGN OF A PROTOTYPE FOR SOIL MOISTURE MONITORING AND WATERING CONTROL OF CHILI PLANTS BASED ON IOT (INTERNET OF THINGS) USING BLYNK

Muhammad Burhan, Al Imran, Iwan Suhardi, Dessy Ana Laila Sari, Muh. Owen M.
article en

Abstract

This study aims to develop an IoT-based prototype system for monitoring soil moisture and controlling irrigation in chili plants using the Blynk platform. The research employs a Research and Development (R&D) approach with a prototypedevelopment model. The system integrates a capacitive soil moisture sensor (Soil Moisture Sensor Capacitive V1.2) to measure soil moisture levels and automate irrigation decisions. The system's effectiveness was evaluated through 56 trials, achieving a 98.15% success rate, indicating high reliability in providing real-time soil moisture data. The usability assessment showed that all respondents rated the system positively, with functionality reaching 100% feasibility and usability rated at 86.3%, categorized as very good. However, further analysis is needed to validate the questionnaire used in usability testing and assess whether training is required for farmers to operate the system efficiently. In terms of reliability, the system recorded a 5% sensor accuracy deviation, highlighting the need for additional calibration and comparative testing with alternative sensors. Overall, this system has the potential to enhance agricultural productivity and optimize water usage, reducing dependence on manual irrigation. Future research should focus on improving system connectivity, refining sensor accuracy, and expanding the system's application to various crops and environmental conditions to promote sustainable and technology-driven farming practices.

Journal of Electrical Engineering and InformaticsVol. 2(2)
State University of Makassar (ID)
Openalex Percentile: Top 94%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.