Muthmainnah, Muthmainnah, Mulyadi, Muhammad Fakhri, Tazi, Imam, Mulyono, Agus ORCID: https://orcid.org/0000-0002-2574-1791, Hananto, Farid Samsu ORCID: https://orcid.org/0000-0002-0305-5803, Chamidah, Ninik and Kusairi, Kusairi (2024) Development of an automated monitoring system for soil moisture and temperature in smart agriculture to enhance lettuce farming productivity based on IoT. Multidisciplinary Science Journal, 6 (11). pp. 1-9. ISSN 25953982
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Abstract
In the era of advanced agriculture, implementing Internet of Things (IoT) technology has brought significant innovations to monitoring plant growth. This article discusses the development of an automation system to monitor soil moisture and temperature in lettuce farming based on smart agriculture. The system integrates soil moisture and temperature sensors connected in real-time through IoT, enabling accurate and continuous monitoring of the environmental conditions for lettuce cultivation. The soil moisture sensor used is YL-69 with the calibration equation y=-0.0612x+64.38 and an R-square value of 0.8953. The average standard deviation value is 0.36, and the average accuracy value is 98.71%. The temperature sensor used is DHT11 with the calibration equation y=0.9619x+2.8107 and an R-square value of 0.9928. The average standard deviation value is 0.023, and the average accuracy is 99.67%. The microcontroller used is ESP8266, known for its reliable connectivity. The IoT platform employed is the Blynk application. Monitoring results over five days yielded average soil moisture values ranging from 76% to 98%, and average temperature values ranged from 22°C to 27°C. Through continuous data collection, farmers can optimize irrigation, apply corrective measures for temperature fluctuations, and design more innovative farming strategies. The results of implementing this system demonstrate a significant improvement in resource efficiency, operational cost savings, and increased productivity in lettuce farming management.
Item Type: | Journal Article |
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Keywords: | accuracy calibration sensor smart farming validation |
Subjects: | 02 PHYSICAL SCIENCES > 0299 Other Physical Sciences > 029999 Physical Sciences not elsewhere classified |
Divisions: | Faculty of Mathematics and Sciences > Department of Physics |
Depositing User: | Farid Samsu Hananto |
Date Deposited: | 04 Jun 2024 13:04 |
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