Low Cost Dual Sensing System for Soil Quality Enhancement Using Temperature and Humidity Monitoring

This paper investigates the system design for soil quality enhancement. The system device measures soil temperature and humidity to provide a soil quality dataset. Data is collected in a period of 4 weeks. In this research, a microcontroller, temperature sensor, humidity sensors and a display module are occupied. By utilizing these dual sensors, it is observable that optimal soil conditions are achieved when temperature is ranging from 20°C to 30°C and the humidity is ranging 60% to 80%. Therefore, this research highlights the potential usefulness in proving an effective system for soil suitability of agricultural uses. Future enhancements could focus on improving sensor protection and automating calibration by providing real-time data monitoring. Thus, this research can facilitate the information of crop management decisions, irrigation procedure and supporting an efficient and sustainable agricultural production.

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Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/icoris63540.2024.10903913
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.60
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Low Cost Dual Sensing System for Soil Quality Enhancement Using Temperature and Humidity Monitoring

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article

Low Cost Dual Sensing System for Soil Quality Enhancement Using Temperature and Humidity Monitoring

Riki Akbar Mc Dougall, Gian Guido Hibatulloh, Reyhan Seifan Safero, Wan Mohamad Axel Rinaldi, Selvi Lukman
article en
1 citations

Abstract

This paper investigates the system design for soil quality enhancement. The system device measures soil temperature and humidity to provide a soil quality dataset. Data is collected in a period of 4 weeks. In this research, a microcontroller, temperature sensor, humidity sensors and a display module are occupied. By utilizing these dual sensors, it is observable that optimal soil conditions are achieved when temperature is ranging from 20°C to 30°C and the humidity is ranging 60% to 80%. Therefore, this research highlights the potential usefulness in proving an effective system for soil suitability of agricultural uses. Future enhancements could focus on improving sensor protection and automating calibration by providing real-time data monitoring. Thus, this research can facilitate the information of crop management decisions, irrigation procedure and supporting an efficient and sustainable agricultural production.

Binus University (ID)
Zero hunger
Openalex Percentile: Top 20%
Smart Agriculture and AI
0.60
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