GPSoil: Towards low-cost soil moisture sensing using GNSS signals
With global population growth, sustainable agriculture requires efficient soil moisture sensing for precise irrigation. While commercial soil moisture sensors are often limited by cost and durability, state-of-the-art RF-based sensing solutions require additional signal transmitter infrastructure, hindering widespread adoption. To fill this gap, we introduce GPSoil—a novel soil moisture sensing system that leverages pervasive Global Navigation Satellite System (GNSS) signals. On the hardware side, we employ two antennas along with a low-cost RF switch, enabling error mitigation for long propagation distances by comparing the signals captured from both antennas. On the software side, we leverage the inherent clock drift errors in commercial GNSS sensors and turn them into tools for fine-grained value extraction, enabling high-resolution sensing from otherwise coarse data. By integrating hardware and software innovations, we successfully achieve practical soil moisture sensing using GNSS signals. Built with off-the-shelf components, GPSoil achieves a soil moisture accuracy of 5.2% at a material cost of only $10.56, making it far more affordable than existing systems. GPSoil can sense moisture up to one meter underground, far surpassing other RF-based sensing systems and meeting the needs of most crops and irrigation systems. This work pioneers the use of GNSS signals in agriculture, offering a scalable, low-cost solution for advancing precision irrigation and promoting sustainable agriculture.
Authors
- Minhao Cui (ORCID: https://orcid.org/0000-0002-1913-846X)
- Huixin Dong (ORCID: https://orcid.org/0000-0002-5984-9194)
- S. Zhang (ORCID: https://orcid.org/0009-0006-0530-4179)
- Jingqi Lin (ORCID: https://orcid.org/0009-0008-4110-6879)
- Wei Wang (ORCID: https://orcid.org/0000-0002-2772-4856)
- Jie Xiong (ORCID: https://orcid.org/0000-0002-5396-4554)
Institutions
- Seoul National University (KR)
- Nanyang Technological University (SG)
- Raffles Institution (SG)
- Wuhan University (CN)
- Huazhong University of Science and Technology (CN)
- The University of Texas at Austin (US)
Publication Details
- Published
- 2025-11-03
- DOI
- https://doi.org/10.1145/3680207.3765236
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Fundamental Research Funds for the Central Universities