SoilCares: Towards Low-cost Soil Macronutrient and Moisture Monitoring Using RF-VNIR Sensing

被引:0
|
作者
Wang, Juexing [1 ]
Feng, Yuda [2 ]
Kumbhar, Gouree [3 ]
Wang, Guangjing [1 ]
Yan, Qiben [1 ]
Jin, Qingxu [1 ]
Ferrier, Robert C. [1 ]
Xiong, Jie [2 ]
Li, Tianxing [1 ]
机构
[1] Michigan State Univ, E Lansing, MI 48824 USA
[2] Univ Massachusetts Amherst, Amherst, MA USA
[3] Dow Chem Co USA, Deer Pk, TX USA
来源
PROCEEDINGS OF THE 2024 THE 22ND ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS AND SERVICES, MOBISYS 2024 | 2024年
关键词
Smart agriculture; Pervasive sensing; Multi-modality; Soil sensing Low-power and low-cost sensing; NEAR-INFRARED SPECTROSCOPY; WATER-CONTENT; REFLECTANCE SPECTROSCOPY; ROOT DISTRIBUTION; POTASSIUM; SYSTEM; MAIZE; NUTRIENTS; POLLUTION; LOSSES;
D O I
10.1145/3643832.3661868
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Accurate measurements of soil macronutrients (i.e., nitrogen, phosphorus, and potassium) and moisture play a key role in smart agriculture. However, existing commodity soil sensors are often expensive and the achieved accuracy is unsatisfactory. To address these issues, we present SoilCares, a low-cost soil sensing system enabling accurate and simultaneous monitoring of the concentration levels of soil moisture and macronutrients. SoilCares overcomes key challenges of accommodating diverse soil types and soil textures by introducing a novel membrane-based scheme. For moisture sensing, SoilCares leverages the multi-modal fusion of RF and NIR signals to significantly increase the sensing accuracy. Through delicate hardware design, we enable negligible-cost sensor data transmission using the existing sensing hardware, building up a complete end-to-end soil sensing system. SoilCares is cost-effective ($63.5), portable (0.5 kg), and low-power (236 mu W), making it suitable for insitu deployment. On-site experimental results show that SoilCares achieves high macronutrient sensing accuracy with a low RMSE of 0.138, and extremely low moisture estimation error of 1%, outperforming the state-of-the-art research and expensive commodity moisture sensors on the market.
引用
收藏
页码:196 / 209
页数:14
相关论文
共 50 条
  • [31] Simultaneous Monitoring of Soil Water Content and Salinity with a Low-Cost Capacitance-Resistance Probe
    Scudiero, Elia
    Berti, Antonio
    Teatini, Pietro
    Morari, Francesco
    SENSORS, 2012, 12 (12): : 17588 - 17607
  • [32] Indoor air quality monitoring and source apportionment using low-cost sensors
    Higgins, Christina
    Kumar, Prashant
    Morawska, Lidia
    ENVIRONMENTAL RESEARCH COMMUNICATIONS, 2024, 6 (01):
  • [33] Calibration of Low-Cost Moisture Sensors in a Biochar-Amended Sandy Loam Soil with Different Salinity Levels
    Gomez-Astorga, Maria Jose
    Villagra-Mendoza, Karolina
    Masis-Melendez, Federico
    Ruiz-Barquero, Anibal
    Rimolo-Donadio, Renato
    SENSORS, 2024, 24 (18)
  • [34] Testing of a commercial vector network analyzer as low-cost TDR device to measure soil moisture and electrical conductivity
    Moret-Fernandez, David
    Lera, Francisco
    Latorre, Borja
    Tormo, Jaume
    Revilla, Jesus
    CATENA, 2022, 218
  • [35] Enhancement and Metrological Characterization of an Accurate and Low-Cost Method Based on Seismic Wave Propagation for Soil Moisture Evaluation
    Attivissimo, F.
    Cannazza, G.
    Cataldo, A.
    De Benedetto, E.
    Fabbiano, L.
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2010, 59 (05) : 1216 - 1223
  • [36] An improved distributed sensing method for monitoring soil moisture profile using heated carbon fibers
    Cao, Ding-Feng
    Shi, Bin
    Wei, Guang-Qing
    Chen, Shen-En
    Zhu, Hong-Hu
    MEASUREMENT, 2018, 123 : 175 - 184
  • [37] Citizen science supporting agricultural monitoring with hundreds of low-cost sensors in comparison to remote sensing data
    Corbari, Chiara
    Paciolla, N.
    Ben Charfi, I
    Skokovic, D.
    Sobrino, J. A.
    Woods, M.
    EUROPEAN JOURNAL OF REMOTE SENSING, 2022, 55 (01) : 388 - 408
  • [38] Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing
    Popovic, Ivan
    Radovanovic, Ilija
    Vajs, Ivan
    Drajic, Dejan
    Gligoric, Nenad
    SENSORS, 2022, 22 (03)
  • [39] Indoor environment monitoring based on humidity conditions using a low-cost sensor network
    Bamodu, Oluleke
    Osebor, Felix
    Xia, Liang
    Cheshmehzangi, Ali
    Tang, Llewellyn
    RENEWABLE ENERGY INTEGRATION WITH MINI/MICROGRID, 2018, 145 : 464 - 471
  • [40] Towards Improved Field Application of Using Distributed Temperature Sensing for Soil Moisture Estimation: A Laboratory Experiment
    Apperl, Benjamin
    Bernhardt, Matthias
    Schulz, Karsten
    SENSORS, 2020, 20 (01)