4.8 Article

CalibrationTalk: A Farming Sensor Failure Detection and Calibration Technique

期刊

IEEE INTERNET OF THINGS JOURNAL
卷 8, 期 8, 页码 6893-6903

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3036859

关键词

Calibration; Soil; Actuators; Humidity; Temperature sensors; Internet of Things; Aging; Failure detection; sensor calibration; smart agriculture; soil moisture sensor

资金

  1. Center for Open Intelligent Connectivity from the Featured Areas Research Center Program
  2. Ministry of Science and Technology Academia-Industry Research Center
  3. Ministry of Science and Technology [1092221-E-009-089-MY2]
  4. Ministry of Economic Affairs [107-EC-17-A-02-S5-007]

向作者/读者索取更多资源

The article introduces the CalibrationTalk mechanism to address the important issue of sensor failure detection and calibration in IoT applications, using smart agriculture as an example. Through measurements and analytical modeling, a method for detecting sensor failures within a specific time frame is proposed, enabling automatic calibration of sensors to resolve inaccuracies caused by aging.
Sensor failure detection and calibration is an important issue for Internet of Things applications. Many smart applications fail due to inaccurate data produced by their sensors. To solve this issue, we propose the CalibrationTalk mechanism. We use smart agriculture as an example to show how CalibrationTalk automatically fixes the sensing accuracy problems in commercial farm operations. Besides manufacturing variation, hardware malfunction and aging, sensing inaccuracy may be caused by soil erosion of rain or irrigation, which changes the positions and the angles of the sensors inserted in the soil. The above sensor failure problems can be detected by CalibrationTalk. In this article, we first extend our previous work to detect sensor failures. If the sensors become inaccurate due to aging or similar reasons, CalibrationTalk automatically calibrates the sensors in the farm fields. We conduct measurements and analytic modeling to investigate the performance of CalibrationTalk, which suggests that to detect a potential moisture sensor failure, it is appropriate to set the detection time as 30 min for moisture sensors. With this setup, true failure is detected while false detections rarely occur. For a detected sensor failure due to aging, CalibrationTalk can automatically build a calibration table. During the calibration table establishment period, the sensors still produce correct measured data and do not interfere with the normal operation of smart farming. The value of CalibrationTalk lies in its power of automation for sensor failure detection and calibration processes developed in this article.

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