Sensor Identification and Fault Detection in IoT Systems

Tusher Chakraborty, A. Nambi, Ranveer Chandra, Rahul Sharma, Manohar Swaminathan, Zerina Kapetanovic
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引用次数: 3

Abstract

The proliferation of Internet of Things (IoT) devices has led to the deployment of various types of sensors in the homes, offices, buildings, lawns, cities, and even in agricultural farms. Due to the diverse nature of IoT deployments and the likelihood of sensor failures in-the-wild, a key challenge in the design of IoT systems is ensuring the integrity, accuracy, and fidelity of sensor data. We present a system based on the Fall-curve primitive -- a sensor's voltage response when the power is turned off -- to characterize the sensor. A sensor's Fall-curve constitutes a unique signature using which it is possible to identify the sensor and also detect whether it is operating correctly or not. In this demo, we show Fall-curve in action to accurately detect and identify the sensors connected to an IoT device. Furthermore, we also show that Fall-curves can reliably detect various transient and permanent sensor faults in an IoT device.
物联网系统中的传感器识别和故障检测
物联网(IoT)设备的激增导致各种类型的传感器在家庭、办公室、建筑物、草坪、城市甚至农场中部署。由于物联网部署的多样性和传感器在野外故障的可能性,物联网系统设计中的一个关键挑战是确保传感器数据的完整性、准确性和保真度。我们提出了一个基于下降曲线原语的系统——当电源关闭时传感器的电压响应——来表征传感器。传感器的下降曲线构成了一个独特的特征,使用它可以识别传感器,也可以检测它是否正常工作。在这个演示中,我们展示了下降曲线的作用,以准确地检测和识别连接到物联网设备的传感器。此外,我们还表明下降曲线可以可靠地检测物联网设备中的各种瞬态和永久传感器故障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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