Real-Time Auto Calibration for Heterogeneous Wireless Sensor Networks

The constant technological advances bring new devices to the market every day. Due this, heterogeneous Wireless Sensor Network (WSN) are common scenarios in many applications. Neural (NN) based models may implement particular features provided by sensor hardware collect surrounding environment information. Thus, a can provide specific group of while others do not. In this perspective, it be required, for some sensors WSN, trained and have their data manually categorized, which does not scale, particularly large WSN setups. light problem, paper proposes Real-time (RT) auto-calibration framework allow collaborate training process enable uncalibrated join network. method need previous knowledge about features. Also, proposal is validated practical experiments evaluating its accuracy image classification. experimental results demonstrate feasibility proposed method.