Adaptive Linear Neuron (ADALINE) with Edge Computing for Reliable Data Computation

Abstract

Edge computing is used to minimize the data transfer rate from the various sensor to the main computing node by filtering the unwanted information from the raw data. In such situations Edge Computing devices will face challenges like network speed, distributed computing, delay, security, data accumulation. Here we going to address the few solutions for improving the data accuracy and to provide reliable data to the main computing node. We propose a model for reliable data collection using Adaptive Linear Neuron with Edge Computing, in which we having two segments such as Reliable data collection and irregularity data detection approach. We use multiple view sensor data collection to generate a reliable data and applying machine learning reinforcement learning to identify the irregular data from the sensors. Our implementation improves the performance in the aspects of IoT devices energy consumptions and provides reliable information to the computing system.