3D Localization in the Era of IIoT by Integrating Machine Learning With 3D Adaptive Stochastic Control Algorithm

Abstract

In recent decades, technological advancements have reshaped industries, particularly in communication, consumer electronics, and medical electronics. The rise of the industrial internet of things (IIoT) has been transformative, revolutionizing industrial processes. Accurate node localization within IIoT-enabled systems is crucial for operational efficiency and informed decision-making. This chapter introduces the 3D adaptive stochastic control algorithm (ASCA), designed explicitly for IIoT environments with machine learning capabilities, including convolutional neural networks. The algorithm leverages received signal strength indicator data and sophisticated machine learning algorithms to accurately determine node positions in a 3D industrial space, offering a cost-effective and energy-efficient alternative. Comparative evaluations show the superiority of the 3D ASCA algorithm, with an average localization error ranging from 0.37 to 0.7, surpassing benchmarks set by other algorithms.