Augmented Data Prediction Efficiency for Wireless Sensor Network Application by AI-ML Technology

Abstract

Practical wireless sensor network (WSN) demands cutting-edge artificial intelligence (AI) technology like deep learning (DL), which is the subset of AI paradigm to impart intelligence to end devices or nodes. Innovation of AI in WSN aids the enhanced connected world of internet of things (IoT). AI is an evolving area of intelligent learning methodologies by computers via machine learning algorithms (MLA). This chapter entirely deals with the implementation of AI technologies in the areas of advanced machine learning, language recognition using natural language processing (NLP), and image recognition through live example of machine learning. MLA are constructed to predict optimized output by giving training dataset inputs. In image recognition, an outcome model utilizing the existing reference model to predict DL-based AI prediction. Complex DL AI services is achieved by Bluemix sole power-driven Watson studio and Watson Assistant Service. Application programming interface keys are designated to connect Watson and Node Red Starter (NRS) to provide the web interface.