Wireless sensor networks and internet of things for E-services applied natural language processing and deep learning

Abstract

Abstract Introduction . The internet of things integration with wireless sensor networks can monitor and record the physical conditions of the environment and forward the collected data to a central location. Natural language processing provides a human-data relationship (H2DR) that deep learning uses to train models of artificial neural networks representing human thoughts. Objective To present methods on how remote systems collect data and semantically analyze and determine a situation. Method and material: Natural language processing applied deep learning on content extraction and evaluation was examined to showcase the strength of e-services based on WSNs and IoTs. Results Based on WSNs and IoTs on e-services, a score of 3.61 out of 5 grades was recorded. Conclusion The study concluded that WSNs and IoTs applied NLP and DL are the best network technologies for E-services to achieve, content awareness, context extraction, summarization, and security standards.