Because of the ubiquitous real-time applications they make possible, Wireless Sensor Network (WSN) technologies are becoming more important and popular in many different industries, including manufacturing, smart city planning, transportation, healthcare, and the IoT. In this study, we survey recent efforts to solve the problems of WSN coverage, deployment, and localization by using latest available techniques along with AI and machine learning techniques. We provide an in-depth review of the most current research on the topic, focusing on the studies that have used different latest available techniques along with AI and machine learning techniques to achieve different WSN goals in the previous several decades. This would let the reader learn about the most recent uses of AI and machine learning techniques for addressing various WSN issues. Then, we compare and evaluate the many AI and machine learning approaches employed in WSNs on a broad scale to help the research community choose the best approach and weigh the costs and advantages of using different AI and machine learning approaches to problems like WSN Localization.

artificial intelligence, machine learning, range based, range free, deployment, localization, wireless sensor networks.