@article{uninimx5637,
           title = {Underwater Wireless Sensor Networks: Enabling Technologies for Node Deployment and Data Collection Challenges},
           pages = {1--1},
          author = {Monika Chaudhary and Nitin Goyal and Abderrahim Benslimane and Lalit Kumar Awasthi and Ayed Alwadain and Aman Singh},
           month = {Febrero},
         journal = {IEEE Internet of Things Journal},
            year = {2022},
        keywords = {Data collection, data communication, node deployment, underwater wireless sensor networks},
        abstract = {The development of underwater wireless sensor networks (UWSNs) has attracted great interest from many researchers and scientists to detect and monitor unfamiliar underwater domains. To achieve this goal, collecting data with an underwater network of sensors is primordial. Moreover, real-time information transmission needs to be achieved through efficient and enabling technologies for node deployment and data collection in UWSN. The Internet of Things (IoT) helps in real time data transmission, and it has great potential in UWSN, i.e., the Internet of Underwater Things (IoUT). The Internet of Underwater Things (IoUT) is a modern communication ecosystem for undersea things in marine and underwater environments. Intelligent boats and ships, automatic maritime transportation, location and navigation, undersea discovery, catastrophe forecasting and avoidance, as well as intelligent monitoring and security are all intertwined with IoUT technology. In this paper, the enabling technologies of UWSN along with several fundamental key aspects are scrupulously explained. The study aims to inquire about node deployment and data collection strategies, and then encourages researchers to lay the groundwork for new node deployment and advanced data collection techniques that enable effective underwater communication techniques. Besides different types of communication media, applications of UWSNs are also part of this paper. Various existing data collection protocols based on the deployment models are simulated using Network Simulator (NS 2.30) to analyse and compare the performance of state-of-the-art techniques.},
             url = {http://repositorio.unini.edu.mx/id/eprint/5637/}
}