{'fraction_non_alphanumeric': 0.013439218081857055, 'fraction_numerical': 0.0, 'mean_word_length': 5.474308300395257, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
WSN topology control design via integration of Kalman filtering and adaptive estimation

The research field of wireless sensor networks is a challenging area of engineering and science. In contrast to most traditional networks, sensor nets of wireless sensor networks encompass numerous small battery powered autonomous devices which are referred to as the sensor nodes. These devices have data processing and short range radio communication capabilities. Each node relies on the wireless channels for transmitting data and receiving data from other nodes. The deployment of sensor nodes is subject to various types of harsh environments. Wireless sensor networks differ in network densities, from sparse to dense deployments, which requires the adaptive protocols. On the other hand, small scale and low energy wireless devices are needed for communication. The combination of computing, sensing and communication technologies makes it possible. With the dense network deployment, broadcasting by simple flooding will lead to information redundancy. It gives rise to the application of adaptive topology control to the wireless sensor network. The maximum distance of the individual node could communicate with each other is characterized by the communication units on the sensor node. The location performance and energy usage, based on communication distance, can be evaluated by the Kalman filter which exploits the different selection approaches. In this article, topology control of the wireless sensor networks via integration of Kalman filters and adaptive estimation has been proposed for the design of wireless sensor networks.