Wireless sensor network
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A wireless sensor network (WSN) is a distributed system composed of spatially dispersed, low-power sensor nodes that wirelessly collect, process, and transmit environmental or physical data to a central system or to one another. Each node typically integrates sensing hardware, a microcontroller, and a radio transceiver, enabling autonomous, infrastructure-free operation across diverse environments. In robotics and AI, WSNs serve as perceptual infrastructure for tasks including robot localization, environmental monitoring, surveillance, and multi-robot coordination. Robots can interact with WSNs as mobile data collectors, traversing sensor fields to gather measurements, or as mobile nodes that extend network coverage and assist in localizing stationary sensors. WSNs also enable "intelligent spaces," where embedded sensing allows environments to perceive and respond to activity. AI techniques such as sensor fusion, distributed estimation, and machine learning are frequently applied to process the large volumes of noisy, heterogeneous data these networks generate. WSNs matter because they dramatically extend a system's sensing reach without requiring continuous human intervention or costly wired infrastructure. Their scalability and low cost make them foundational to applications ranging from disaster response and smart cities to precision agriculture and industrial monitoring, directly enabling more capable and autonomous robotic systems.
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