The Compressed Sensing of Wireless Sensor Networks Based on Internet of Things

In the application of wireless sensor networks, poor computing power, limited storage space, and short duration have severely restricted the development of wireless sensor networks. Compressed sensing technology is an emerging signal front-end processing technology, which breaks the original use restrictions, saves storage space and energy consumption, and has become a research hotspot in the field of electronic technology. Based on the wireless network, this paper combines the big data P2P direct connection perception idea to expand the compression algorithm spatially. First, locate the data on different nodes, then perform task allocation on the data compression calculation in the cloud, and finally wait for the node to compress the data to be compressed. The results show that compressed sensing technology can accurately locate objects, overcome node defects in wireless sensor networks, reduce node energy consumption, improve data processing capabilities and calculation speed, and track targets. Specific references for more accurate investigation and positioning.