Design Of Node In WSN And Energy Optimization Based On Solar Charging

With the popularization of the evolution of information technology and network technology, wireless sensor networks are increasingly being applied in various fields. Wireless sensors are mostly tiny in size, low cost and easy to deploy, but still there are some limitations. More and more wireless sensors are required to stable decades or more, but the limiting factors between the battery capacity and the volume of the node are difficult to resolve, as well as the battery replacement. Therefore, energy harvesting has become an available method.We have designed a node which conforms to the WSN-HEAP scheme. The node uses a solar panel and a lithium battery to collect and store energy. Operational efficiency and the performance of WSN and nodes are measured by experiments under different circumstances, with different transmit power, distances and other impact factors.In order to quantify the solar charging characteristics, the solar charging nodes in TinyOS will first harvest the solar energy. After certain charging time, when enough energy has been accumulated, the BaseStation will be switched on to get data from solar charging nodes. After resynchronizing the BaseStation and the charging nodes, solar charging nodes will begin to send message by broadcast. As soon as the message is received, the BaseStation will read the message and analyze the content data through PC. Data collected will be stored in a file in PC. By measuring and analyzing the data, we can get the curve of the voltage in specific time, and then we can study the battery level and packet delivery ratio.Finally, based on the experimental results, this paper also offers certain optimization, which provides guidance for future work.The innovations of this paper are:(1) Customized design and implementation for telosb solar-powered sensor nodes;(2) Design and implementation of collection and measurement systems based on the collection of solar energy wireless sensor network information;(3) Design and implementation of experiments based on measurements carried out and data analysis.