Abstract
In this paper, a real-time image transmission algorithm in WSN with limited bandwidth networks is studied. Firstly, a simple and effective monitoring network architecture is established, which allows multiple video monitoring nodes to access the network, and the data transmission is controlled by the synchronization mechanism without collision. Then, the image data is compressed locally at the monitoring nodes (over 85%), so that the image of each node can meet the needs of real-time data transmission, and the overall power consumption of the system is greatly reduced. Finally, based on NVIDIA TX1, four test nodes are constructed to test the algorithm cumulatively, which verifies the effectiveness of the system framework and compression algorithm.
Highlights
1.1 BackgroundWith the decrease of unit cost and the great improvement of performance, frontend embedded high performance computing systems such as NVIDIA TX1 get more and more attention in the Internet of Things and artificial intelligence
A large amount of data generated by the network will cause great pressure to the power consumption of the limited wireless network bandwidth and the nodes (Recent work has investigated the application of image coding in wireless sensor networks (WSN) for high-bandwidth networks [3])
Due to the high complexity and specificity of in-situ data processing, our research focuses on the system application in complex environment, which can realize real-time image transmission under the condition of limited bandwidth and take into account the requirement of low power consumption so that it can be long-term deployed outdoors [4]
Summary
With the decrease of unit cost and the great improvement of performance, frontend embedded high performance computing systems such as NVIDIA TX1 get more and more attention in the Internet of Things and artificial intelligence. A large amount of data generated by the network will cause great pressure to the power consumption of the limited wireless network bandwidth and the nodes (Recent work has investigated the application of image coding in WSNs for high-bandwidth networks [3]). Compression or processing, which results in the emerging term of "edge calculation", it is more pointed to such as NVIDIA TX1 which has stronger computing ability and can meet the needs of a certain complex computing task and better support the development of future systems such as Internet of Things and artificial intelligence. Due to the high complexity and specificity of in-situ data processing, our research focuses on the system application in complex environment, which can realize real-time image transmission under the condition of limited bandwidth and take into account the requirement of low power consumption so that it can be long-term deployed outdoors [4]. It is necessary to pay more attention to the image compression algorithm on the front-end node to effectively reduce the network load pressure
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