Research Article
An Adaptive Solution for Images Streaming in Vehicle Networks Using MQTT Protocol
@INPROCEEDINGS{10.1007/978-3-030-00410-1_31, author={Ming-Fong Tsai and Thanh-Nam Pham and Fu-Hsiang Ching and Le-Hung Chen}, title={An Adaptive Solution for Images Streaming in Vehicle Networks Using MQTT Protocol}, proceedings={IoT as a Service. Third International Conference, IoTaaS 2017, Taichung, Taiwan, September 20--22, 2017, Proceedings}, proceedings_a={IOTAAS}, year={2018}, month={10}, keywords={Internet of vehicles MQTT protocol 4G network Image streaming}, doi={10.1007/978-3-030-00410-1_31} }- Ming-Fong Tsai
Thanh-Nam Pham
Fu-Hsiang Ching
Le-Hung Chen
Year: 2018
An Adaptive Solution for Images Streaming in Vehicle Networks Using MQTT Protocol
IOTAAS
Springer
DOI: 10.1007/978-3-030-00410-1_31
Abstract
In this study, we explored solutions to improve the quality of real-time image transmission in vehicle networks. We deployed multiple cameras in each vehicle to collect scene data on the road. Then, the collected data was transmitted to a streaming server through a gateway and using a 4G internet connection. We use the MQTT protocol to implement our system since this is a protocol designed specifically for Internet of Things technologies and has several advantages in terms of image streaming. In addition, in order to adapt to the change in bandwidth channel due to the movement of vehicles, we propose an algorithm to control the quality of image capture which is based on threshold levels. This algorithm is based on the current throughput of local network nodes, as compared with threshold values, to control the rate of sending data from each local node in subsequent transmissions. The results of simulation show that our proposed network significantly reduces both end-to-end delay and the delay in arrival of messages in the network when the number of nodes increases. The experimental results showed that the collected images are of high quality and allow accurate analysis of the surrounding environment of the moving vehicles.