Wireless multimedia sensor networks (WMSNs) are increasingly being deployed for surveillance and monitoring applications. WMSNs applications produce large amount of data, which require high transmission rates. An efficient and seamless delivery of multimedia services in WMSNs is still a challenging task. This article proposes an intelligent video surveillance platform (IVSP) for wireless multimedia sensor networks. IVSP presents the design of a networked system for joint rate control and error control of video over resource-constrained embedded devices. First, a combination of two different congestion indicators is introduced to differentiate between congestion levels and handle them accordingly. Second, a feedback-based rate controller is developed to maximize received video quality, in which sensor nodes can adaptively adjust their sending rates. Finally, a different retransmission mechanism for different packets is proposed. Lost packets can be stored temporarily and resend when free channel is available to avoid congestion. The core component of IVSP is an open source hardware platform, which is based on Raspberry Pi sensor nodes. IVSP is extensively evaluated on 7 Raspberry Pi sensor nodes. We present the results of 7-node real-world deployment of IVSP in a video surveillance application and show that it works well in long-term deployments.

Wireless multimedia sensor networks (WMSNs) generate a huge amount of multimedia data. Congestion is one of the most challenging open issues in WMSNs. Congestion causes low throughput, high packet loss and low energy efficiency. Congestion happens when the data carried by the network surpasses the available capacity. This article presents an energy-efficient distributed congestion control protocol (DCCP) to mitigate congestion and improve end-to-end delay. Compared to the other protocols, the DCCP protocol proposed in this article can alleviate congestion by intelligently selecting the best path. First, congestion is detected by using two congestion indicators. Second, each node aggregates the received data and builds a traffic congestion map. The traffic congestion map is used to calculate the best path. Therefore, the traffic is balanced on different routes, which reduces the end-to-end delay. Finally, a rate controller is designed to prevent congestion in the network by sending a congestion notification message to a source node. After receiving a congestion notification message, the source node immediately adjusts its transmission rate. Experimental results based on raspberry pi sensor nodes show that the proposed DCCP protocol significantly improves network performance and is superior to existing modern congestion control protocols.

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