Intelligent Video Surveillance Platform for Wireless Multimedia Sensor Networks

The Internet of Things (IoT) is faced with challenges that require green solutions and energy-efficient paradigms. Architectures (such as ARM) have evolved significantly in recent years, with improvements to processor efficiency, essential for always-on devices, as a focal point. However, as far as software is concerned, few approaches analyse the advantages of writing efficient code when programming IoT devices. Therefore, this proposal aims to improve source code optimization to achieve better execution times. In addition, the importance of various techniques for writing efficient code for Raspberry Pi devices is analysed, with the objective of increasing execution speed. A complete set of tests have been developed exclusively for analysing and measuring the improvements achieved when applying each of these techniques. This will raise awareness of the significant impact the recommended techniques can have.

Section: Introductionmentioning

confidence: 99%

Evaluation of Strategies for the Development of Efficient Code for Raspberry Pi Devices

Corral-García¹,

González-Sánchez²,

Pérez-Toledano

2018

“…Routing algorithms for WMSNs is an active research area [15,17,19,20]. A pair-wise directional geographical routing was proposed to solve energy issue in multi-path routing for WMSNs [21].…”

Section: Related Workmentioning

confidence: 99%

“…Routing protocols that employ a single path approach tend to be very sensitive to the highly dynamic nature of the wireless links and the limited capacity of the multi-hop path, which make them incapable of providing high data communication for WMSNs [12,13,14]. Moreover, the performance of the WMSN can be influenced profoundly by congestion [15,16] since the sensor nodes have limited resources like bandwidth, memory, and computational energy. As a result, many different types of routing protocols with various approaches for enhancing the efficiency of the routing protocols such as clustering, multipath routing, and multi-hop routing have been advanced in the literature [17].…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Multipath Routing Algorithm for Wireless Multimedia Sensor Network

Genta

Lobiyal

Abawajy

2019

Wireless multimedia sensor networks (WMSNs) are capable of collecting multimedia events, such as traffic accidents and wildlife tracking, as well as scalar data. As a result, WMSNs are receiving a great deal of attention both from industry and academic communities. However, multimedia applications tend to generate high volume network traffic, which results in very high energy consumption. As energy is a prime resource in WMSN, an efficient routing algorithm that effectively deals with the dynamic topology of WMSN but also prolongs the lifetime of WMSN is required. To this end, we propose a routing algorithm that combines dynamic cluster formation, cluster head selection, and multipath routing formation for data communication to reduce energy consumption as well as routing overheads. The proposed algorithm uses a genetic algorithm (GA)-based meta-heuristic optimization to dynamically select the best path based on the cost function with the minimum distance and the least energy dissipation. We carried out an extensive performance analysis of the proposed algorithm and compared it with three other routing protocols. The results of the performance analysis showed that the proposed algorithm outperformed the three other routing protocols.

“…WMSNs are often composed of many wirelessly interconnected devices such as low-cost hardware CMOS cameras, microphones, and other sensor nodes with computational and wireless sensing capabilities; they can help to complete varies of tasks in remote sensing [2,6,7].…”

Section: Introductionmentioning

confidence: 99%

Multi-Level Features Extraction for Discontinuous Target Tracking in Remote Sensing Image Monitoring

Zhou

Duan

et al. 2019

Many techniques have been developed for computer vision in the past years. Features extraction and matching are the basis of many high-level applications. In this paper, we propose a multi-level features extraction for discontinuous target tracking in remote sensing image monitoring. The features of the reference image are pre-extracted at different levels. The first-level features are used to roughly check the candidate targets and other levels are used for refined matching. With Gaussian weight function introduced, the support of matching features is accumulated to make a final decision. Adaptive neighborhood and principal component analysis are used to improve the description of the feature. Experimental results verify the efficiency and accuracy of the proposed method.