Design of Integrated Artificial Intelligence Techniques for Video Surveillance on IoT Enabled Wireless Multimedia Sensor Networks

The recent advancements in the Internet of Things (IoT) and Wireless Multimedia Sensor Networks (WMSN) made high-speed multimedia streaming, data processing, and essential analytics processes with minimal delay. Multimedia sensors used in WMSN-based surveillance applications are beneficial helpful in attaining accurate and elaborate details. However, it has become essential to design an effective and lightweight solution for data traffic management in WMSN owing to the massive quantities of data, generated by multimedia sensors. The development of Artificial Intelligence (AI) and Machine Learning (ML) techniques can be leveraged to investigate, collect, store, and process multimedia streaming data for decision-making in real-time scenarios. In this aspect, the current study develops an Integrated AI technique for Video Surveillance in IoT-enabled WMSN, called IAIVS-WMSN. The proposed IAIVS-WMSN technique aims to design a practical scheme for object detection and data transmission in WMSN. The proposed IAIVS-WMSN approach encompasses three stages: object detection, image compression, and clustering. The Mask Regional Convolutional Neural Network (Mask RCNN) technique is primarily utilized for object detection in the target region. Besides, Neighbourhood Correlation Sequence-based Image Compression (NCSIC) technique is applied to reduce data transmission. Finally, Artificial Flora Algorithm (AFA)-based clustering technique is designed for the election of Cluster Heads (CHs) and construction clusters. The design of object detection with compression and clustering techniques for WMSN shows the novelty of the work. These three processes’ designs enable one to accomplish effective data transmission in IoT-enabled WMSN. The researchers conducted multiple simulations to highlight the supreme performance of the IAIVS-WMSN approach. The simulation outcomes inferred the enhanced performance of the IAIVS-WMSN algorithm to the existing approaches

GECOM: GREEN COMMUNICATION CONCEPTS FOR ENERGY EFFICIENCY IN WIRELESS MULTIMEDIA SENSOR NETWORK

Wireless multimedia sensor network (WMSN) is one of broad wide application for developing a smart city. Each node in the WMSN has some primary components: sensor, microcontroller, wireless radio, and battery. The components of WMSN are used for sensing, computing, communicating between nodes, and flexibility of placement. However, the WMSN technology has some weakness, i.e. enormous power consumption when sending a media with a large size such as image, audio, and video files. Research had been conducted to reduce power consumption, such as file compression or power consumption management, in the process of sending data. We propose Green Communication (GeCom), which combines power control management and file compression methods to reduce the energy consumption. The power control management method controls data transmission. If the current data has high similarity with the previous one, then the data will not be sent. The compression method compresses massive data such as images before sending the data. We used the low energy image compression algorithm algorithm to compress the data for its ability to maintain the quality of images while producing a significant compression ratio. This method successfully reduced energy usage by 2% to 17% for each data.  

A Fusion-Based Framework for Wireless Multimedia Sensor Networks in Surveillance Applications

Multimedia sensors enable monitoring applications to obtain more accurate and detailed information. However, the development of efficient and lightweight solutions for managing data traffic over wireless multimedia sensor networks (WMSNs) has become vital because of the excessive volume of data produced by multimedia sensors. As part of this motivation, this paper proposes a fusion-based WMSN framework that reduces the amount of data to be transmitted over the network by intra-node processing. This framework explores three main issues: 1) the design of a wireless multimedia sensor (WMS) node to detect objects using machine learning techniques; 2) a method for increasing the accuracy while reducing the amount of information transmitted by the WMS nodes to the base station, and; 3) a new cluster-based routing algorithm for the WMSNs that consumes less power than the currently used algorithms. In this context, a WMS node is designed and implemented using commercially available components. In order to reduce the amount of information to be transmitted to the base station and thereby extend the lifetime of a WMSN, a method for detecting and classifying objects on three different layers has been developed. A new energy-efficient cluster-based routing algorithm is developed to transfer the collected information/data to the sink. The proposed framework and the cluster-based routing algorithm are applied to our WMS nodes and tested experimentally. The results of the experiments clearly demonstrate the feasibility of the proposed WMSN architecture in the real-world surveillance applications

Copyright protection of scalar and multimedia sensor network data using digital watermarking

This thesis records the research on watermarking techniques to address the issue of copyright protection of the scalar data in WSNs and image data in WMSNs, in order to ensure that the proprietary information remains safe between the sensor nodes in both. The first objective is to develop LKR watermarking technique for the copyright protection of scalar data in WSNs. The second objective is to develop GPKR watermarking technique for copyright protection of image data in WMSN

Evaluation of Video Quality in Wireless Multimedia Sensor Networks

Simulating wireless sensor networks; there implementation and evaluation, require the use of a discrete event simulator. Omnet++ is quite a powerful simulator which supports concise and easy modeling of wired as well as wireless sensors environment. Scenarios involving multimedia transmissions with characteristics of video quality control and evaluation must be computed on the basis of Quality of Experience which relies on user’s perception to maintain the video quality. For the multimedia growth and awareness of future WMSNs, it is quite necessary that the performance should be tested for different types of radio models. So varying the radio parameters may allow for the optimization and improvement of the video quality. In this paper we have provided a test bench for the easy evaluation and optimization of the performance of WMSNs using different radio models. The performance is evaluated based on the QoE metrics; i.e. PSNR(Peak Signal-to-Noise ratio) and MoS(Mean Opinion Score), which depend on user’s perception to maintain the video quality

Wireless multimedia sensor networks, security and key management

Wireless Multimedia Sensor Networks (WMSNs) have emerged and shifted the focus from the typical scalar wireless sensor networks to networks with multimedia devices that are capable to retrieve video, audio, images, as well as scalar sensor data. WMSNs are able to deliver multimedia content due to the availability of inexpensive CMOS cameras and microphones coupled with the significant progress in distributed signal processing and multimedia source coding techniques. These mentioned characteristics, challenges, and requirements of designing WMSNs open many research issues and future research directions to develop protocols, algorithms, architectures, devices, and testbeds to maximize the network lifetime while satisfying the quality of service requirements of the various applications. In this thesis dissertation, we outline the design challenges of WMSNs and we give a comprehensive discussion of the proposed architectures and protocols for the different layers of the communication protocol stack for WMSNs along with their open research issues. Also, we conduct a comparison among the existing WMSN hardware and testbeds based on their specifications and features along with complete classification based on their functionalities and capabilities. In addition, we introduce our complete classification for content security and contextual privacy in WSNs. Our focus in this field, after conducting a complete survey in WMSNs and event privacy in sensor networks, and earning the necessary knowledge of programming sensor motes such as Micaz and Stargate and running simulation using NS2, is to design suitable protocols meet the challenging requirements of WMSNs targeting especially the routing and MAC layers, secure the wirelessly exchange of data against external attacks using proper security algorithms: key management and secure routing, defend the network from internal attacks by using a light-weight intrusion detection technique, protect the contextual information from being leaked to unauthorized parties by adapting an event unobservability scheme, and evaluate the performance efficiency and energy consumption of employing the security algorithms over WMSNs