النشر العلمي

  • Modeling Multi-Camera Coverage for Placement Optimization

Modeling camera coverage is essential in many visual sensor applications. Particularly in visual surveillance, planning the coverage modeling is critical to estimate the coverage and to design the sensor deployment. Given the environment representation, the coverage model produces the sensor coverage based on the device specifications; however, analyzing the visibility in an arbitrary scene is a challenging part. This letter proposes a preliminary setup based on imaging techniques to assist in solving the camera placement problem. The proposed setup computes the camera coverage in a two-dimensional digitized floor-plan. Additionally, a pixelwise line drawing routine analyzes the ray's visibility from the viewpoint to the width of the field of view. Three commercial surveillance cameras are modeled and the obtained result forms the necessary coverage table for subsequent optimization tasks. Finally, the …

published in IEEE Sensors Letters

  • Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming

Optimizing the visual sensors coverage to perform security monitoring tasks has an undeniable impact on the performance as well as the cost of video surveillance systems. The placement arrangement is an NP-hard problem, in which the main target is to seek an approximate solution. This paper addresses the placement of security cameras to maximize the total coverage of the camera network. The coverage of the visual sensor array is modeled descriptively using an enhanced pinhole camera model to obtain the layout of the field of view. The main contribution of the paper is to introduce a dynamic programming algorithm, which defines an optimal policy for solving the visual sensor coverage problem. To validate the proposed algorithm, we compared the outcomes of the dynamic programming algorithm with the existing benchmarking placement optimization techniques. The assessment reveals the effectiveness …

published in IEEE Sensors Journal

  • Work in Progress: LEACH-Based Energy Efficient Routing Algorithm for Large-Scale Wireless Sensor Networks

Wireless sensor network (WSN) is one of the active research topics which links telecommunication and microelectro- mechanical system (MEMS). WSN has a broad range of important applications such as environmental monitoring, health monitoring, and various industrial and military applications. The various routing protocols in WSN manage the load balance, energy consumption and the expansion of the network. This study outlines the procedure of developing scalable, low energy and highly adaptive clustering hierarchy routing protocol. The main objective is to maintain the network lifespan over the network expansion. We refer to the proposed protocol as Energy-Efficient Scalable Routing Algorithm (EESRA). The EESRA protocol is expected to optimize the wellknown LEACH protocol for more energy efficiency on a large scale WSN.

published in Journal of Telecommunication, Electronic and Computer Engineering (JTEC)

  • Optimizing Visual Sensor Coverage Overlaps for Multiview Surveillance Systems

Modern surveillance systems rely on coverage overlapping to attain multi-viewing capabilities and to support coverage redundancy. This paper examines the coverage overlapping configurations in visual surveillance systems. This paper proposes a robust dynamic programming framework to optimize visual surveillance sensor coverage overlaps. Based on visual sensor parameters information, and the features of the area to be monitored, this paper uses a deterministic modeling approach to model the sensor coverage in a 2-D space. Then, the minimization and the maximization arrangements of the coverage overlapping are formulated as discrete optimization problems. The obtained solutions from the dynamic programming technique are evaluated with respect to local and global greedy search algorithms. The results reveal the feasibility of the proposed technique compared with the benchmarked optimization methods in terms of the amount of coverage redundancy.

published in IEEE Sensors Journal

  • Optimizing Camera Placement Based on Task Modeling

Optimizing the camera configurations impacts the performance of the video surveillance applications. Where, proper camera placement reduces the total cost and increases the surveillance efficiency. Various methods are used to optimize the coverage such as greedy search and linear programming, hence the typical cost function for optimizing the camera placement focuses on obtaining the maximum coverage regardless of the area significance or the camera capabilities. This work proposes a novel cost function for camera placement problem. The proposed approach models the camera vision capability based on the task to be performed. The model represents the significance of the monitored area by means of risk maps. Then the coverage optimization is performed based on the area significance modeling results and the sensor capability. The outcomes show the applicability of the proposed cost function in various scenarios.

published in IEEE SENSORS CONFERENCE 2018

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