Results 1 - 10
of
17
Barrier Coverage in Camera Sensor Networks
"... Barrier coverage has attracted much attention in the past few years. However, most of the previous works focused on traditional scalar sensors. We propose to study barrier coverage in camera sensor networks. One fundamental difference between camera and scalar sensor is that cameras from different p ..."
Abstract
-
Cited by 16 (1 self)
- Add to MetaCart
(Show Context)
Barrier coverage has attracted much attention in the past few years. However, most of the previous works focused on traditional scalar sensors. We propose to study barrier coverage in camera sensor networks. One fundamental difference between camera and scalar sensor is that cameras from different positions can form quite different views of the object. As a result, simply combining the sensing range of the cameras across the field does not necessarily form an effective camera barrier since the face image (or the interested aspect) of the object may be missed. To address this problem, we use the angle between the object’s facing direction and the camera’s viewing direction to measure the quality of sensing. An object is full-view covered if there is always a camera to cover it no matter which direction it faces and the camera’s viewing direction is sufficiently close to the object’s facing direction. We study the problem of constructing a camera barrier, which is essentially a connected zone across the monitored field such that every point within this zone is full-view covered. We propose a novel method to select camera sensors from an arbitrary deployment to form a camera barrier, and present redundancy reduction techniques to effectively reduce the number of cameras used. We also present techniques to deploy cameras for barrier coverage in a deterministic environment, and analyze and optimize the number of cameras required for this specific deployment under various parameters.
Minimizing Service Delay in Directional Sensor Networks
"... Abstract—In directional sensor networks, sensors can steer around to serve multiple target points. Most previous works assume there are always enough deployed sensors so that all target points can be served simultaneously. However, this assumption may not hold when the mission requirement changes or ..."
Abstract
-
Cited by 7 (2 self)
- Add to MetaCart
(Show Context)
Abstract—In directional sensor networks, sensors can steer around to serve multiple target points. Most previous works assume there are always enough deployed sensors so that all target points can be served simultaneously. However, this assumption may not hold when the mission requirement changes or when more target points need to be served. Since it is not always practical to deploy new sensors, we propose to reconfigure the network by letting existing sensors steer and serve the targets periodically. As a result, targets may not be served continuously, and the service delay affects the quality of service. One important problem is how to choose the optimal set of targets to serve by each sensor such that the maximum service delay is minimized. We first show that this problem is NP-complete, and then we propose a centralized protocol whose performance is bounded by a logarithm factor of the optimal solution. We also propose a distributed protocol which achieves the same performance as the centralized protocol. Finally, we extend the optimization model and the protocols by considering the rotation delay, which is critical for some applications but ignored by previous work. I.
Barrier coverage in hybrid directional sensor networks
- in Mobile Ad-Hoc and Sensor Systems (MASS), 2013 IEEE 10th International Conference on, Oct 2013
"... Abstract-Barrier coverage is a critical issue in wireless sensor networks for security applications (e.g., border protection) where directional sensors (e.g., cameras) are becoming more popular and advantageous than omni-directional scalar sensors for the extra dimensional information they provide. ..."
Abstract
-
Cited by 2 (0 self)
- Add to MetaCart
(Show Context)
Abstract-Barrier coverage is a critical issue in wireless sensor networks for security applications (e.g., border protection) where directional sensors (e.g., cameras) are becoming more popular and advantageous than omni-directional scalar sensors for the extra dimensional information they provide. However, barrier coverage can not be guaranteed after initial random deployment of sensors, especially for directional sensors with limited sensing angles. In this paper, we study how to efficiently achieve barrier coverage in hybrid directional sensor networks by moving mobile sensors to fill in gaps and form a barrier with stationary sensors. In specific, we introduce the notion of directional barrier graph to model the barrier coverage formation problem. We prove that the minimum number of mobile sensors required to form a barrier with stationary sensors is the length of the shortest path from the source node to the destination node on the directional barrier graph. We then formulate the problem of minimizing the cost of moving mobile sensors to fill in the gaps on the shortest path as a minimum cost bipartite assignment problem, and solve it in polynomial time using the Hungarian algorithm. Both analytical and experimental studies demonstrate the effectiveness of the proposed algorithm.
Full-View Barrier Coverage with Rotatable Camera
- Sensors, IEEE/CIC International Conference on Communications in China (ICCC
, 2014
"... Abstract—Camera sensors can collect visual information from regions of interest (RoI) and provide more informa-tion to classify the intruder. In practice, randomly deployed camera sensors can not guarantee that the barrier is full-view covered, and lead to a waste of sensing resources. Our work take ..."
Abstract
-
Cited by 1 (1 self)
- Add to MetaCart
(Show Context)
Abstract—Camera sensors can collect visual information from regions of interest (RoI) and provide more informa-tion to classify the intruder. In practice, randomly deployed camera sensors can not guarantee that the barrier is full-view covered, and lead to a waste of sensing resources. Our work takes the first attempt to explore the deploy-ment strategy to achieve full-view barrier coverage with rotatable camera sensors. We propose a method to select camera sensors from an existing and arbitrary deployment and determine their orientation to obtain a full-view barrier coverage. Our simulation results demonstrate that our algorithm outperforms existing algorithms for fixed directional camera sensors in saving the number of camera sensors. I.
Critical Sensing Range for Mobile Heterogeneous Camera Sensor Networks
, 2013
"... Abstract—In camera sensor networks (CSNs), full view cov-erage, in which any direction of any point in the operational region is covered by at least one camera sensor, is of great significance since image shot at the frontal viewpoint considerably increases the possibility to recognize the object. H ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
(Show Context)
Abstract—In camera sensor networks (CSNs), full view cov-erage, in which any direction of any point in the operational region is covered by at least one camera sensor, is of great significance since image shot at the frontal viewpoint considerably increases the possibility to recognize the object. However, finding the critical condition to achieve full view coverage in mobile heterogeneous CSNs remains an open question. In this paper, we analyze both the static and mobile random deployed camera sensor networks. A centralized parameter – equivalent sensing radius (ESR) – is defined to evaluate the critical requirement for asymptotic full view coverage in heterogeneous CSNs. We derive the critical sensing range for full view coverage under static model, 2-dimensional random walk mobility model, 1-dimensional random walk mobility model and random rotating model. We then discuss the impact of various mobility patterns on sensing energy consumption and study the power-delay tradeoff and show that random walk mobility model can decrease the sensing energy consumption under certain delay tolerance. To our knowledge, our work is the very first that derive the critical condition to achieve full view coverage in mobile heterogeneous CSNs. I.
Critical Sensing Range for Camera Sensor Networks
, 2014
"... In camera sensor networks (CSNs), full view coverage, in which any direction of any point in the operational region is covered by at least one camera sensor, is of great sig-nificance since image shot at the frontal viewpoint considerably increases the possibility to recognize the object. However, f ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
(Show Context)
In camera sensor networks (CSNs), full view coverage, in which any direction of any point in the operational region is covered by at least one camera sensor, is of great sig-nificance since image shot at the frontal viewpoint considerably increases the possibility to recognize the object. However, finding the critical condition to achieve full view cov-erage in CSNs remains an open question. In this paper, we analyze both the static and mobile random deployed camera sensor networks. A centralized parameter – equivalent sensing radius (ESR) – is defined to evaluate the critical requirement for asymptotic full view coverage in heterogeneous CSNs. We derive ESR for full view coverage under static model, 2-dimensional random walk mobility model, 1-dimensional random walk mobility model and random rotating model. We also proof that the critical ESR to achieve almost surely coverage is 1.225 times of the critical ESR to achieve coverage with high probability, and extend the result to homogeneous network. We then discuss the impact of various mobility patterns on sensing energy consumption and study the power-delay tradeo ↵ and show that random walk mobility model can decrease the sensing energy consumption under certain delay tolerance. To our knowledge, our work is the very first that derive the critical condition to achieve full view coverage in mobile heterogeneous CSNs. 1 21
Coverage in Visual Sensor Networks with Pan-Tilt-Zoom Cameras: the MaxFoV Problem
"... Abstract—We consider the problem of target coverage in visual sensor networks with Pan-Tilt-Zoom (PTZ) cameras. The finely controllable movement in PTZ dimensions creates a large number of possible Field-of-View (FoV) settings, making it pro-hibitively expensive to consider them all in coverage algo ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
(Show Context)
Abstract—We consider the problem of target coverage in visual sensor networks with Pan-Tilt-Zoom (PTZ) cameras. The finely controllable movement in PTZ dimensions creates a large number of possible Field-of-View (FoV) settings, making it pro-hibitively expensive to consider them all in coverage algorithms. However, these FoVs are redundant as each group of targets is generally covered by many FoVs. Thus, an important problem is how to identify FoVs that cover all maximal subsets of targets (MaxFoV) efficiently. We show that MaxFoV is an instance of generating all maximal cliques, which is NP-hard in general but polynomial if the number of cliques is polynomial. We construct an optimal algorithm to solve the problem with a worst case complexity of O(n3). Simulation and testbed experiments show that the algorithm drastically reduces the number of FoVs allowing multi-camera coverage to scale without sacrificing coverage quality. I.
SmartPhoto: A Resource-Aware Crowdsourcing Approach for Image Sensing with Smartphones
"... Photos obtained via crowdsourcing can be used in many critical applications. Due to the limitations of communi-cation bandwidth, storage and processing capability, it is a challenge to transfer the huge amount of crowdsourced photos. To address this problem, we propose a framework, called SmartPhoto ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
(Show Context)
Photos obtained via crowdsourcing can be used in many critical applications. Due to the limitations of communi-cation bandwidth, storage and processing capability, it is a challenge to transfer the huge amount of crowdsourced photos. To address this problem, we propose a framework, called SmartPhoto, to quantify the quality (utility) of crowd-sourced photos based on the accessible geographical and geo-metrical information (called metadata) including the smart-phone’s orientation, position and all related parameters of the built-in camera. From the metadata, we can infer where and how the photo is taken, and then only transmit the most useful photos. Three optimization problems regard-ing the tradeoffs between photo utility and resource con-straints, namely the Max-Utility problem, the online Max-Utility problem and the Min-Selection problem, are stud-ied. Efficient algorithms are proposed and their perfor-mance bounds are theoretically proved. We have imple-mented SmartPhoto in a testbed using Android based smart-phones, and proposed techniques to improve the accuracy of the collected metadata by reducing sensor reading errors and solving object occlusion issues. Results based on real implementations and extensive simulations demonstrate the effectiveness of the proposed algorithms.
Maximum Lifetime Suspect Monitoring on the Street with Battery-powered Camera Sensors
- WIRELESS NETWORKS
, 2015
"... A camera sensor network is a sensor net-work of a group of camera sensors and is being deployed for various surveillance and monitoring applications. In this paper, we propose a new surveillance model for camera sensor network, namely half-view model, which requires a camera sensor network to capt ..."
Abstract
- Add to MetaCart
A camera sensor network is a sensor net-work of a group of camera sensors and is being deployed for various surveillance and monitoring applications. In this paper, we propose a new surveillance model for camera sensor network, namely half-view model, which requires a camera sensor network to capture the face image of any object if it moves forward to pass over an area of interest. Based on this new surveillance model, we introduce a new sleep-wakeup scheduling problem in camera sensor network, namely the maximum life-time half-view barrier-coverage (MaxL-HV-BC) prob-lem, whose goal is to find an on-off schedule of battery-operated camera sensors such that the continuous time duration providing half-view barrier-coverage over an area of interest is maximized. We develop a strategy to check if a region is half-view covered by a given set of camera sensors, and use this strategy to design two new heuristic algorithms for MaxL-HV-BC. We also conduct simulations to compare the average performance of the proposed algorithms with a trivial solution as well as the theoretical upper bound.
Energy Efficient Content Based Image Retrieval in Sensor Networks
, 2012
"... The presence of increased memory and computational power in imaging sensor networks attract researchers to exploit image processing algorithms on distributed memory and computational power. In this paper, a typical perimeter is in-vestigated with a number of sensors placed to form an image sensor ne ..."
Abstract
- Add to MetaCart
(Show Context)
The presence of increased memory and computational power in imaging sensor networks attract researchers to exploit image processing algorithms on distributed memory and computational power. In this paper, a typical perimeter is in-vestigated with a number of sensors placed to form an image sensor network for the purpose of content based distri-buted image search. Image search algorithm is used to enable distributed content based image search within each sensor node. The energy model is presented to calculate energy efficiency for various cases of image search and transmission. The simulations are carried out based on consideration of continuous monitoring or event driven activity on the perime-ter. The simulation setups consider distributed image processing on sensor nodes and results show that energy saving is significant if search algorithms are embedded in image sensor nodes and image processing is distributed across sensor nodes. The tradeoff between sensor life time, distributed image search and network deployed cost is also investigated.
