On accurate and efficient statistical counting in sensor-based surveillance systems

Guo, Shuang; He, Tian; Mokbel, Mohamed F.; Stankovic, J.A.; Abdelzaher, Tarek

doi:10.1016/j.pmcj.2009.07.013

Cited by 12 publications

(14 citation statements)

References 19 publications

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“…Based on the presence of victims, in [38], the search and rescue space is reduced, and in [32,33], a communication backbone is formed using robotics. The work in [26,27] uses robots to search and guide victims, and in [31], the number of civilians in an emergency is assessed. Finally, the following papers, [45][46][47][48][49][50], concentrate on the optimization of search and rescue cost.…”

Section: Characteristics Of Existing Evacuation Systemsmentioning

confidence: 99%

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Future Research on Cyber-Physical Emergency Management Systems

Gelenbe

2013

Future Internet

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Cyber-physical systems that include human beings and vehicles in a built environment, such as a building or a city, together with sensor networks and decision support systems have attracted much attention. In emergencies, which also include mobile searchers and rescuers, the interactions among civilians and the environment become much more diverse, and the complexity of the emergency response also becomes much greater. This paper surveys current research on sensor-assisted evacuation and rescue systems and discusses the related research issues concerning communication protocols for sensor networks, as well as several other important issues, such as the integrated asynchronous control of large-scale emergency response systems, knowledge discovery for rescue and prototyping platforms. Then, we suggest directions for further research.

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Section: Characteristics Of Existing Evacuation Systemsmentioning

confidence: 99%

“…to extract knowledge from sensing data (e.g., counting, discovery, localization and tracking of civilians) [30][31][32][33][34][35][36][37][38]. Moreover, dynamic prediction and forecast of environmental changes should be conducted to avoid unnecessary casualties [20,21,[39][40][41][42][43][44].…”

Section: Introduction and Overall Visionmentioning

confidence: 99%

Future Research on Cyber-Physical Emergency Management Systems

Gelenbe

2013

Future Internet

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“…The amount of partitioning can be controlled to strike the desired tradeoff between optimality and computational complexity. The idea of applying partitioning techniques is also employed by Guo et al [13] who use a statistical approach to count targets in an area while avoiding double-counting. In addition to considering a different problem (maximization of average coverage), the distinctive feature of our work is that we use full information on the partitioning process to compute relatively tight bounds with respect to the optimal solution, even when this is not known.…”

Section: State-of-the-artmentioning

confidence: 99%

“…Given the optimal schedule , we can restrict the computation of the coverage to the two sets and getting and , respectively. Because the subproblems are less constrained, it follows that: (12) The total coverage of can be found by adding together the contributions of the three sets , , and Hence, in view of (12), we can write Considering that and that obviously we obtain (13) The value of can be easily computed once the schedule is known, i.e., after the two individual subproblems have been solved. The situation is different for , since we do not have the global optimal solution.…”

Section: Solving and Bounding The Problemmentioning

confidence: 99%

Scalable Offline Optimization of Industrial Wireless Sensor Networks

Palopoli

Rizano

2011

IEEE Trans. Ind. Inf.

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Abstract-Sensor networks are increasingly used to control and monitor industrial and manufacturing processes. In this paper, we consider the problem of optimizing a cost function for wireless sensor networks of this kind under energy consumption constraints. We focus, in particular, on the problem of coverage optimization through scheduling. Following existing approaches, we use a mixed integer linear program formulation. We show how to use partitioning techniques to decompose the problem into separate subproblems, solved individually, overcoming the exponential complexity typical of integer linear programming, while minimizing the loss in optimality. In addition, we evaluate the achieved degree of optimality by computing relatively tight bounds with respect to the optimal solution. Finally, we employ simple but effective heuristics to further improve our solution. The results show that our procedure is very efficient and scalable, and is able to find solutions that are very close to optimal. These characteristics make our approach a perfect fit for large and fixed deployments of wireless sensors, typical in factory automation and industrial applications. To show the generality of the approach, we apply our methodology to three different models of varying complexity.

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“…Without loss of generality, we use the Poisson distribution as a concrete exemplary distribution for the attacker model [14]. Under the Poisson distribution, objects are uniformly distributed in an area within intensity of λ.…”

Section: Attacker Modelmentioning

confidence: 99%

A Privacy-Preserving Location Monitoring System for Wireless Sensor Networks

Chow

Mokbel

2011

IEEE Trans. on Mobile Comput.

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Abstract-Monitoring personal locations with a potentially untrusted server poses privacy threats to the monitored individuals. To this end, we propose a privacy-preserving location monitoring system for wireless sensor networks. In our system, we design two innetwork location anonymization algorithms, namely, resource-and quality-aware algorithms, that aim to enable the system to provide high quality location monitoring services for system users, while preserving personal location privacy. Both algorithms rely on the well established k-anonymity privacy concept, that is, a person is indistinguishable among k persons, to enable trusted sensor nodes to provide the aggregate location information of monitored persons for our system. Each aggregate location is in a form of a monitored area A along with the number of monitored persons residing in A, where A contains at least k persons. The resource-aware algorithm aims to minimize communication and computational cost, while the quality-aware algorithm aims to maximize the accuracy of the aggregate locations by minimizing their monitored areas. To utilize the aggregate location information to provide location monitoring services, we use a spatial histogram approach that estimates the distribution of the monitored persons based on the gathered aggregate location information. Then the estimated distribution is used to provide location monitoring services through answering range queries. We evaluate our system through simulated experiments. The results show that our system provides high quality location monitoring services for system users and guarantees the location privacy of the monitored persons.

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On accurate and efficient statistical counting in sensor-based surveillance systems

Abstract: Abstract

Cited by 12 publications

References 19 publications

Future Research on Cyber-Physical Emergency Management Systems

Future Research on Cyber-Physical Emergency Management Systems

Scalable Offline Optimization of Industrial Wireless Sensor Networks

A Privacy-Preserving Location Monitoring System for Wireless Sensor Networks

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