Dynamic networking and smart sensing enable next-generation landmines

Merrill, William; Cirod, L.; Schiffer, B.; Mclntire, D.; Rava, G.; Sohrabi, K.; Newberg, F.; Elson, Jeremy; Kaiser, W.J.

doi:10.1109/mprv.2004.4

Cited by 15 publications

(15 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Since we currently have only 10 nodes, we have not attempted to address this issue. However, in prior experience with similar algorithms [24], we have been able to scale to larger networks by solving the system incrementally, adding a few nodes at a time.…”

Section: Costs and Convergence Propertiesmentioning

confidence: 99%

The design and implementation of a self-calibrating distributed acoustic sensing platform

Girod

Lukáč

Trifa

et al. 2006

Proceedings of the 4th International Conference on Embedded Networked Sensor Systems

143

108

View full text Add to dashboard Cite

We present the design, implementation, and evaluation of the Acoustic Embedded Networked Sensing Box (ENSBox), a platform for prototyping rapid-deployable distributed acoustic sensing systems, particularly distributed source localization. Each ENSBox integrates an ARM processor running Linux and supports key facilities required for source localization: a sensor array, wireless network services, time synchronization, and precise self-calibration of array position and orientation. The ENSBox's integrated, high precision self-calibration facility sets it apart from other platforms. This self-calibration is precise enough to support acoustic source localization applications in complex, realistic environments: e.g., 5 cm average 2D position error and 1.5 degree average orientation error over a partially obstructed 80x50 m outdoor area. Further, our integration of array orientation into the position estimation algorithm is a novel extension of traditional multilateration techniques. We present the result of several different test deployments, measuring the performance of the system in urban settings, as well as forested, hilly environments with obstructing foliage and 20-30 m distances between neighboring nodes.

show abstract

Section: Costs and Convergence Propertiesmentioning

confidence: 99%

The design and implementation of a self-calibrating distributed acoustic sensing platform

Girod

Lukáč

Trifa

et al. 2006

Proceedings of the 4th International Conference on Embedded Networked Sensor Systems

143

108

View full text Add to dashboard Cite

show abstract

“…In addition to a 32-bit CPU, those nodes include sophisticated peripherals and megabytes of RAM and flash as well as a highbandwidth 802.11 radio. 32-bit nodes are used in standalone wireless sensor network deployments [3], [4], [5] as well as in tiered architectures, where they operate in conjunction with microcontroller-based WSN devices [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

End-to-End Routing for Dual-Radio Sensor Networks

Stathopoulos¹,

Lukáč²,

Mclntire³

et al. 2007

IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications

View full text Add to dashboard Cite

Abstract-Dual-radio, dual-processor nodes are an emerging class of Wireless Sensor Network devices that provide both lowenergy operation as well as substantially increased computational performance and communication bandwidth for applications. In such systems, the secondary radio and processor operates with sufficiently low power that it may remain always vigilant, while the the main processor and primary, high-bandwidth radio remain off until triggered by the application. By exploiting the high energy efficiency of the main processor and primary radio along with proper usage, net operating energy benefits are enabled for applications. The secondary radio provides a constantly available multi-hop network, while paths in the primary network exist only when required. This paper describes a topology control mechanism for establishing an end-to-end path in a network of dual-radio nodes using the secondary radios as a control channel to selectively wake up nodes along the required end-to-end path. Using numerical models as well as testbed experimentation, we show that our proposed mechanism provides significant energy savings of more than 60% compared to alternative approaches, and that it incurs only moderately greater application latency.

show abstract

“…Therefore, many ongoing efforts have focused on developing the offroute mines that could be triggered by means such as sound, magnetism and vibration, so that the mine could detonate even when it is not touched. As far as we know, the work in [1] is the only published effort to achieve this goal by integrating the latest sensor technology [2] into the landmine design (so called smart-mine). In agreement with [1], we believe that the marriage with sensor technology could bring new opportunities and even revolutionize the entire mine industry.…”

mentioning

confidence: 99%

“…As far as we know, the work in [1] is the only published effort to achieve this goal by integrating the latest sensor technology [2] into the landmine design (so called smart-mine). In agreement with [1], we believe that the marriage with sensor technology could bring new opportunities and even revolutionize the entire mine industry. While [1] mainly focuses on the single sensor-enabled mine design, in this paper, we take one step further and investigate the networking opportunities that the sensor technology can bring to the next generation landmine.…”

mentioning

confidence: 99%

Minimizing the Cost of Mine Selection Via Sensor Networks

Liu

2009

Ieee Infocom 2009

View full text Add to dashboard Cite

Abstract-In this paper, we study sensor enabled landmine networks by formulating a minimum-cost mine selection problem. The problem arises in a target defence scenario, where the objective is to destroy the intruding targets using the minimumcost pre-deployed mines. Due to the problem complexity, we first transform it using a novel bucket-tub model, and then propose several approximation algorithms. Among them, it is shown that the layering algorithm can achieve an approximation ratio of α · f , where α ≥ 1 is the tunable relaxation factor and f is the maximum number of mines that a target is associated with, and that the greedy algorithm has an approximation ratio of P j Rj, where Rj is the coefficient in the related integer program. We also present a localized greedy algorithm which is shown to produce the same solution set as the global greedy algorithm. Theoretical analysis and extensive simulations demonstrate the effectiveness of the proposed algorithms.

show abstract

Dynamic networking and smart sensing enable next-generation landmines

Cited by 15 publications

References 6 publications

The design and implementation of a self-calibrating distributed acoustic sensing platform

The design and implementation of a self-calibrating distributed acoustic sensing platform

End-to-End Routing for Dual-Radio Sensor Networks

Minimizing the Cost of Mine Selection Via Sensor Networks

Contact Info

Product

Resources

About