Information-Driven Dynamic Sensor Collaboration for Tracking Applications

By Feng Zhao, Jae-Hyuck Shin, J. Reich. 2002

538 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b6fa565b05ae71bd9a25529eb77d58ab96f582ef

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Citations in the corpus

Data-centric storage in sensornets (2003, background): “[25] describe a collaborative tracking application built on top of directed diffus ion.”
A line in the sand: a wireless sensor network for target detection, classification, and tracking (2004, methodology): “Section 5 considers the phenomenology of the target models in the six energy domains.”
On a stochastic sensor selection algorithm with applications in sensor scheduling and sensor coverage (2006, unknown): “…dealt with robust sensor scheduling (A. Savkin and R. Evans and E. Ska(cid:12)das 2000), a greedy algorithm with an information based cost measure (Zhao et al. 2002), a numerical method for obtaining sub-optimal schedules with error bounds (Alriksson and Rantzer 2005) and include the works of…”
DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks (2004, background): “[6], [23] studied the problem of tracking a mobile target using an information-driven approach.”
Looking ahead in pervasive computing: Challenges and opportunities in the era of cyber-physical convergence (2012, unknown): “For example, [84] considered collaborating sensors in a sensor field for increasing the information utility in an object-tracking”
Information fusion for wireless sensor networks: Methods, models, and classifications (2007, methodology): “An example of complementary fusion consists in fusing data from sensor nodes (e.g., a sample from the sensor .eld) into a feature map that describes the whole sensor .eld [Zhao et al. 2002b; Willett et al. 2004; Nowak et al. 2004; Singh et al. 2006], hence broader information.”
VigilNet: An integrated sensor network system for energy-efficient surveillance (2006, background): “In addition, Zhao [Zhao et al. 2002] propose a optimal sensor selection approach to aggregate the fidelity of detections while eliminating redundant communication.”
Data-Centric Storage in Sensornets with GHT, a Geographic Hash Table (2003, background): “Zhao et al. [30] describe a collaborative tracking application built on top of directed diffusion.”
Optimal Value of Information in Graphical Models (2009, methodology): “Zhao et al. (2002) proposed heuristics for selectively querying nodes in a sensor network in order to reduce the entropy of the prediction.”
On neighbor discovery in wireless networks with directional antennas (2005, background): “Sensor networks have applications such as surveillance and tracking [16], environmental observation [2], habitat monitoring [7], and health monitoring [13], while mesh networks [8] enable nodes to connect home networks together forming a community ad-hoc network.”
Decentralized estimation and control of graph connectivity in mobile sensor networks (2008, background): “In mobile sensor network systems, current research areas include target tracking [14], [22], [11], formation and coverage control [2]–[4], [6], environmental monitoring [10], [16], [18], and several others.”
Sensor Selection via Convex Optimization (2009, background): “The sensor selection problem (and various extensions described in Section V) can be formulated in an information theoretic framework [16]–[19], and in a Bayesian framework [20], [21].”
Sensor networks: evolution, opportunities, and challenges (2003, background): “Zhao et al. [38] addressed the dynamic sensor collaboration problem in distributed tracking to determine dynamically which sensor is most appropriate to perform the sensing, what needs to be sensed, and to whom to communicate the information.”
Tracking a moving object with a binary sensor network (2003, background): “Target tracking is necessary in various domains such as computer vision [7], sensor networks [13], tactical battlefield surveillance, air traffic control, perimeter security and first response to emergencies .”
Distributed algorithms for guiding navigation across a sensor network (2003, methodology): “More specifically, we build on important previous work by [16], [10], [26], [6], [ 27 ] and examine in more detail reactive sensors that can adapt to their environment by capturing a danger level map and distributing this map across the network.”