Sensor networks: Evolution, opportunities, and challenges

Chong, Chee-Yee; Kumar, Sudarshan

doi:10.1109/jproc.2003.814918

Cited by 2,294 publications

(169 citation statements)

References 26 publications

(17 reference statements)

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“…These methods are not easy to apply, however, because their communication structures differ from those of the active RFID system [13]. The MAC of the active RFID has a reader central communication structure, wherein the reader…”

Section: Fig 31 Types Of Rfidmentioning

confidence: 99%

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Lifetime Analysis of a Slotted Aloha-Based Wireless Sensor Network Using a Cross-Layer Frame Rate Adaptation Scheme

Devi¹

2015

IJAREEIE

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ABSTRACT:A wireless sensor network consists of a large number of nodes spread over a specific area where we want to look after at the changes going on there. A sensor node generally consists of sensors, actuators, memory, a processor and they do have communication ability. All the sensor nodes are allowed to communicate through a wireless medium. The wireless medium may either of radio frequencies, infrared or any other medium, of course, having no wired connection. Many techniques are proposed for energy saving, Clustering is one of them. In this technique, the clusters are formed by clustering of the grouping nodes. The cluster heads are elected periodically such that members of a cluster can communicate with their cluster heads. These cluster heads send data received from its members to a base station. The multi clustering can also be used. RFID is used in it. The cluster head should have to be rotated for the balancing of energy and then there will be equal load on every node.A master node is deployed within sensor network that is synchronized with GPS. Master node gives the timing information to all sensor nodes so they all are synchronized to each other.

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Section: Fig 31 Types Of Rfidmentioning

confidence: 99%

“…they are out of coverage area of each other, the data can be send to the other node by using the nodes in between them. This property is referred as multi-hoping [13].…”

Section: Iintroductionmentioning

confidence: 99%

Lifetime Analysis of a Slotted Aloha-Based Wireless Sensor Network Using a Cross-Layer Frame Rate Adaptation Scheme

Devi¹

2015

IJAREEIE

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“…Strategic seed programs begun in the 1990s, such as DARPA's SENSIT initiative [8], have grown into an international research movement.…”

Section: Related Workmentioning

confidence: 99%

Parasitic Mobility for Pervasive Sensor Networks

Laibowitz¹,

Paradiso²

2005

Lecture Notes in Computer Science

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Abstract. Distributed sensor networks offer many new capabilities for contextually monitoring environments. By making such systems mobile, we increase the application-space for the distributed network mainly by providing dynamic context-dependent deployment, continual relocatability, automatic node recovery, and a larger area of coverage. In existing models, the addition of actuation to the nodes has exacerbated three of the main problems with distributed systems: power usage, node size, and node complexity. In this paper we propose a solution to these problems in the form of parasitically actuated nodes that harvest their mobility and local navigational intelligence by selectively engaging and disengaging from mobile hosts in their environment. We analyze the performance of parasitically mobile distributed networks through software simulations and design, implement, and demonstrate hardware prototypes.

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“…[1,2]. Military or civilian surveillance systems are designed to provide better situational awareness to the operators and decision makers.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Situational Awareness and Security Assessment in Surveillance Systems Using Cloud Model Theory

Khoshnaw¹,

Al-Dalowi²,

QasMarrogy³

2017

Cihan Univ.-Erbil Sci. J.

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Cloud Model Theory is a mathematical method to model the two components of uncertainty, Randomness and Fuzziness in linguistic concepts. This paper introduces a method to assess information, make and fuse decisions in multi-layered sensing systems using the cloud model to process uncertainty. In this research, Cloud model theory is used to model information extracted from digital images taken for the purpose of monitoring and surveillance in multi-layered sensing systems. The extracted information is assessed using the cloud models to make decisions about the level of security situations in the area under surveillance. The threat level of any security situation can be considered as concepts and can be modeled using cloud models to produce assessments; these assessments are then fused to make a decision about the level of the security threat. Cloud models provided a robust methodology to make decisions and evaluate security situations which led to enhanced situation awareness. Test results showed that cloud models performed much better in comparison with just using standard fuzzy logic models.

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Sensor networks: Evolution, opportunities, and challenges

Cited by 2,294 publications

References 26 publications

Lifetime Analysis of a Slotted Aloha-Based Wireless Sensor Network Using a Cross-Layer Frame Rate Adaptation Scheme

Lifetime Analysis of a Slotted Aloha-Based Wireless Sensor Network Using a Cross-Layer Frame Rate Adaptation Scheme

Parasitic Mobility for Pervasive Sensor Networks

Enhanced Situational Awareness and Security Assessment in Surveillance Systems Using Cloud Model Theory

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