Application and Modeling of a Magnetic WSN for Target Localization

Baghaee, Sajjad; Gürbüz, Sevgi Zübeyde; Uysal-Biyikoğlu, Elif

doi:10.1109/uksim.2013.54

Cited by 12 publications

(5 citation statements)

References 18 publications

(19 reference statements)

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“…In Fig. 10, shows the number of published articles that are energy efficient, cluster-based network has the highest number of papers that are energy efficient [117], [121], [122], [56], [87], [106] followed by the tree-based networks [123], [124]. The methods are energy efficient only in situations where the target speed is constant.…”

Section: Fig 9 Object Recoverymentioning

confidence: 99%

Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions

Adam

Anisi

Ali

2020

Future Generation Computer Systems

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The development of pervasive communication devices and the emergence of the Internet of Things (IoT) have acted as an essential part in the feasibility of smart city initiatives. Wireless sensor network (WSN) as a key enabling technology in IoT offers the potential for cities to get smatter. WSNs gained tremendous attention during the recent years because of their rising number of applications that enables remote monitoring and tracking in smart cities. One of the most exciting applications of WSNs in smart cities is detection, monitoring, and tracking which is referred to as object tracking sensor networks (OTSN). The adaptation of OTSN into urban cities brought new exciting challenges for reaching the goal of future smart cities. Such challenges focus primarily on problems related to active monitoring and tracking in smart cities. In this paper, we present the essential characteristics of OTSN, monitoring and tracking application used with the content of smart city. Moreover, we discussed the taxonomy of OTSN along with analysis and comparison. Furthermore, research challenges are investigated concerning energy reservation, object detection, object speed, accuracy in tracking, sensor node collaboration, data aggregation and object recovery position estimation. This review can serve as a benchmark for researchers for future development of smart cities in the context of OTSN. Lastly, we provide future research direction. Highlights One of the most interesting applications of wireless sensor networks in smart cities would be detecting and monitoring or tracking of objects based on object tracking sensor networks (OTSN).  The review delineates the advantages as well as the weakness of existing OTSN and conduct a comparative view.  Furthermore, research challenges in OTSNs and existing methods are investigated with a focal point of energy constraints, object detection, object speed, tracking accuracy, sensor node collaboration, data aggregation and object recovery position estimation in WSN and smart cities.  Open research issues that required further improvement are summarized.

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Section: Fig 9 Object Recoverymentioning

confidence: 99%

Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions

Adam

Anisi

Ali

2020

Future Generation Computer Systems

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“…Conserving a node's battery power and voltage as much as possible is important for many sensing applications, as variations in power supply voltage level may directly affect the sensor output [29].…”

Section: Energy Consumption Model and Componentsmentioning

confidence: 99%

Powering-up Wireless Sensor Nodes Utilizing Rechargeable Batteries and an Electromagnetic Vibration Energy Harvesting System

et al. 2014

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This paper presents a wireless sensor node (WSN) system where an electromagnetic (EM) energy harvester is utilized for charging its rechargeable batteries while the system is operational. The capability and the performance of an in-house low-frequency EM energy harvester for charging rechargeable NiMH batteries were experimentally verified in comparison to a regular battery charger. Furthermore, the power consumption of MicaZ motes, used as the WSN, was evaluated in detail for different operation conditions. The battery voltage and current were experimentally monitored during the operation of the MicaZ sensor node equipped with the EM vibration energy harvester. A compact (24.5 cm 3 ) in-house EM energy harvester provides approximately 65 µA charging current to the batteries when excited by 0.4 g acceleration at 7.4 Hz. It has been shown that the current demand of the MicaZ mote can be compensated for by the energy harvester for a specific low-power operation scenario, with more than a 10-fold increase in the battery lifetime. The presented results demonstrate the autonomous operation of the WSN, with the utilization of a vibration-based energy harvester. OPEN ACCESSEnergies 2014, 7 6324

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“…For example, it was observed in [9] that variations in supply voltage can have significant effect on measurements and the consequent estimations of target location on a magnetic WSN.…”

Section: Wsn Nodes and Their Energy Consumptionmentioning

confidence: 99%

“…Since battery voltage level of the MicaZ motes is critical for some applications such as tracking a target on a WSN [9], an experiment was set up in order to analyze the characteristic of an AA battery. MicaZ motes have an accurate internal voltage reference that can be used to measure battery voltage (V batt ).…”

Section: Measurementsmentioning

confidence: 99%

Towards a vibration energy harvesting WSN demonstration testbed

Baghaee

Uluşan

Chamanian

et al. 2013

2013 24th Tyrrhenian International Workshop on Digital Communications - Green ICT (TIWDC)

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This paper presents initial results toward the implementation of a wireless sensor network (WSN) demonstration testbed powered up by vibration energy, as part of the E-CROPS project. The testbed uses MicaZ Motes, supplied by AA batteries. The power drawn by Motes in different modes of operation are measured. Design details of an electromagnetic harvester, and experimental results of charging AA batteries with this harvester at 10 Hz vibration generated in the laboratory, are presented.

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Application and Modeling of a Magnetic WSN for Target Localization

Cited by 12 publications

References 18 publications

Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions

Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions

Powering-up Wireless Sensor Nodes Utilizing Rechargeable Batteries and an Electromagnetic Vibration Energy Harvesting System

Towards a vibration energy harvesting WSN demonstration testbed

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