Wireless visual sensor networks for smart city applications:A relevance-based approach for multiple sinks mobility

Peixoto, João Paulo Just; Costa, Daniel G.

doi:10.1016/j.future.2017.05.027

Cited by 55 publications

(27 citation statements)

References 27 publications

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“…Moreover, they attribute the mule role to vehicles with fixed trajectories and periodic schedule leading to an increased data delivery delay. In this regard, the works presented in previous studies are basically relevant to the research described here as they involve sensors deployed at fixed geographical positions. Lan and Wu, studied the feasibility of using public transport as DMs to collect information about road traffic collected by stationary sensors.…”

Section: Related Workmentioning

confidence: 99%

“…However, data delivery latency is significantly high (in the order of 24 hours) which may not be suitable for short delay applications. In Peixoto and Costa, mobile sinks are used to collect data from sensor cameras. Mobiles sinks move towards relevant sensors according to dynamically computed optimal paths.…”

Section: Related Workmentioning

confidence: 99%

“…One effective, economical, and suitable way to deliver sensor data to the central controller is to exploit mobile elements (MEs) that may be robots or vehicles. In fact, while moving, MEs can download sensors data once they are within their communication range . This approach, well known as data mule (DM) approach, is proved to be effective in energy economy as well as energy consumption balancing, which are considered as the main issues in traditional WSN multi‐hop forwarding strategies.…”

Section: Introductionmentioning

confidence: 99%

“…The DM concept is then extended to a more realistic entity called “oblivious data mules” where taxicabs are used to deliver the data of a smart city to the urban monitoring center. Vehicles are also proposed to act as mobile sinks to collect the data from stationary sensors in smart cities . However, these works employ vehicles to collect data for long trajectories that correspond to vehicles' itinerary.…”

Section: Introductionmentioning

confidence: 99%

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OMS: Opportunistic mules for short latency data collection in smart cities

Chehbour

Doukha

Moussaoui

et al. 2019

Int J Communication

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In smart city scenarios, data collected by sensors are required to be conveyed to central controllers for processing. Thus, efficient data collection mechanisms considering the urban environment characteristics should take place. To that end, the data mules approach is proved to be efficient. However, being applied to urban environment leads to high data delivery latency due to the characteristics of this environment. Motivated by the need to reduce the collection latency of such an approach, we propose to provide each road segment with a data mule to create a process of distributed data collection. Our scheme leverages opportunistic inter-vehicular communications for assigning the mule role to adequate vehicles. The simulation in realistic mobility settings reveals that our scheme can provide more than 80% of the area of interest with data mules in less than 1 minute. In addition, the data collection latency can be reduced from 24 hours to few minutes. VANETs INTRODUCTIONOne goal of Internet of Things (IoT) paradigm is to provide cities with smart services in order to enhance their sustainability. Smart City projects rely on advanced technologies such as wireless sensing and communication technologies to deal with air pollution, poor waste management, traffic congestion, and energy misuse. 1 Wireless sensor networks (WSNs) are core components for data acquisition in smart city applications. Indeed, due to their low cost and small size, sensing devices can be easily deployed at a large variety of locations allowing coupling the physical infrastructure to information and communication technologies. However, the issue of collecting the data from the huge amount of sensors and actuators spread across streets is still considered as the main challenge for smart city realization. In fact, the complexity of the urban environment can cause network fragmentation due to forcefully sparse node deployments or unpredictable dynamics in wireless link availability. 2 Even if cellular communications have been suggested as an alternative solution, it could be very expensive because of the need of a permanent infrastructure to be built to cover all the nodes. Moreover, it is difficult from economic and administrative points of view to equip each sensor device with a SIM card. 3 Furthermore, the energy consumed for the data collection process could be critical and highly dependent on the quality of the required communication.One effective, economical, and suitable way to deliver sensor data to the central controller is to exploit mobile elements (MEs) that may be robots or vehicles. In fact, while moving, MEs can download sensors data once they are within their communication range. [2][3][4][5][6][7][8] This approach, well known as data mule (DM) approach, is proved to be effective in energy Int J Commun Syst. 2020;33:e4207.wileyonlinelibrary.com/journal/dac

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

OMS: Opportunistic mules for short latency data collection in smart cities

Chehbour

Doukha

Moussaoui

et al. 2019

Int J Communication

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“…The wired network was adopted because the popular Zigbee-based wireless sensor network (WSN) is not suitable for underground communication. After all, the Zigbee-based WSN cannot support simultaneous high-quality transmission of various data with its narrow bandwidth [14][15][16][17][18][19][20][21]. To sum up, our wire-based IUT communication and monitoring system consists of three parts: the ground management system, the underground wired network and the underground monitoring system containing multiple MISs.…”

Section: Introductionmentioning

confidence: 99%

A Novel Communication and Monitoring System for Integrated Utility Tunnel

Han¹,

Shao²,

Wang³

et al. 2019

I2M

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This paper attempts to develop a highly reliable security monitoring system for integrated utility tunnel (IUT). For this purpose, a minimum integrated system (MIS) with multiple sensors was designed to acquire the main parameters in the IUT, including air composition, temperature, pipeline pressure, humidity, and shot video/image of the IUT. Then, each MIS was connected to the software system on the ground via a wired network, forming a wire-based IUT communication and monitoring system. Next, three subsystems were designed on Java, including pipeline operation monitoring subsystem, internal environment monitoring subsystem and security monitoring subsystem. The test results show that the data measured by our method agree well with the actual data in the IUT, indicating that the proposed system can effectively monitor various parameters in the IUT. The research findings lay the basis for intelligent monitoring in smart cities, and mark the future trend of IUT management in Chinese cities.

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Visual node module: An open‐source extension to the ns‐3 network simulator

Mosaif

Rakrak

2020

Int J Communication

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SummaryA wireless visual sensor network is a collective network of directional and battery‐operated sensor nodes equipped with cameras. The field of view of these nodes depends on the camera opening angle, its direction, and its depth of view. Therefore, coverage and object detection in this type of networks are more challenging compared with the traditional wireless sensor networks. Thus, many researchers propose algorithms and solutions in this field that need tests and simulations. In this paper, we focus on network simulator 3 (ns‐3), which is an open‐source and discrete‐event tool suitable for wireless network simulation targeted primarily for research and educational use. The lack of models that can simulate visual sensor nodes in this simulator motivated us to design and develop a new visual node module as an extension of the ns‐3 core libraries and also to adapt the NetAnim tool to present these nodes graphically. This module will help researchers to simulate, test, and visualize their solutions in wireless visual sensor networks field. In this paper, we present the design and implementation of the proposed module. Furthermore, we show how it can be used in ns‐3 to simulate different scenarios of object detection and visualize the results in NetAnim tool.

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Wireless visual sensor networks for smart city applications:A relevance-based approach for multiple sinks mobility

Cited by 55 publications

References 27 publications

OMS: Opportunistic mules for short latency data collection in smart cities

OMS: Opportunistic mules for short latency data collection in smart cities

A Novel Communication and Monitoring System for Integrated Utility Tunnel

Visual node module: An open‐source extension to the ns‐3 network simulator

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