Real-Time Air Pollution Monitoring Systems Using Wireless Sensor Networks Connected in a Cloud-Computing, Wrapped up Web Services

Guanochanga, Byron; Cachipuendo, Rolando; Fuertes, Walter; Salvador, Santiago; Benítez, Diego S.; Toulkeridis, Theofilos; Torres, Jenny; Villacís, César; Tapia, Freddy; Meneses, Fausto

doi:10.1007/978-3-030-02686-8_14

Cited by 23 publications

(13 citation statements)

References 36 publications

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“…In Wang et al, the paper engages the private cloud in the process of the streaming data analytics for fault detection and tracking of the large‐scale information gathered by continuous monitoring using the WSN for the IoT. In Guanochanga et al, the secure low‐cost pollution monitoring of the air is implemented using the three‐layer architecture that consists of raspberry pie, Arduino, and the MQTTP for the processing of the data and transmitting, respectively. Wang et al proffer a fog‐based hierarchical structure that employs the WSN in monitoring and performing the data analytics in the fog layer, preventing the energy consumption and detection of the malicious nodes and recovering the misjudged nodes within an acceptable delay.…”

Section: Related Workmentioning

confidence: 99%

“…The big data gathered based on the tangible environmental changes from the industries or any other application needs an alternative with the substantial storage and the processing capabilities. So, the WSNs in most of the large‐scale application prefer the on‐demand cloud infrastructures that help in the storing, computing, and conveying of the information, eg, in health‐care service, in intelligent road transportation, in water quality monitoring, in the industries of hydraulic fracturing, agriculture, real‐time continuous monitoring of humidity, air pressure, pollution, temperature, natural, and manmade disasters, the WSNs concentrate only on the monitoring and conveys the content gathered to the cloud infrastructure service providers. The cloud service providers who enable a rented service on the software, platform, and the infrastructure are capable of storing an enormous amount of information by the transparent and the ubiquitous sharing of the infrastructure .…”

Section: Introductionmentioning

confidence: 99%

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Performance analysis of wireless sensor networks assisted by on‐demand‐based cloud infrastructure

Umamaheswari¹

2020

Int J Communication

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The wireless sensor networks composed of tiny sensor with the capability of monitoring the tangible changes for a wide range of applications are limited with the capabilities on processing and storage. Their limited capabilities make them seek the help of the cloud that provides the rented service of processing and storage.The dense deployment of the wireless sensor and their vulnerability to the unknown attacks, alterations make them incur difficulties in the process of the conveyance causing the modifications or the loss of the content. So, the paper proposes an optimized localization of the nodes along with the identification of the trusted nodes and minimum distance path to the cloud, allowing the target to have anytime and anywhere access of the content. The performance of the cloud infrastructure-supported wireless sensor network is analyzed using the network simulator 2 on the terms of the forwarding latency, packet loss rate, route failure, storage, reliability, and the network longevity to ensure the capacities of the cloud infrastructure-supported wireless sensor networks. K E Y W O R D Scloud, infrastructure as service, localization of nodes, performance enhancements, trusted nodes, wireless sensor networks

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance analysis of wireless sensor networks assisted by on‐demand‐based cloud infrastructure

Umamaheswari¹

2020

Int J Communication

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“…Now advances in communication and sensor technologies enable the arrangement of dense grids of wireless distributed air monitoring nodes for monitoring pollution. An emerging safety application is cooperative collision avoidance using vehicle to vehicle wireless communication protocols . From different sources, the data that are related to traffic are collected such as vehicles in roads, traffic lights, roadside sensors, and web sources.…”

Section: Introductionmentioning

confidence: 99%

EPO: An Optimization technique for Urban Traffic Management While Limiting the Pollution using WSN

Shrivastava

2020

Int J Communication

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Summary In the world, the vehicular traffic is endlessly expanding all over the place and at the point of intersection can cause terrible traffic congestion. Today, the vast majority of the traffic lights is fixed green light system; therefore, it is resolved without considering the incidence of vehicles emergency. The vehicles of emergency like fire trucks and ambulances are need to reach their destinations at the time. Many people face danger situation when they spent lot of time in traffic. To resolve the above mentioned problem, this paper proposed an optimization technique (Emperor Penguin Optimizer) for urban traffic organisation while limiting the pollution using wireless sensor network. At first, the basic parameters are explained like headway, throughput, density, flow, volume, and waiting time. After that, find the traffic pollutions and calculate the emergency vehicle based on the priority. Lastly, based on the above conditions, the traffic light will be displayed. The proposed work will be evaluated by using MATLAB in terms of latency (32 s), buffer (30 KB/s/vehicle), packet delivery ratio (99%), delay (0.7 s), overhead (20%), packet loss ratio (1%), throughput (99%), and time. Proposed work can also be compared with other recent techniques for the research evaluation.

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“…The big data gathered based on the tangible environmental changes from the industries or any other application needs an alternative with the substantial storage and the processing capabilities. So, the WSNs in most of the large-scale application prefer the on-demand cloud infrastructures that help in the storing, computing, and conveying of the information, eg, in health-care service, 4 in intelligent road transportation, 5 in water quality monitoring, 1 in the industries of hydraulic fracturing, 6 agriculture, 7 real-time continuous monitoring 8 of humidity, air pressure, pollution, temperature, natural, and manmade disasters, the WSNs concentrate only on the monitoring and conveys the content gathered to the cloud infrastructure service providers. The cloud service providers who enable a rented service on the software, platform, and the infrastructure are capable of storing an enormous amount of information by the transparent and the ubiquitous sharing of the infrastructure.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of wireless sensor networks assisted by on-demand-based cloud infrastructure

Umamaheswari¹

2020

Preprint

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The wireless sensor networks composed of tiny sensor with the capability of mon- itoring the tangible changes for a wide range of applications are limited with the capabilities on processing and storage. Their limited capabilities make them seek the help of the cloud that provides the rented service of processing and storage. The dense deployment of the wireless sensor and their vulnerability to the unknown attacks, alterations make them incur difficulties in the process of the conveyance causing the modifications or the loss of the content. So, the paper proposes an optimized localization of the nodes along with the identification of the trusted nodes and minimum distance path to the cloud, allowing the target to have anytime and anywhere access of the content. The performance of the cloud infrastructure-supported wireless sensor network is analyzed using the network simulator 2 on the terms of the forwarding latency, packet loss rate, route failure, storage, reliability, and the network longevity to ensure the capacities of the cloud infrastructure-supported wireless sensor networks.

show abstract

Real-Time Air Pollution Monitoring Systems Using Wireless Sensor Networks Connected in a Cloud-Computing, Wrapped up Web Services

Cited by 23 publications

References 36 publications

Performance analysis of wireless sensor networks assisted by on‐demand‐based cloud infrastructure

Performance analysis of wireless sensor networks assisted by on‐demand‐based cloud infrastructure

EPO: An Optimization technique for Urban Traffic Management While Limiting the Pollution using WSN

Performance analysis of wireless sensor networks assisted by on-demand-based cloud infrastructure

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