Optimal Deployment of Wireless Sensor Networks for Air Pollution Monitoring

Boubrima, Ahmed; Matigot, Frederic; Bechkit, Walid; Rivano, Hervé; Ruas, Anne

doi:10.1109/icccn.2015.7288443

Cited by 28 publications

(20 citation statements)

References 13 publications

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“…Additionally, smart appliances for home automation systems [42] are now being researched [43]. IoT-based use cases for smart cities have been also identified, like traffic monitoring [44], surveillance [45] and pollution monitoring [46]. Within this scenario, the content of the samples acquired may expose critical information.…”

Section: Compelling Cots Iot Applicationsmentioning

confidence: 99%

A Review on Internet of Things for Defense and Public Safety

Fraga‐Lamas

Fernández‐Caramés

Suárez-Albela

et al. 2016

Sensors

184

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The Internet of Things (IoT) is undeniably transforming the way that organizations communicate and organize everyday businesses and industrial procedures. Its adoption has proven well suited for sectors that manage a large number of assets and coordinate complex and distributed processes. This survey analyzes the great potential for applying IoT technologies (i.e., data-driven applications or embedded automation and intelligent adaptive systems) to revolutionize modern warfare and provide benefits similar to those in industry. It identifies scenarios where Defense and Public Safety (PS) could leverage better commercial IoT capabilities to deliver greater survivability to the warfighter or first responders, while reducing costs and increasing operation efficiency and effectiveness. This article reviews the main tactical requirements and the architecture, examining gaps and shortcomings in existing IoT systems across the military field and mission-critical scenarios. The review characterizes the open challenges for a broad deployment and presents a research roadmap for enabling an affordable IoT for defense and PS.

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Section: Compelling Cots Iot Applicationsmentioning

confidence: 99%

A Review on Internet of Things for Defense and Public Safety

Fraga‐Lamas

Fernández‐Caramés

Suárez-Albela

et al. 2016

Sensors

184

View full text Add to dashboard Cite

show abstract

“…Finally, the sustainable development of smart cities is expected to handle large amounts of data generated from large number of sensors with the consequent necessity for quick aggregation of the data, which could be exploited to detect correlated events. Among possible applications, smart building management systems rely on service-oriented continuous queries over sensor data streams in case of energy consumption monitoring [7], air pollution monitoring applications heavily rely on sensors to detect threshold crossings [8]. More generally, Stankovic [9] argues that the real time analysis of large and distributed data streams is of utmost importance to tackle issues related to creative knowledge, robustness, privacy, and security.…”

Section: Introductionmentioning

confidence: 99%

Lightweight Metric Computation for Distributed Massive Data Streams

Anceaume

Busnel

2017

Transactions on Large-Scale Data- And Knowledge-Centered Systems XXXIII

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International audienceThe real time analysis of massive data streams is of utmost importance in data intensive applications that need to detect as fast as possible and as efficiently as possible (in terms of computation and memory space) any correlation between its inputs or any deviance from some expected nominal behavior. The IoT infrastructure can be used for monitoring any events or changes in structural conditions that can compromise safety and increase risk. It is thus a recurrent and crucial issue to determine whether huge data streams, received at monitored devices , are correlated or not as it may reveal the presence of attacks. We propose a metric, called codeviation, that allows to evaluate the correlation between distributed massive streams. This metric is inspired from classical metric in statistics and probability theory, and as such enables to understand how observed quantities change together, and in which proportion. We then propose to estimate the codeviation in the data stream model. In this model, functions are estimated on a huge sequence of data items, in an online fashion, and with a very small amount of memory with respect to both the size of the input stream and the values domain from which data items are drawn. We then generalize our approach by presenting a new metric, the Sketch-metric, which allows us to define a distance between updatable summaries of large data streams. An important feature of the Sketch-metric is that, given a measure on the entire initial data streams, the Sketch-metric preserves the axioms of the latter measure on the sketch. We finally present results obtained during extensive experiments conducted on both synthetic traces and real data sets allowing us to validate the robustness and accuracy of our metrics

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“…We compare the two models in terms of execution time and show that the second ow based formulation is much better. [9] …”

Section: Optimal Deployment Of Wireless Sensor Network For Air Pomentioning

confidence: 99%

IOT-Enabled Air Pollution Meter with Digital Dashboard on Smart-Phone for Vehicles

Taskar¹

2017

IJRASET

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Air pollution is one of the main environmental issues nowadays. Airpollution is a most serious problem of the current time all over the world especially in the large cities because of industrialization and huge number of vehicles. The release of gaseous pollutants from burning fuel of motor vehicles is one major reason of air pollution. Vehicles release harmful gaseous like Carbon Monoxide (CO), Carbon Dioxide (CO2) which accounts for 50% of the total atmospheric pollutants. This project focuses on the monitoring and controlling the air pollution generated by vehicles. It is an real-time embedded system in which, a device will be attached to Silencer of vehicle. When pollution generated by vehicles goes beyond the threshold value, sensors will detect and then device will give intimation to the owner of vehicle through android app. If owner doesn't repair his/her vehicle and vehicle again generates pollution above threshold, then second intimation will be given to owner. And if the same repeats for third time, then device will lock the vehicle after 10 kilometers and send the details of the vehicles to RTO.

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Optimal Deployment of Wireless Sensor Networks for Air Pollution Monitoring

Cited by 28 publications

References 13 publications

A Review on Internet of Things for Defense and Public Safety

A Review on Internet of Things for Defense and Public Safety

Lightweight Metric Computation for Distributed Massive Data Streams

IOT-Enabled Air Pollution Meter with Digital Dashboard on Smart-Phone for Vehicles

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