IMA: An Integrated Monitoring Architecture With Sensor Networks

Chen, Pengpeng; Zhang, Hao; Jiang, Mingxing; Li, Chunrong

doi:10.1109/tim.2012.2186395

Cited by 30 publications

(8 citation statements)

References 30 publications

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“…Behind every sensor/monitor network there is an underlying data architecture which supports the collection, processing and dissemination of the data (Castell et al, 2015). The complexity and capacity of the sensor/monitor network architectures is proportional to the number of sensors/monitors deployed, the predicted future capacity of the network, the amount of data gathered per sensor, the required level of availability/reliability the backend services require, the post-processing requirements and the data dissemination methods desired (Guo et al, 2012).…”

Section: Data: Communication Storage Cloud Services Processing Anmentioning

confidence: 99%

Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

Morawska

Thai

Liu

et al. 2018

Environment International

600

366

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Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders of magnitude lower than standard/reference instruments, many avenues for applications have opened up. In particular, broader participation in air quality discussion and utilisation of information on air pollution by communities has become possible. However, many questions have been also asked about the actual benefits of these technologies. To address this issue, we conducted a comprehensive literature search including both the scientific and grey literature. We focused upon two questions: (1) Are these technologies fit for the various purposes envisaged? and (2) How far have these technologies and their applications progressed to provide answers and solutions? Regarding the former, we concluded that there is no clear answer to the question, due to a lack of: sensor/monitor manufacturers' quantitative specifications of performance, consensus regarding recommended end-use and associated minimal performance targets of these technologies, and the ability of the prospective users to formulate the requirements for their applications, or conditions of the intended use. Numerous studies have assessed and reported sensor/monitor performance under a range of specific conditions, and in many cases the performance was concluded to be satisfactory. The specific use cases for sensors/monitors included outdoor in a stationary mode, outdoor in a mobile mode, indoor environments and personal monitoring. Under certain conditions of application, project goals, and monitoring environments, some sensors/monitors were fit for a specific purpose. Based on analysis of 17 large projects, which reached applied outcome stage, and typically conducted by consortia of organizations, we observed that a sizable fraction of them (~ 30%) were commercial and/or crowd-funded. This fact by itself signals a paradigm change in air quality monitoring, which previously had been primarily implemented by government organizations. An additional paradigm-shift indicator is the growing use of machine learning or other advanced data processing approaches to improve sensor/monitor agreement with reference monitors. There is still some way to go in enhancing application of the technologies for source apportionment, which is of particular necessity and urgency in developing countries. Also, there has been somewhat less progress in wide-scale monitoring of personal exposures. However, it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure. Traditional personal monitoring would still be valuable where spatial variability of pollutants of interest is at a finer resolution than the monitoring network can resolve.

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Section: Data: Communication Storage Cloud Services Processing Anmentioning

confidence: 99%

Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

Morawska

Thai

Liu

et al. 2018

Environment International

600

366

View full text Add to dashboard Cite

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“…This paper is inspired by one of our ongoing projects, in which 18 nodes are deployed on the sea surface for collecting the received signal strength, light and temperature for several months [20]. After analyzing the experimental results, we find that the closer nodes have more similar received signal strength values.…”

Section: Introductionmentioning

confidence: 93%

SSL: Signal Similarity-Based Localization for Ocean Sensor Networks

Chen

Gao

et al. 2015

Sensors

Self Cite

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Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes’ positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes’ positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes’ relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks.

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“…Our monitoring system carries out the integration within an Arduino ARM controller. This paper presents real-time ZigBee signals sent to smartphones via the Wi-Fi protocol using our integrated digital controller [ 12 ]. Our study presents a controller used to integrate different protocols, therefore, the proposed controller is called integrated controller.…”

Section: Systems Analysis and Descriptionmentioning

confidence: 99%

Mobile Monitoring and Embedded Control System for Factory Environment

Lian

Hsiao

Sung

2013

Sensors

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This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones.

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IMA: An Integrated Monitoring Architecture With Sensor Networks

Cited by 30 publications

References 30 publications

Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

SSL: Signal Similarity-Based Localization for Ocean Sensor Networks

Mobile Monitoring and Embedded Control System for Factory Environment

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