Deploying a LEACH Data Aggregation Technique for Air Quality Monitoring in Wireless Sensor Network

Abdulsalam, Hanady M.; Ali, Bader; Alyatama, Anwar; AlRoumi, Eman S.

doi:10.1016/j.procs.2014.07.055

Cited by 15 publications

(6 citation statements)

References 7 publications

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“…Air pollution monitoring is another field where WSNs are employed; the meteorological conditions, such as wind speed and atmospheric turbulence, affect air quality as reported in [ 30 ] where a WSN was designed, with an effective energy-saving system for each sensor node, for air and environment pollution detection. In this context, in [ 31 ] the authors propose a low-cost WSN for air monitoring applications; the sensor node is based on commercial gas sensors and a low power ZigBee (zonal intercommunication global-standard bee) module, which shares the acquired information with the cloud by means of a gateway.…”

Section: Scientific Work and Commercial Devices For Precision Farmentioning

confidence: 99%

Development of Sensors-Based Agri-Food Traceability System Remotely Managed by a Software Platform for Optimized Farm Management

Visconti

Fazio

Velázquez

et al. 2020

Sensors

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The huge spreading of Internet of things (IoT)-oriented modern technologies is revolutionizing all fields of human activities, leading several benefits and allowing to strongly optimize classic productive processes. The agriculture field is also affected by these technological advances, resulting in better water and fertilizers’ usage and so huge improvements of both quality and yield of the crops. In this manuscript, the development of an IoT-based smart traceability and farm management system is described, which calibrates the irrigations and fertigation operations as a function of crop typology, growth phase, soil and environment parameters and weather information; a suitable software architecture was developed to support the system decision-making process, also based on data collected on-field by a properly designed solar-powered wireless sensor network (WSN). The WSN nodes were realized by using the ESP8266 NodeMCU module exploiting its microcontroller functionalities and Wi-Fi connectivity. Thanks to a properly sized solar power supply system and an optimized scheduling scheme, a long node autonomy was guaranteed, as experimentally verified by its power consumption measures, thus reducing WSN maintenance. In addition, a literature analysis on the most used wireless technologies for agri-food products’ traceability is reported, together with the design and testing of a Bluetooth low energy (BLE) low-cost sensor tag to be applied into the containers of agri-food products, just collected from the fields or already processed, to monitor the main parameters indicative of any failure or spoiling over time along the supply chain. A mobile application was developed for monitoring the tracking information and storing conditions of the agri-food products. Test results in real-operative scenarios demonstrate the proper operation of the BLE smart tag prototype and tracking system.

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Section: Scientific Work and Commercial Devices For Precision Farmentioning

confidence: 99%

Development of Sensors-Based Agri-Food Traceability System Remotely Managed by a Software Platform for Optimized Farm Management

Visconti

Fazio

Velázquez

et al. 2020

Sensors

View full text Add to dashboard Cite

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“…Environmental monitoring has been undertaken in many countries, mainly focusing on air quality monitoring [5][6][7][8][9][10][11][12][13][14], water or soil environmental quality monitoring [15][16][17][18][19][20], and marine environmental quality monitoring [21][22][23][24][25][26]. The literature [4][5][6][7][8] established air pollution monitoring networks respectively covering whole monitoring areas by means of the genetic algorithm (SGA), mixed multiple criteria decision-making (MCDM) theory, geographic information system (GIS), analytic network Process(ANP), and the ordered weighted averaging (OWA) method, and verified the validity of the air pollution monitoring network.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The literature [4][5][6][7][8] established air pollution monitoring networks respectively covering whole monitoring areas by means of the genetic algorithm (SGA), mixed multiple criteria decision-making (MCDM) theory, geographic information system (GIS), analytic network Process(ANP), and the ordered weighted averaging (OWA) method, and verified the validity of the air pollution monitoring network. The literature [9][10][11][12][13][14] conducted monitoring and evaluation on-site data by studying low-cost and high-efficiency air quality sensors, and proposed a better selection of sensor location and configuration to improve its accuracy. The literature [15][16][17][18][19][20] proposed key contents, main monitoring facilities, and monitoring indicators of water or soil resources maintenance monitoring based on the regional natural environment and social and economic characteristics by using methods such as the neural network and genetic algorithm, ArcGIS and clustering analysis, the analytic hierarchy process, and the proximity method.…”

Section: Literature Reviewmentioning

confidence: 99%

Layout Planning of Highway Transportation Environment Monitoring Network: The Case of Xinjiang, China

et al. 2019

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Environmental monitoring is an important tool for environmental protection supervision and management. Environmental monitoring can help us effectively understand and master the degree of environmental pollution, and provide data support for putting forward environmental protection measures. Scientific layout and reasonable level of environmental monitoring network design is an essential cornerstone for environmental monitoring, and a significant measure to promote the industry and green sustainable development. This paper systematically analyzed its requirements of monitoring stations in the highway traffic environment monitoring network. First of all, the paper analyzed the influencing factors of regional monitoring stations in the Xinjiang transportation environment monitoring network by referring to the idea of planning the distribution points of the national transportation environment monitoring network, and determines the weight of them by using the analytic hierarchy process (AHP), which lays a foundation for the subsequent selection and determination of environmental monitoring stations. Secondly, the advantage order of ecological monitoring objects’ importance degree was synthetically sorted by the fuzzy comprehensive evaluation method. Finally, the ranking results of the environmental monitoring objects were integrated to determine the number of traffic environmental monitoring stations that need to be built, and the layout of the highway traffic environment monitoring network in Xinjiang was proposed.

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“…Manu people can schedule their activities according to the environmental quality of some particular regions since it is harmful to take part in activities in the region with poor environmental quality. There are lots of studies about how to complete the data acquisition task, and most of those works use traditional wireless sensor network (WSN) [31,32,33,34,35,36,37,38,39] or vehicle sensor network (VSN) [40,41,42,43]. Wireless sensor network collects the information and transmits the data to the server through wireless transmission by deploying some wireless sensors in critical region.…”

Section: Introductionmentioning

confidence: 99%

Maximizing Coverage Quality with Budget Constrained in Mobile Crowd-Sensing Network for Environmental Monitoring Applications

Chen

Yang

2019

Sensors

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The Mobile Crowd-sensing Network is a novel cyber–physical–social network which has received great attention recently and can be used as a powerful tool to monitor the phenomenon of the field of interest. Due to the limited budget, how to choose appropriate participants to maximize the coverage quality is one of the most important issues when the mobile crowd-sensing network applies to practical application, such as air quality monitoring. In this paper, given the number of available participants, the traverse path and the reward of each participant, we investigate the problem of how to choose suitable participants to monitor an environment of a critical region by a crowd-sensing network, while the total rewards for all selected participants is not larger than the limited budget. In our solution, we first divide a big critical region such as a city into smaller regions of different size, and select some sampling points in the smaller region; the collected data of those sampling points represents the collected data of the whole smaller region. Then, we design a greedy algorithm to select participants to cover the maximum sampling points while the total rewards of selected participants does not exceed the limited budget. Finally, we evaluate the validity and efficiency of the proposed algorithm by conducting extensive simulations. The simulation results show that the greedy algorithm outperforms an existing scheme.

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Deploying a LEACH Data Aggregation Technique for Air Quality Monitoring in Wireless Sensor Network

Cited by 15 publications

References 7 publications

Development of Sensors-Based Agri-Food Traceability System Remotely Managed by a Software Platform for Optimized Farm Management

Development of Sensors-Based Agri-Food Traceability System Remotely Managed by a Software Platform for Optimized Farm Management

Layout Planning of Highway Transportation Environment Monitoring Network: The Case of Xinjiang, China

Maximizing Coverage Quality with Budget Constrained in Mobile Crowd-Sensing Network for Environmental Monitoring Applications

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