Journal of Sensors

Sensors for Environmental Monitoring


Publishing date
13 May 2016
Status
Published
Submission deadline
25 Dec 2015

Lead Editor

1Cornell University, Ithaca, USA

2University of Oxford, Oxford, UK

3Texas A&M University, College Station, USA

4Taiyuan University of Science and Technology, Shanxi, China


Sensors for Environmental Monitoring

Description

Many potentially harmful chemicals released by industries and human activities can contaminate our water, soil, or air and further impact the environment and our health. Real-time and in situ monitoring of various contaminants such as pathogens, metals, radioisotopes, volatile organic compounds, crude oil, and agricultural chemicals in low concentration is mandatory in the fields of industrial plants, automotive technologies, health and medicine, air and water quality control, natural soil/land/sea, and so forth. Reliable sensing technologies with high performance are highly desirable to settle these issues. The types of sensors include, but are not limited to, optical sensors, electronic sensors, acoustic wave sensors, chemical sensors, and any new sensing materials based sensors. Sensitivity, selectivity, and limit of detection are several key parameters to evaluate the performance of sensors. We invite investigators to submit original research and review articles that will contribute to the sensors for environmental monitoring. We are particularly interested in articles exploring the current concepts in addressing key requirements for future sensing technology.

Potential topics include, but are not limited to:

  • Design and fabrication of sensor platforms
  • Sensor miniaturization
  • Portable sensors
  • New sensing materials and sensing schemes/mechanisms
  • Theoretical studies in sensing mechanisms and principles
  • Sensor sensitivity, selectivity, response time, and limit of detection
  • Detection of pathogens in water
  • Monitoring pollutant gases
  • Inspection and monitoring of contaminated soil/land/sea
  • Multitarget detection

Articles

  • Special Issue
  • - Volume 2016
  • - Article ID 4108790
  • - Editorial

Sensors for Environmental Monitoring

Liling Fu | Panagiotis Dallas | ... | Kewei Zhang
  • Special Issue
  • - Volume 2016
  • - Article ID 5328130
  • - Research Article

Edge Detection from RGB-D Image Based on Structured Forests

Heng Zhang | Zhenqiang Wen | ... | Gang Xu
  • Special Issue
  • - Volume 2016
  • - Article ID 4287834
  • - Research Article

A Stream Processing System for Multisource Heterogeneous Sensor Data

Liang Hu | Rui Sun | ... | Kuo Zhao
  • Special Issue
  • - Volume 2016
  • - Article ID 5656245
  • - Research Article

Citizen Sensing for Improved Urban Environmental Monitoring

Qijun Jiang | Frank Kresin | ... | Joost Wesseling
  • Special Issue
  • - Volume 2016
  • - Article ID 9358358
  • - Research Article

Deployment of Wireless Sensor Networks for Oilfield Monitoring by Multiobjective Discrete Binary Particle Swarm Optimization

Zhen-Lun Yang | Angus Wu | Hua-Qing Min
  • Special Issue
  • - Volume 2016
  • - Article ID 7073619
  • - Research Article

Identifying and Correcting Step Losses in Single-Ended Fiber-Optic Distributed Temperature Sensing Data

Mark B. Hausner | Scott Kobs
  • Special Issue
  • - Volume 2016
  • - Article ID 1458147
  • - Research Article

An Architecture Offering Mobile Pollution Sensing with High Spatial Resolution

Oscar Alvear | Willian Zamora | ... | Pietro Manzoni
  • Special Issue
  • - Volume 2016
  • - Article ID 6250319
  • - Research Article

Energy Management in Wireless Sensor Networks Based on Naive Bayes, MLP, and SVM Classifications: A Comparative Study

Abdulaziz Y. Barnawi | Ismail M. Keshta
  • Special Issue
  • - Volume 2016
  • - Article ID 8325845
  • - Research Article

Forest Monitoring and Wildland Early Fire Detection by a Hierarchical Wireless Sensor Network

Antonio Molina-Pico | David Cuesta-Frau | ... | Alba Rozas
  • Special Issue
  • - Volume 2016
  • - Article ID 7184980
  • - Research Article

Measuring Gas Concentration and Wind Intensity in a Turbulent Wind Tunnel with a Mobile Robot

Dani Martínez | Javier Moreno | ... | Jordi Palacín
Journal of Sensors
 Journal metrics
See full report
Acceptance rate12%
Submission to final decision129 days
Acceptance to publication27 days
CiteScore2.600
Journal Citation Indicator0.440
Impact Factor1.9
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