Autonomous real-time water quality sensing as an alternative to conventional monitoring to improve the detection of food, energy, and water indicators

Ziqian Dong (), Fang Li (), Babak Beheshti (), Alan Mickelson (), Marta Panero () and Nada Anid ()
Additional contact information
Ziqian Dong: New York Institute of Technology
Fang Li: New York Institute of Technology
Babak Beheshti: New York Institute of Technology
Alan Mickelson: University of Colorado
Marta Panero: New York Institute of Technology
Nada Anid: New York Institute of Technology

Journal of Environmental Studies and Sciences, 2016, vol. 6, issue 1, No 19, 200-207

Abstract: Abstract Advances in sensors and wireless sensor networks (WSNs) are enabling real-time environmental monitoring, which has the potential to provide a plethora of fine-grained data to assist in understanding the symbiosis between food, energy, and water (FEW) systems. This paper presents the advantages of autonomous real-time water quality monitoring systems over conventional systems and proposes cost-effective and feasible approaches to designing a system that autonomously collects environmental data by integrating digital and mechanical devices connected through various communication networks, both wired and wireless. More specifically, the autonomous sensing devices proposed include low-cost water quality sensors implemented on commercial hardware and cell-based biosensors using electric cell-substrate impedance sensing (ECIS), which are capable of detecting water and/or air toxicants in real time. The paper discusses the key design considerations of the underlying WSN communication system supporting autonomous data transmission, including the spatial distribution of sensors, costs, and operation autonomy. Communication among connected devices (e.g., sensors) requires both precision timing and network security against attacks, as well as means to ensure the privacy and integrity of the data being collected and transmitted through the network. Preliminary results demonstrate the importance of precision timing and synchronization by using measured timing information and signal strength to identify man-in-the-middle attacks in fixed wireless networks and to locate the attack source using machine-learning approaches. Data modeling and recovery methods are presented to efficiently analyze and process sensing data to address the missing measurement issue caused by noise and device failure. The system proposed herein can serve as a valuable tool for real-time monitoring of FEW resources and can be broadly applied to efficient management of their sustainability.

Keywords: Water quality sensing; Real-time; Wireless sensor network; Autonomous; Cell-based sensors; Indicators (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s13412-016-0383-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jenvss:v:6:y:2016:i:1:d:10.1007_s13412-016-0383-8

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/13412

DOI: 10.1007/s13412-016-0383-8

Access Statistics for this article

Journal of Environmental Studies and Sciences is currently edited by Walter A. Rosenbaum

More articles in Journal of Environmental Studies and Sciences from Springer, Association of Environmental Studies and Sciences
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().