Design of a Water Environment Monitoring System Based on Wireless Sensor Networks

A water environmental monitoring system based on a wireless sensor network is proposed. It consists of three parts: data monitoring nodes, data base station and remote monitoring center. This system is suitable for the complex and large-scale water environment monitoring, such as for reservoirs, lakes, rivers, swamps, and shallow or deep groundwaters. This paper is devoted to the explanation and illustration for our new water environment monitoring system design. The system had successfully accomplished the online auto-monitoring of the water temperature and pH value environment of an artificial lake. The system's measurement capacity ranges from 0 to 80 °C for water temperature, with an accuracy of ±0.5 °C; from 0 to 14 on pH value, with an accuracy of ±0.05 pH units. Sensors applicable to different water quality scenarios should be installed at the nodes to meet the monitoring demands for a variety of water environments and to obtain different parameters. The monitoring system thus promises broad applicability prospects

Wireless Sensor Networks for Oceanographic Monitoring: A Systematic Review

Monitoring of the marine environment has come to be a field of scientific interest in the last ten years. The instruments used in this work have ranged from small-scale sensor networks to complex observation systems. Among small-scale networks, Wireless Sensor Networks (WSNs) are a highly attractive solution in that they are easy to deploy, operate and dismantle and are relatively inexpensive. The aim of this paper is to identify, appraise, select and synthesize all high quality research evidence relevant to the use of WSNs in oceanographic monitoring. The literature is systematically reviewed to offer an overview of the present state of this field of study and identify the principal resources that have been used to implement networks of this kind. Finally, this article details the challenges and difficulties that have to be overcome if these networks are to be successfully deployed

The impact of agricultural activities on water quality: A case for collaborative catchment-scale management using integrated wireless sensor networks

The challenge of improving water quality is a growing global concern, typified by the European Commission Water Framework Directive and the United States Clean Water Act. The main drivers of poor water quality are economics, poor water management, agricultural practices and urban development. This paper reviews the extensive role of non-point sources, in particular the outdated agricultural practices, with respect to nutrient and contaminant contributions. Water quality monitoring (WQM) is currently undertaken through a number of data acquisition methods from grab sampling to satellite based remote sensing of water bodies. Based on the surveyed sampling methods and their numerous limitations, it is proposed that wireless sensor networks (WSNs), despite their own limitations, are still very attractive and effective for real-time spatio-temporal data collection for WQM applications. WSNs have been employed for WQM of surface and ground water and catchments, and have been fundamental in advancing the knowledge of contaminants trends through their high resolution observations. However, these applications have yet to explore the implementation and impact of this technology for management and control decisions, to minimize and prevent individual stakeholder’s contributions, in an autonomous and dynamic manner. Here, the potential of WSN-controlled agricultural activities and different environmental compartments for integrated water quality management is presented and limitations of WSN in agriculture and WQM are identified. Finally, a case for collaborative networks at catchment scale is proposed for enabling cooperation among individually networked activities/stakeholders (farming activities, water bodies) for integrated water quality monitoring, control and management

Antiviral potential of human IFN-α subtypes against influenza A H3N2 infection in human lung explants reveals subtype-specific activities.

Influenza is an acute respiratory infection causing high morbidity and mortality in annual outbreaks worldwide. Antiviral drugs are limited and pose the risk of resistance development, calling for new treatment options. IFN-α subtypes are immune-stimulatory cytokines with strong antiviral activities against IAV in vitro and in vivo. However, the clinical use of IFN-α2, the only licensed subtype of this multi-gene family, could not prevent or limit IAV infections in humans. However, the other subtypes were not investigated.Therefore, this study evaluated the induction and antiviral potential of all human IFN-α subtypes during H3N2 IAV infection in human lung explants. We found that subtypes with weak antiviral activities were preferentially induced during IAV infection in human lungs. Intriguingly, non-induced subtypes α16, α5 and α4 suppressed viral replication up to 230-fold more efficiently than α2. Furthermore, our results demonstrate that subtypes with stronger antiviral activities induce higher expression of IAV-specific restriction factors and that MxA expression is a determinant of the subtype-specific antiviral activity towards H3N2 IAV. These results corroborate that IFN-α subtypes exhibit differential antiviral activities and emphasize that subtypes α16, α5 and α4 should be further investigated for the prevention and treatment of severe infections with seasonal H3N2 IAV