In-situ and remote monitoring of environmental water quality

Environmental water pollution affects human health and reduces the quality of our natural water ecosystems and resources. As a result, there is great interest in monitoring water quality and ensuring that all areas are compliant with legislation. Ubiquitous water quality monitoring places considerable demands upon existing sensing technology. The combined challenges of system longevity, autonomous operation, robustness, large-scale sensor networks, operationally difficult deployments and unpredictable and lossy environments collectively represents a technological barrier that has yet to be overcome[1]. Ubiquitous sensing envisages many aspects of our environment being routinely sensed. This will result in data streams from a large variety of heterogeneous sources, which will often vary in their volume and accuracy. The challenge is to develop a networked sensing infrastructure that can support the effective capture, filtering, aggregation and analysis of such data. This will ultimately enable us to dynamically monitor and track the quality of our environment at multiple locations. Microfluidic technology provides a route to the development of miniaturised analytical instruments that could be deployed remotely, and operate autonomously over relatively long periods of time (months–years). An example of such a system is the autonomous phosphate sensor[2] which has been developed at the CLARITY Centre, in Dublin City University. This technology, in combination with the availability of low power, reliable wireless communications platforms that can link sensors and analytical devices to online databases and servers, form the basis for extensive networks of autonomous analytical ‘stations’ or ‘nodes’ that will provide high quality information about key chemical parameters that determine the quality of our aquatic environment. The system must also have sufficient intelligence to enable adaptive sampling regimes as well as accurate and efficient decision-making responses. A particularly exciting area of development is the combination of remote satellite/aircraft based monitoring with the in-situ ground-based monitoring described above. Remote observations from satellites and aircraft can provide significant amounts of information on the state of the aquatic environment over large areas. As in-situ deployments of sensor networks become more widespread and reliable, and satellite data becomes more widely available, information from each of these sources can complement and validate the other, leading to an increased ability to rapidly detect potentially harmful events, and to assess the impact of environmental pressures on scales ranging from small river catchments to the open ocean. In this paper, we will assess the current status of these approaches, and the challenges that must be met in order to realise the vision of true internet- or global-scale monitoring of our environment. References: [1] Integration of analytical measurements and wireless communications – Current issues and future strategies. King Tong Lau, Sarah Brady, John Cleary and Dermot Diamond, Talanta 75 (2008) 606–612. [2] An autonomous microfluidic sensor for phosphate: on-site analysis of treated wastewater. John Cleary, Conor Slater, Christina McGraw and Dermot Diamond, IEEE Sensors Journal, 8 (2008) 508-515

The impact of the death criterion on the WSN lifetime using EM pollution monitoring algorithm

Wireless sensor networks (WSNs) are one of the most advanced means that are used for monitoring and reporting. The fact that they consist of small, low cost sensor nodes that are continuously used in a variety of applications has made them become a very attractive field in research. One of the main applications of interest in this research is monitoring the electromagnetic (EM) pollution caused by the rapid expansion of electronic and wireless devices. Research has proven that radiations that these devices emit have a huge effect on the human’s health and therefore are worth monitoring. An advanced algorithm was developed in order to monitor these emissions and its main parameters were randomized to give the algorithm a room of flexibility to suit a variety of monitoring scenarios. Although WSNs are used in numerous critical applications, they still face some challenges. Relying on battery-operated sensors causes the network to be resource constrained and therefore, there is a continuous need for prolonging the network lifetime. In this thesis, different death criteria will be applied and their effect on the network lifetime will be investigated. Moreover the impact of changing the number of sensing cycles per network master will be investigated, since the main aim is to exploit the sensor’s energy efficiently. Finally, the selection of network master will be examined, i.e., random vs. planned to evaluate its effect on the previous simulations and more importantly on the network lifetime

Low Power EMC Optimized Wireless Sensor Network for Air Pollution Monitoring System

Air pollution has significant repercussion on the concentrations of constituents in atmosphere leading to consequences like global warming and acid rain. Traditional air polluting monitoring methods are expensive and bulky, to overcome this disadvantage WSN (Wireless Sensor Network) has come into existence which has advantage of being small, easy to setup, inexpensive and provide real time monitoring of data. In this paper, modular wireless sensor architecture for pollution monitoring system that measures the level of carbon monoxide, particulate Matter, nitrogen-di-oxide and sulphur-di-oxide in environment and sends the measured data to server is proposed. The proposed system is designed for extremely low power operation which monitors the pollutants level and sends the data to server via GPRS and can be used in secured places like military and defence. DOI: 10.17762/ijritcc2321-8169.15061

Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

Software Engineering for Mapping Radio Frequency Pollution

Electromagnetic fields radiation has raised concerns within several segments of the population in the past three decades. Many studies proved inconclusive, in part due to the scarcity of data. We propose the idea of a geographical model based radiation pollution database. We discuss networked sensing technology for detection and monitoring of electromagnetic fields. We elaborate on software engineering issues for the visualization in real time of electromagnetic field mappings and the dissemination of information through various means and levels of access. We propose the database be complimented by a data algorithmic software solution for the extraction of patterns