Towards Dependable Measurements in Coastal Sensors Networks Gonçalo Jesus1, António Casimiro2, and Anabela Oliveira1 1
LNEC – National Laboratory for Civil Engineering, Lisbon, Portugal {gjesus,aoliveira}@lnec.pt 2 FCUL – Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal
[email protected]
Abstract. A flood monitoring system incorporates water sensor networks, forecast simulations models, and a decision-support web-based system. The objective of the system is to achieve reliable flood protection and response. This is challenging because of the inherent presence of a cascade of uncertainties in the forecast models, and also uncertainties affecting the timeliness and quality of raw sensor data that is used in the forecasting processes. Achieving real-time and accurate data collection is difficult due to the pervasive nature of the monitoring networks and because sensors and sensor nodes are vulnerable to external disturbances affecting data accuracy. In this paper we motivate for the need of dependable data collection in harsh coastal and marine environments, we overview the main challenges that need to be addressed and we introduce some initial ideas on what needs to be done in order to deal with external disturbances causing faulty measurements. Keywords: Marine sensors, reliable measurements, dependable sensors, failure detection.
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Introduction
Preventive strategies against natural and man-made disasters are currently being improved and their effectiveness will lessen the impact of the hazards. Thus, the availability of reliable systems delivering reliable information from reliable sources is vital for the protection of human lives as well as material and natural assets. In flood managing those systems need to issue alerts or to support decisions on mitigation measures to be performed in areas at risk, with the help of reliable forecasts and dependable real-time monitored data, such as water level, flow or precipitation level. The systems which integrate monitoring networks, large-scale distributed computation (using shared heterogeneous pooled resources across administrative domains) either for forecasting/simulations or data analysis, and a web-based system to support posterior on-time decisions, are addressed as pervasive management support (PMS) systems [1], used mainly to manage environmental threats. Although PMS systems are complex, the constrained time frame of a response is desirably short, for successful protection of people and assets. When it exceeds the M. Vieira and J.C. Cunha (Eds.): EWDC 2013, LNCS 7869, pp. 190–193, 2013. © Springer-Verlag Berlin Heidelberg 2013
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target response time, warnings are useless and might carry significant financial penalties and loss of human lives, so both hardware and software failures are not tolerable at critical moments in any of the tiers.
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Real-Time Environment Monitoring
Water bodies monitoring for early flood detection and enhanced response has become a vital infrastructure system in order to provide accurate, reliable and timely information to assist local authorities and experts in responding flood events. The availability, coupled with reliability, of the near real-time monitoring information is a difficult requirement in effective implementations of monitoring networks. So, in the last years, many studies on wireless sensor networks have been performed, in order to cover the usually large monitoring area [2] and to fulfill the requirements. The quality of flood forecasting also depends on the quality of measurements, or on the forecasts of precipitation and other forcings. The better the estimation of the input of water during an event, the better is the chance of producing accurate forecasts. The most common problems in measuring networks are the accuracy of the sensor measurements, the possibility of the equipment getting damaged in environment-related events (leading to data unavailability or data corruption) and the occupancy of the area to be monitored (with influence on the probability that some hazard will happen). Thus some calibration of the effective values of the monitored parameters is generally necessary. Nowadays the use of real-time sensors in flood monitoring is an important nonstructural measure of flood control. One of the most used infrastructures to build the monitoring network of a PMS system is a wireless sensor network [2-4], where the monitoring system can be decomposed into a set of remote wireless communication systems, which log water condition data, and transfer the data to a web-based information center to build a real-time web-based management system. These wireless remote sensors are scattered in the field and separated from each other by a large distance.
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Coastal Sensors Network Challenges
The increasing level of heterogeneity is a relevant issue in modern distributed systems. Generic instruments or applications that were built or studied to be adaptive, autonomic, dependable, secure and scalable, and tested on controlled situations, now need to operate in increasingly-varied environments, such as a pervasive and complex marine environment, combined with different types of sensors measuring several parameters (many interconnected). In the design of context-aware monitoring networks, the first thought is that there should be a deep understanding of application requirements in order to develop software and hardware that automatically adapts to aspects of the environment, such as sensor’s current location and activity, the time of day, and the presence of other factors in the vicinities [5].
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As mentioned above, real-time accurate monitoring of hydraulic parameters is key for flood forecasting. But for these hydraulic applications the sensors may have technological limitations, and so besides the regular requirements a number of additional ones are necessary [3]: • Power lifetime – the power sources are often not available at all the locations of interest. Moreover, these locations are usually unsafe, unprotected, and, if renewable energy devices are used, they are prone to vandalism or theft. Thus, it is imperative the use of sensor nodes with low-consumption, with standard batteries that should last several months cycle; • Sensor hardware compatibility – most hydrologic sensor nodes include a data logger device connected through a cable to the measurement instruments. The data logger must offer interfaces to communicate with a range of specific sensor hardware, which involves issues of power supply, and selective time for power dispatching, involving a optimal power management and facilitation of the expansion of connected instruments; • Reliability – the harsh weather conditions may cause failures in the measurements and in the wireless communication over the monitoring network. Backup mechanisms in local sensor data loggers must be used to avoid information losses in unexpected crashes; • Long-range communication – hydraulic measurement locations are commonly sparse over large areas, and not even in the same area of the control center. Thus, with these requirements, it is imperative to understand the different factors that affect the operation of the floating or diving sensors. Each type has its own and unique characteristics that should be reflected on the sensor’s measurements. A careful study on these factors should be conducted and a comparative analysis of the different characteristics should be carried out.
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Study Considerations and Future Approaches
The paper introduces an on-going research for the development of a framework that will support the dependability on aquatic real-time forecasting systems, starting by the study on the influence of external factors related with coastal and marine environment on the sensor network behavior, more specifically on the sensors measurements, and their consequences on the forecasts and alert systems that will be fed with the monitored data. The correct modeling of the impact of external factors such as weather events and conditions and marine interferences as a cause of measurement failures in interference-prone wireless sensor networks [6-8] is of the utmost importance to define and develop system solutions providing awareness of the delivered sensor data quality, aiming at achieving dependable reliable coastal and marine sensor networks. The first step is to identify and characterize the probable factors of disturbances, possibly done through a statistic analysis of the negative influence of natural environmental events on the measurement process of the available sensors on the field. This statistical validation of the measurements can offer a robust and inexpensive way
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to minimize the influence of these faults on future flood monitoring systems, providing a simple method to increase the fault tolerance aspect of those particular sensors, and the confidence of the data provided. A second step would be the development of solutions to automatically adjust the sensors measurements to each disturbance accordingly, contributing to an important increase on the quality of the measurements, thus supplying other layers of PMS systems with dependable monitoring data. However, on further steps, much has to be done in studying all aspects of the criticality of the sensor network in the monitoring process, including the timeliness requirements of the flood warning systems. Future work will include studying the real impact of networking faults and temporal uncertainties and devising solutions to deal with them, namely using approaches based on redundancy and sensor fusion. Acknowledgements. This study was funded by FCT through the Multiannual Funding Program and through PhD Grant (SFRH/BD/82489/2011) with the support of NTI group of DHA-LNEC and LaSIGE research unit, and also FCT’s project Pac:man (PTDC/AAC-AMB/113469/2009), SPRES (Interreg Atlantic Area Transnational Cooperation Programme 2007-2013 project SPRES - 2011-1/168), and FLAD (project CWOS).
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