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typical drawback of this approach is the considerable communication overhead introduced by exchanging so many messages This is an important issue in the context of energy constrained WSN nodes Event detection Event detection is similar to state monitoring in the sense that the sensor network itself is in charge of monitoring the environment in which its nodes are placed, and it is used to detect the occurrence of certain events With the event detection mechanism, exceptional situations can be detected and consequently reported Each sensor node has the task of detecting a possible event based on the data it obtains through its sensors, and through communication with other nodes Additionally, the occurrence of an event, along with its position, magnitude or other properties need to be reported.

In many situations, the value of these additional properties can only be determined, or more accurately be determined, when the sensor data of multiple sensor nodes are considered The detection and reporting of these tasks will need to be performed in an ef cient way, using only limited communication between the nodes, whenever data of interest is gathered, instead of reporting every sensed data sample Additionally, a description of the event and its properties will be needed to perform the task Event detection has been tried in several WSN applications already In [128], a description is given on a networked sensor array for monitoring volcanic eruptions Seismic and infrasonic data is gathered continuously, and when higher levels of activity are measured, the recently measured data from different sensors is correlated and analyzed to nd data on the recent event.

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The main reasons are that in the axiomatic approach a possibility distribution is defined for a random variable, but as yet we only have a sample space, and that there are, of course, random variables for which the possibility distribution is not an assignment of degrees of possibility to the elementary events of the underlying sample space Therefore we deviate from the terminology mentioned above and call the function that assigns a degree of possibility to each elementary event of a sample space the basic or elementary possibility assignment Analogously, we speak of a basic or elementary probability assignment This deviation in terminology goes less far, though, than one might think at first sight, since a basic possibility or probability assignment is, obviously, identical to a specific possibility or probability distribution, namely the one of the random variable that has the sample space as its range of values.

Embryos and larvae may be used in screening tests for aquatic toxicity testing to derive maximum acceptable toxicant concentrations. The most common end-points are hatching success, early larval survival and growth (Dave & Xiu, 1991; Hutchinson et al., 1994; Matta et al., 1997). Other studies include observations on the occurrence of developmental abnormalities in embryos and larvae (Call et al., 1985; Henry et al., 1997; Olivieri & Cooper, 1997) or larval behaviour (Olivieri & Cooper, 1997). It is generally accepted that embryos and larvae are very sensitive to contaminants and as a result whole life cycle toxicity tests have often been replaced by early life-stage tests. Much of the data that has been reported in the literature was derived from experiments carried out on embryos exposed after fertilisation for short time periods to environmentally unrealistic concentrations of contaminants. As noted above, embryos in the natural environment could be affected by xenobiotics in at least four additional ways, through genetic damage, via the yolk synthesised during oogenesis by exposed females, during the brief period between the shedding of the gametes and formation of the chorion and through feeding. For organic contaminants there is a high correlation between maternal transfer during oogenesis and the lipid content of the egg (Nimi, 1983). There are few studies of the impact of contaminants on gametes prior to fertilisation. There are some examples, however: reduced sperm motility was observed in trout after exposure to Hg (McIntyre, 1973) and there was reduced hatch in trout eggs when sperm from male trout exposed to Hg were used to fertilise the eggs (Birge et al., 1979).

The implementation described does not make use of in-network processing of the sensor data, but a feasibility analysis is performed Other uses of event detection are shown in systems that are concerned with the detection, identi cation, localization or tracking of objects in sensor elds [101, 123, 42, 31] In these applications, sensor nodes around the object or event of interest collaborate to nd the location of the object or event Fault tolerance and consensus Clouqueur et al in [26] presents two distinct approaches, value-fusion and decision-fusion, for achieving fault tolerance in collaborative target detection algorithms When performing a target detection task, multiple sensors in a region detect the presence of an object using sound, motion, or heat associated with the object of interest Therefore, combining their views and obtaining a consistent conclusion through the fusion process is highly desirable.

The value-fusion method consists of two phases: (i) exchanging the measured values and (ii) arriving to a consensus by computing the average of values and comparing it to a threshold In the presence of faulty sensors, in order to preserve precision and accuracy, the extreme values are dropped from the set that is going to be averaged In contrast, in the decision-fusion method, each device.

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