# Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks
## 3 Event Detection and Sensory Data Aggregation
However, energy efficiency, event coverage and source determination are not the focus. To summarize, although event coverage detection has been explored relatively extensively in terrestrial WSNs, there are few techniques addressing this challenge in underwater WSNs nowadays. This article proposes a technique for localizing events in the underwater environment and aims to identify potential event sources for supporting the response enactment. Traditional techniques on query processing may facilitate the event coverage detection in underwater WSNs. In [22], a sub-region query processing mechanism is proposed, since a sub-region, rather than the whole network region, may be of interest for certain applications. Whether a sensor node is located within an interesting sub-region or not is determined through underwater localization techniques [23]. A routing tree is constructed where hop counts are adopted to represent the distance for sensory data routing to sink node(s). The energy efficiency on routing tree maintenance is of importance since sensor nodes may drift along the water dynamics. Query processing is effective and more energy efficient when multiple queries are issued by users concurrently, and the results of some queries can be reused for answering other queries. Leveraging this observation, the authors proposed a multiple query result merging scheme for reducing the energy consumption in underwater sensory data transmissions [37]. Specifically, queries are rewritten as their simplest forms, which are easier for conducting the queries. When the results of these queries are returned to \(S\!N\), they can be reused for queries with the same data fields and relations. It is argued that this scheme can decrease redundant message transmissions and reduce the energy consumption. In fact, our event coverage detection technique is complementary to query processing mechanisms, which aim to gather and route sensory data packets to sink node(s) in an energy-efficient manner. Event coverage detection is related to the problem of network boundary determination. In fact, they are similar somehow when events occur in the whole network region. A boundary detection mechanism in three-dimensional wireless networks has been proposed in [18], where sensor nodes on the boundaries are identified based on local information within a one-hop neighborhood. An algorithm that locally constructs planarized triangular meshes is developed and extended from two- to three-dimensions for producing the boundary surface. This work is interesting and inspiring for us to develop the technique in this article. Note that this technique applies to well-connected networks, where no degenerated line segments exist. Specifically, given a line segment between two sensor nodes (\(w_{i}\) and \(w_{j}\)), there must be at least one node from which the distances to \(uv_{i}\) and \(w_{j}\) are less than the distance between \(w_{i}\) and \(w_{j}\). Due to the sparsity of sensor nodes to be deployed in underwater WSNs, the constraint of well-connected networks may not be satisfied. The network coverage quality is studied with respect to the number of sensor nodes deployed in underwater WSNs [38]. Sensor nodes are deployed at the seabed initially and can move vertically in three dimensions for adjusting their depths and locations. An optimal network coverage can be achieved through the adjustment of sensor nodes, when the coverage can hardly be improvedany further. Underwater sensor node deployment for guaranteeing optimal monitoring quality is a challenge in underwater UWSNs [39]. To solve this problem, a depth adjustment algorithm based on a connected tree is proposed, where the parent-child relations specified in the connected tree are adopted for the maintenance of network connectivity and the detection and optimization of network coverage. A connected tree is similar to our routing tree somehow. It is observed that AUVs are increasingly used for the monitoring of vast ocean space.