An agent-based wireless sensor network for water quality data collection

Abstract

Future generation intelligent systems will harvest embedded intelligence as a means of delivering new and innovative services in diverse domains. Amongst the most challenging scenarios are those that consist of Wireless Sensor Networks (WSNs) as their functional operating constraints are significant. This paper proposes the use of in-network data aggregation techniques to enable the efficient acquisition of data in a water quality forecasting WSN application. Such an approach reduces the energy required for data transmission by collecting statistics from the network rather than analyzing the raw data centrally. Specifically, clustering points, where aggregation occurs, are modelled as mobile intelligent agents. © 2012 Springer-Verlag.