In the need to conserve communication energy we consider one bit aggregation in wireless sensor network (WSN) in the context of event detection. In this paper we propose a novel Adaptive Weighted Aggregation Scheme (AdWAS) for star as well as tree topology. We compare the performance of the proposed adaptive weighted aggregation scheme with existing one bit non-adaptive aggregation schemes. In non-adaptive schemes, a slight variation in the topology or performance indices necessitate recalculation of the initial setup. However, in the proposed adaptive scheme we just need to fine tune the weights starting from the previously adapted weights to compensate for any small variation in the topology. Moreover, there is hardly any performance degradation when using AdWAS. This clearly makes the adaptive setup more appealing.
The late blight disease is the most common disease in potato, which is caused by the pathogen Phytopthora infestans. In this paper, a novel method to collect symptoms of the disease, as observed by the farmers, using a mobile phone application has been presented. A cumulative composite risk index (CCRI) obtained from more than one existing disease forecast models is validated from the actual late blight queries received from the farmers. The main contribution of the paper is a protocol that combines the symptoms based diagnostic approach along with the plant disease forecasting models resulting in detection of Potato late blight with higher accuracy. This in turn reduces the disease risk along with avoiding the unnecessary application of fungicide.
In our work, we consider a querying application of a Multihop Cell phone Sensor Networks (MCpSN). It requires data to be sensed within a time window and further uploaded at the Querying Access Point within a time deadline. Considering a Random Waypoint distribution of cell phone users, we propose a novel, energy-efficient Spatio-Temporal Power Adaptive (ST P A) protocol for this application. ST P A is compared to purely spatially/temporally adaptive schemes through simulations.
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