WIRELESS COMMUNICATIONS AND MOBILE COMPUTING Wirel. Commun. Mob. Comput. (2011) Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/wcm.1139 RESEARCH ARTICLE Interpolation techniques for building a continuous map from discrete wireless sensor network data Mohammad Hammoudeh 1 * , Robert Newman 2 , Christopher Dennett 2 and Sarah Mount 2 1 Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, U.K. 2 School of Computing and Information Technology,University of Wolverhampton, Wolverhampton, U.K. ABSTRACT Wireless sensor networks (WSNs) typically gather data at a discrete number of locations. However, it is desirable to be able to design applications and reason about the data in more abstract forms than in points of data. By bestowing the ability to predict inter-node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. This interpolation capability is realised as a service of the network. In this paper, the ‘map’ style of presentation has been identified as a suitable sense data visualisation format. Although map generation is essentially a problem of interpolation between points, a new WSN service, called the map generation service, which is based on a Shepard interpolation method, is presented. A modified Shepard method that aims to deal with the special characteristics of WSNs is proposed. It requires small storage, can be localised and integrates the information about the application domain to further reduce the map generation cost and improve the mapping accuracy. Empirical analysis has shown that the map generation service is an accurate, a flexible and an efficient method. Copyright © 2011 John Wiley & Sons, Ltd. KEYWORDS wireless sensor networks; services; visualisation; information extraction; interpolation *Correspondence Mohammad Hammoudeh, Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, U.K. E-mail: m.hammoudeh@mmu.ac.uk 1. INTRODUCTION With the increase in applications of wireless sensor net- works (WSNs), information extraction and visualisation have become a key issue to develop and to operate in these networks. WSNs typically gather data at a discrete num- ber of locations. By bestowing the ability to predict inter- node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. Not all information that is collected from a WSN comes ready to use. Often, WSNs field data collection takes the form of single points that need to be pro- cessed to have a continuous data presentation. Interpola- tion describes this process of taking many single points and building a complete surface, the inter-node gaps being filled based on the spatial statistics of the observation points. Interpolating these points will produce more use- ful information such as maps related to water chemi- cal content for the end-user. The ability to interpolate point information is necessary for carrying out mapping tasks. The problem of map generation is essentially a prob- lem of interpolation from sparse and irregular points. This interpolation capability is realised as a service of the net- work. In this paper, one particular interpolation approach, Shepard interpolation [1], is examined and shown to be suitable for the constraints imposed by the nature of WSNs. Visual aspects, sensitivity to parameters and timing requirements were used to test the characteristics of this method. The rest of the paper is organised as follows. Section 2 explains why map is a suitable discrete data visualisa- tion format. Sections 3 and 4 provide a brief description of map generation algorithms and mapping applications in the literature, respectively. Section 5 defines the problem on map generation. Section 6 defines Shepard interpolation method. Sections 7 and 8 describe the modified Shepard map generation. Evaluation of the map generation service (MGS) is presented in Section 9. Example application of Copyright © 2011 John Wiley & Sons, Ltd.